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- evaluation/agentic_eval_48.json +48 -56
- evaluation/agentic_fidelity_vs_bf16.json +9 -9
- evaluation/behavior_probes_16.json +132 -158
- evaluation/kl_vs_fp8.json +18 -18
- evaluation/native_transcripts_vs_bf16.json +611 -0
- evaluation/scale_correction_report.json +884 -0
- evaluation/served_reasoning_matrix.json +786 -0
- jang_config.json +12 -0
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README.md
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# JANGQ-AI/GLM-5.3-Flash-JANGH2
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**GLM-5.3-Flash for 128 GB Macs.** Same size as our previous affine release, with **2.
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points top-1**, and faster decode.
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A JANGH bundle of [zai-org/GLM-5.3-Flash](https://huggingface.co/zai-org/GLM-5.3-Flash): a 300B-class MoE (288
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precision.
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- **Vision tower**: kept in bf16.
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This replaces `JANGQ-AI/GLM-5.3-Flash-JANG` and `-JANG-MTP` (and was briefly published as `GLM-5.3-Flash-JANGTQ2`).
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## JANGH vs JANGTQ
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| Bundle | Size | median KL ↓ | mean KL ↓ | p90 / p95 / p99 ↓ | top-1 ↑ | top-5 ↑ | top-10 ↑ |
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| **GLM-5.3-Flash-JANGH2** | **95.89 GiB** | **0.
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| GLM-5.3-Flash-JANG (affine, previous release) | 95.35 GiB | 0.0882 | 0.528 | 1.50 / 2.55 / 5.67 | 78.6% | 94.6% | 96.8% |
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| orcarouter GLM-5.3-Flash-MLX `2bit-lite` ¹ | 95.4 GiB | 0.2122 | 0.83 | — | 71.4% | 90.8% | 94.3% |
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¹ Measured earlier on the same 20 prompts (15,850 positions), loading its shipped quantized weights natively.
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## Agentic fidelity vs the bf16 model itself
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Scored against the full bf16 model, run layer by layer from disk. 72 held-out tool-use conversations (25,867
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positions; tools and phrasings disjoint from calibration), including 114 "call a tool or answer?" decision points.
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| | **JANGH2** | affine JANG (previous) |
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| median KL vs bf16 | **0.
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| top-1 agreement with bf16 | **
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| tool-call decisions: same choice as bf16 | **50 / 50** | 50 / 50 |
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| median P(`<tool_call>`) at call points (bf16: 0.998) | **0.999** | 0.981 |
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| lowest P(`<tool_call>`) at a call point | **0.
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| answer decisions: same next token as bf16 | **
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| decisions flipped call ↔ answer vs bf16 | **0** | 3 |
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These are synthetic agent transcripts, so absolute KL is high for every bundle; read
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The calibration set includes agent-style conversations from the same generator (different tools and wording), so
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part of this gain is in-distribution. The FP8 table above is independent of that.
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| | **JANGH2** | affine JANG (previous) |
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| decode (tok/s) | **27.
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| prefill, ~5.2k-token prompt (tok/s) |
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| peak memory while serving | 96.7 GiB | 96.1 GiB |
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Two interleaved runs per bundle, same runtime build, each run the median of 3 probes on a never-seen prompt.
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Decode is **~
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## What's in the bundle
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- **Vision + video**: full bf16 vision tower + the consolidated image/video processor config.
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- **Thinking + agentic**:
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- Thinking is ON by default (the template opens `<think>`).
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- Reasoning efforts are **`low` / `high` / `max`** (default `max`). There is no `medium`: the template renders any
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other value as Max.
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- `clear_thinking=false` preserves thinking in history.
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- **Tool calls**: GLM's XML dialect (`<tool_call>name<arg_key>…</arg_key><arg_value>…</arg_value></tool_call>`),
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declared as `tool_parser: glm_xml_args`; tool results render as `<|observation|>`. Hermes-style JSON parsers will
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- plus a bf16 agentic capture (448 GLM-template tool conversations), with evaluation prompts held out
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- Experts: JANGH (odd-cubic codebook, fp16 per-row scale, Hadamard-32 rotation), GPTQ on all 42 MoE layers with a
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per-expert importance matrix, bit allocation measured per layer (gate/up 2-3 bit, down 2-3 bit)
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Quantized and validated by **Jinho Jang** — eric@jangq.ai
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# JANGQ-AI/GLM-5.3-Flash-JANGH2
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**GLM-5.3-Flash for 128 GB Macs.** Same size as our previous affine release, with **2.9x lower median KL**, **+5.3
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points top-1**, and faster decode.
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A JANGH bundle of [zai-org/GLM-5.3-Flash](https://huggingface.co/zai-org/GLM-5.3-Flash): a 300B-class MoE (288
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precision.
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- **Vision tower**: kept in bf16.
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## Revision 2: long reasoning now ends on its own
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The first upload could not end long reasoning. After a few thousand reasoning tokens the probability of `</think>` was
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hundreds to thousands of times too low, so the model kept thinking, and the text eventually degraded into repetition.
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With the default effort (`max`) that range is reached on ordinary tasks.
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Cause: error-minimizing row scales shrink every low-bit matrix a little (12% at 2 bits). Three matrices per expert
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and 42 MoE layers deep, that weakens exactly the strong, late decisions, and "stop thinking" is one of them.
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Revision 2 changes **only the row scales of the routed experts** (126 small tensors). The quantized codes, the size,
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the format and the speed are unchanged, and no runtime change is needed.
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| where the reference model ends its reasoning | bf16 | **revision 2** | revision 1 | affine JANG (previous) |
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| P(`</think>`), held-out design task, after 8,025 reasoning tokens | 0.82 | **0.75** | 0.03 | 0.02 |
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| P(`</think>`), coding task, after 3,288 reasoning tokens | 0.99 | **0.94** | 0.19 | - |
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| long design prompt, served, vendor sampling: reasoning ended by the model | **revision 2** | revision 1 |
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| effort `low` | **3 / 3** | 0 / 5 |
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| effort `high` | **2 / 2** | - |
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| effort `max` (40k-token budget; the reference model needs 17-23k reasoning tokens here) | **1 / 1** | 0 / 2 |
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Your copy is revision 2 if `jang_config.json` has a `scale_correction` entry.
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This replaces `JANGQ-AI/GLM-5.3-Flash-JANG` and `-JANG-MTP` (and was briefly published as `GLM-5.3-Flash-JANGTQ2`).
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## JANGH vs JANGTQ
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| Bundle | Size | median KL ↓ | mean KL ↓ | p90 / p95 / p99 ↓ | top-1 ↑ | top-5 ↑ | top-10 ↑ |
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| **GLM-5.3-Flash-JANGH2** | **95.89 GiB** | **0.0301** | **0.376** | **0.98 / 1.97 / 5.24** | **83.9%** | **96.8%** | **98.3%** |
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| GLM-5.3-Flash-JANG (affine, previous release) | 95.35 GiB | 0.0882 | 0.528 | 1.50 / 2.55 / 5.67 | 78.6% | 94.6% | 96.8% |
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| orcarouter GLM-5.3-Flash-MLX `2bit-lite` ¹ | 95.4 GiB | 0.2122 | 0.83 | — | 71.4% | 90.8% | 94.3% |
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¹ Measured earlier on the same 20 prompts (15,850 positions), loading its shipped quantized weights natively.
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## Fidelity vs the bf16 model on real transcripts
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Scored against the full bf16 model, run layer by layer from disk. 16 held-out transcripts written by the model
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itself in its native format: long design and coding reasoning, and multi-step tool conversations with tool results
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(60,243 assistant positions).
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| top-1 agreement with bf16 | **82.6%** | 77.1% |
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| median KL vs bf16 | **0.069** | 0.158 |
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| mean KL vs bf16 | **0.218** | 0.356 |
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| tool-call points: `<tool_call>` is the top choice (bf16 agrees on all 41) | **40 / 41** | 35 / 41 |
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| median P(`<tool_call>`) at those points | **0.9998** | 0.968 |
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| lowest P(`<tool_call>`) at those points | 0.165 | **0.245** |
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## Agentic fidelity vs the bf16 model itself
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Scored against the full bf16 model, run layer by layer from disk. 72 held-out tool-use conversations (25,867
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positions; tools and phrasings disjoint from calibration), including 114 "call a tool or answer?" decision points.
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| | **JANGH2** | affine JANG (previous) |
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| median KL vs bf16 | **0.579** | 0.595 |
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| top-1 agreement with bf16 | **57.3%** | 54.9% |
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| tool-call decisions: same choice as bf16 | **50 / 50** | 50 / 50 |
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| median P(`<tool_call>`) at call points (bf16: 0.998) | **0.999** | 0.981 |
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| lowest P(`<tool_call>`) at a call point | **0.914** | 0.784 |
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| answer decisions: same next token as bf16 | **87.5%** | 50.0% |
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| decisions flipped call ↔ answer vs bf16 | **0** | 3 |
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These are synthetic agent transcripts rendered with empty think blocks, so absolute KL is high for every bundle; read
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the columns against each other. Revision 2 gives up fidelity on this set (revision 1: median KL 0.145, top-1 68.7%) in
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exchange for ending long reasoning; on assistant output alone top-1 is 92.3% (revision 1: 94.4%). Tool decisions are
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unchanged.
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The calibration set includes agent-style conversations from the same generator (different tools and wording), so
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part of this gain is in-distribution. The FP8 table above is independent of that.
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| | **JANGH2** | affine JANG (previous) |
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| decode (tok/s) | **27.71 / 27.71** | 26.81 / 26.85 |
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| prefill, ~5.2k-token prompt (tok/s) | 339 / 361 | 421 / 416 |
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| peak memory while serving | 96.7 GiB | 96.1 GiB |
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Two interleaved runs per bundle, same runtime build, each run the median of 3 probes on a never-seen prompt.
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Decode is **~3% faster** than the affine bundle; long-prompt prefill is currently ~15% slower.
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## What's in the bundle
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- **Vision + video**: full bf16 vision tower + the consolidated image/video processor config.
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- **Thinking + agentic**:
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- Thinking is ON by default (the template opens `<think>`).
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- Reasoning efforts are **`low` / `high` / `max`** (default `max`). There is no `medium`: the template renders any
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other value, and a missing value, as Max.
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- Budget for thinking: the model reasons for 8-10k tokens at `low` and 17-23k at `max` on a large design task, and
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for 4-6k at `max` even on a small coding task. Use `low` or `high` for interactive work and a generous `max_tokens`.
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- `clear_thinking=false` preserves thinking in history.
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- **Tool calls**: GLM's XML dialect (`<tool_call>name<arg_key>…</arg_key><arg_value>…</arg_value></tool_call>`),
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declared as `tool_parser: glm_xml_args`; tool results render as `<|observation|>`. Hermes-style JSON parsers will
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- plus a bf16 agentic capture (448 GLM-template tool conversations), with evaluation prompts held out
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- Experts: JANGH (odd-cubic codebook, fp16 per-row scale, Hadamard-32 rotation), GPTQ on all 42 MoE layers with a
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per-expert importance matrix, bit allocation measured per layer (gate/up 2-3 bit, down 2-3 bit)
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- Revision 2: row scales corrected to unit gain along the source row (`jang_config.json` → `scale_correction`)
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Quantized and validated by **Jinho Jang** — eric@jangq.ai
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| 674 |
},
|
| 675 |
{
|
| 676 |
"task": 10,
|
|
|
|
| 683 |
{
|
| 684 |
"name": "get_weather",
|
| 685 |
"arguments": "{\"city\": \"Osaka\", \"unit\": \"fahrenheit\"}"
|
|
|
|
|
|
|
|
|
|
|
|
|
| 686 |
}
|
| 687 |
],
|
| 688 |
"pass": true,
|
| 689 |
+
"seconds": 5.355681207962334
|
| 690 |
},
|
| 691 |
{
|
| 692 |
"task": 10,
|
|
|
|
| 699 |
{
|
| 700 |
"name": "get_weather",
|
| 701 |
"arguments": "{\"city\": \"Osaka\", \"unit\": \"fahrenheit\"}"
|
|
|
|
|
|
|
|
|
|
|
|
|
| 702 |
}
|
| 703 |
],
|
| 704 |
"pass": true,
|
| 705 |
+
"seconds": 5.431290292006452
|
| 706 |
},
|
| 707 |
{
|
| 708 |
"task": 11,
|
|
|
|
| 718 |
}
|
| 719 |
],
|
| 720 |
"pass": true,
|
| 721 |
+
"seconds": 2.563839749956969
|
| 722 |
},
|
| 723 |
{
|
| 724 |
"task": 11,
|
|
|
|
| 734 |
}
|
| 735 |
],
|
| 736 |
"pass": true,
|
| 737 |
+
"seconds": 0.6448427090072073
|
| 738 |
},
|
| 739 |
{
|
| 740 |
"task": 11,
|
|
|
|
| 750 |
}
|
| 751 |
],
|
| 752 |
"pass": true,
|
| 753 |
+
"seconds": 3.3341305830399506
|
| 754 |
},
|
| 755 |
{
|
| 756 |
"task": 11,
|
|
|
|
| 766 |
}
|
| 767 |
],
|
| 768 |
"pass": true,
|
| 769 |
+
"seconds": 1.3245216659852304
|
| 770 |
}
|
| 771 |
],
|
| 772 |
"score": {
|
evaluation/agentic_fidelity_vs_bf16.json
CHANGED
|
@@ -1,23 +1,23 @@
|
|
| 1 |
{
|
| 2 |
-
"bundle": "GLM-5.3-Flash-
|
| 3 |
"positions": 25867,
|
| 4 |
-
"median_kl": 0.
|
| 5 |
-
"mean_kl":
|
| 6 |
-
"p90":
|
| 7 |
-
"p99":
|
| 8 |
-
"top1_pct":
|
| 9 |
"decisions": {
|
| 10 |
"call": {
|
| 11 |
"n": 50,
|
| 12 |
"argmax_agree_pct": 100.0,
|
| 13 |
"call_answer_flips": 0,
|
| 14 |
"median_p_toolcall_ref": 0.9978413073418699,
|
| 15 |
-
"median_p_toolcall_q": 0.
|
| 16 |
-
"min_p_toolcall_q": 0.
|
| 17 |
},
|
| 18 |
"answer": {
|
| 19 |
"n": 64,
|
| 20 |
-
"argmax_agree_pct":
|
| 21 |
"call_answer_flips": 0
|
| 22 |
},
|
| 23 |
"end_think": {
|
|
|
|
| 1 |
{
|
| 2 |
+
"bundle": "GLM-5.3-Flash-JANGH2 (revision 2)",
|
| 3 |
"positions": 25867,
|
| 4 |
+
"median_kl": 0.5786294944794285,
|
| 5 |
+
"mean_kl": 1.9186985662251947,
|
| 6 |
+
"p90": 5.704473737727082,
|
| 7 |
+
"p99": 15.565772008253802,
|
| 8 |
+
"top1_pct": 57.33560134534349,
|
| 9 |
"decisions": {
|
| 10 |
"call": {
|
| 11 |
"n": 50,
|
| 12 |
"argmax_agree_pct": 100.0,
|
| 13 |
"call_answer_flips": 0,
|
| 14 |
"median_p_toolcall_ref": 0.9978413073418699,
|
| 15 |
+
"median_p_toolcall_q": 0.9986819378506473,
|
| 16 |
+
"min_p_toolcall_q": 0.9143006757904859
|
| 17 |
},
|
| 18 |
"answer": {
|
| 19 |
"n": 64,
|
| 20 |
+
"argmax_agree_pct": 87.5,
|
| 21 |
"call_answer_flips": 0
|
| 22 |
},
|
| 23 |
"end_think": {
|
evaluation/behavior_probes_16.json
CHANGED
|
@@ -2,7 +2,7 @@
|
|
| 2 |
{
|
| 3 |
"name": "math thinking_on",
|
| 4 |
"request": {
|
| 5 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 6 |
"messages": [
|
| 7 |
{
|
| 8 |
"role": "system",
|
|
@@ -20,16 +20,16 @@
|
|
| 20 |
}
|
| 21 |
},
|
| 22 |
"response": {
|
| 23 |
-
"id": "chatcmpl-
|
| 24 |
"object": "chat.completion",
|
| 25 |
-
"created":
|
| 26 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 27 |
"choices": [
|
| 28 |
{
|
| 29 |
"index": 0,
|
| 30 |
"message": {
|
| 31 |
"role": "assistant",
|
| 32 |
-
"content": "17 \u00d7 19 = **323**",
|
| 33 |
"tool_calls": null,
|
| 34 |
"reasoning_content": "17 \u00d7 19 = 17 \u00d7 20 - 17 = 340 - 17 = 323"
|
| 35 |
},
|
|
@@ -39,23 +39,20 @@
|
|
| 39 |
],
|
| 40 |
"usage": {
|
| 41 |
"prompt_tokens": 28,
|
| 42 |
-
"completion_tokens":
|
| 43 |
-
"total_tokens":
|
| 44 |
-
"prompt_tokens_details":
|
| 45 |
-
"cached_tokens": 27,
|
| 46 |
-
"cache_detail": "native-glm+disk"
|
| 47 |
-
}
|
| 48 |
},
|
| 49 |
"warnings": null,
|
| 50 |
"context_exhaustion": null
|
| 51 |
},
|
| 52 |
"pass": true,
|
| 53 |
-
"seconds":
|
| 54 |
},
|
| 55 |
{
|
| 56 |
"name": "math followup thinking_off",
|
| 57 |
"request": {
|
| 58 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 59 |
"messages": [
|
| 60 |
{
|
| 61 |
"role": "system",
|
|
@@ -67,7 +64,7 @@
|
|
| 67 |
},
|
| 68 |
{
|
| 69 |
"role": "assistant",
|
| 70 |
-
"content": "17 \u00d7 19 = **323**",
|
| 71 |
"tool_calls": null,
|
| 72 |
"reasoning_content": "17 \u00d7 19 = 17 \u00d7 20 - 17 = 340 - 17 = 323"
|
| 73 |
},
|
|
@@ -83,10 +80,10 @@
|
|
| 83 |
}
|
| 84 |
},
|
| 85 |
"response": {
|
| 86 |
-
"id": "chatcmpl-
|
| 87 |
"object": "chat.completion",
|
| 88 |
-
"created":
|
| 89 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 90 |
"choices": [
|
| 91 |
{
|
| 92 |
"index": 0,
|
|
@@ -101,21 +98,21 @@
|
|
| 101 |
}
|
| 102 |
],
|
| 103 |
"usage": {
|
| 104 |
-
"prompt_tokens":
|
| 105 |
"completion_tokens": 10,
|
| 106 |
-
"total_tokens":
|
| 107 |
"prompt_tokens_details": null
|
| 108 |
},
|
| 109 |
"warnings": null,
|
| 110 |
"context_exhaustion": null
|
| 111 |
},
|
| 112 |
"pass": true,
|
| 113 |
-
"seconds": 1.
|
| 114 |
},
|
| 115 |
{
|
| 116 |
"name": "tool p1 think=False choice=required",
|
| 117 |
"request": {
|
| 118 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 119 |
"messages": [
|
| 120 |
{
|
| 121 |
"role": "user",
|
|
@@ -151,10 +148,10 @@
|
|
| 151 |
}
|
| 152 |
},
|
| 153 |
"response": {
|
| 154 |
-
"id": "chatcmpl-
|
| 155 |
"object": "chat.completion",
|
| 156 |
-
"created":
|
| 157 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 158 |
"choices": [
|
| 159 |
{
|
| 160 |
"index": 0,
|
|
@@ -162,7 +159,7 @@
|
|
| 162 |
"role": "assistant",
|
| 163 |
"tool_calls": [
|
| 164 |
{
|
| 165 |
-
"id": "
|
| 166 |
"type": "function",
|
| 167 |
"function": {
|
| 168 |
"name": "lookup_code",
|
|
@@ -182,12 +179,12 @@
|
|
| 182 |
}
|
| 183 |
},
|
| 184 |
"pass": true,
|
| 185 |
-
"seconds": 1.
|
| 186 |
},
|
| 187 |
{
|
| 188 |
"name": "tool p1 think=False choice=auto",
|
| 189 |
"request": {
|
| 190 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 191 |
"messages": [
|
| 192 |
{
|
| 193 |
"role": "user",
|
|
@@ -223,10 +220,10 @@
|
|
| 223 |
}
|
| 224 |
},
|
| 225 |
"response": {
|
| 226 |
-
"id": "chatcmpl-
|
| 227 |
"object": "chat.completion",
|
| 228 |
-
"created":
|
| 229 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 230 |
"choices": [
|
| 231 |
{
|
| 232 |
"index": 0,
|
|
@@ -234,7 +231,7 @@
|
|
| 234 |
"role": "assistant",
|
| 235 |
"tool_calls": [
|
| 236 |
{
|
| 237 |
-
"id": "
|
| 238 |
"type": "function",
|
| 239 |
"function": {
|
| 240 |
"name": "lookup_code",
|
|
@@ -258,12 +255,12 @@
|
|
| 258 |
}
|
| 259 |
},
|
| 260 |
"pass": true,
|
| 261 |
-
"seconds": 0.
|
| 262 |
},
|
| 263 |
{
|
| 264 |
"name": "tool p1 think=True choice=required",
|
| 265 |
"request": {
|
| 266 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 267 |
"messages": [
|
| 268 |
{
|
| 269 |
"role": "user",
|
|
@@ -299,10 +296,10 @@
|
|
| 299 |
}
|
| 300 |
},
|
| 301 |
"response": {
|
| 302 |
-
"id": "chatcmpl-
|
| 303 |
"object": "chat.completion",
|
| 304 |
-
"created":
|
| 305 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 306 |
"choices": [
|
| 307 |
{
|
| 308 |
"index": 0,
|
|
@@ -310,7 +307,7 @@
|
|
| 310 |
"role": "assistant",
|
| 311 |
"tool_calls": [
|
| 312 |
{
|
| 313 |
-
"id": "
|
| 314 |
"type": "function",
|
| 315 |
"function": {
|
| 316 |
"name": "lookup_code",
|
|
@@ -318,7 +315,7 @@
|
|
| 318 |
}
|
| 319 |
}
|
| 320 |
],
|
| 321 |
-
"reasoning_content": "The user wants me to look up the code for label \"alpha\" using the lookup_code tool.
|
| 322 |
"content": null
|
| 323 |
},
|
| 324 |
"finish_reason": "tool_calls"
|
|
@@ -326,21 +323,17 @@
|
|
| 326 |
],
|
| 327 |
"usage": {
|
| 328 |
"prompt_tokens": 193,
|
| 329 |
-
"completion_tokens":
|
| 330 |
-
"total_tokens":
|
| 331 |
-
"prompt_tokens_details": {
|
| 332 |
-
"cached_tokens": 192,
|
| 333 |
-
"cache_detail": "native-glm+disk"
|
| 334 |
-
}
|
| 335 |
}
|
| 336 |
},
|
| 337 |
"pass": true,
|
| 338 |
-
"seconds":
|
| 339 |
},
|
| 340 |
{
|
| 341 |
"name": "tool p1 think=True choice=auto",
|
| 342 |
"request": {
|
| 343 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 344 |
"messages": [
|
| 345 |
{
|
| 346 |
"role": "user",
|
|
@@ -376,10 +369,10 @@
|
|
| 376 |
}
|
| 377 |
},
|
| 378 |
"response": {
|
| 379 |
-
"id": "chatcmpl-
|
| 380 |
"object": "chat.completion",
|
| 381 |
-
"created":
|
| 382 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 383 |
"choices": [
|
| 384 |
{
|
| 385 |
"index": 0,
|
|
@@ -387,7 +380,7 @@
|
|
| 387 |
"role": "assistant",
|
| 388 |
"tool_calls": [
|
| 389 |
{
|
| 390 |
-
"id": "
|
| 391 |
"type": "function",
|
| 392 |
"function": {
|
| 393 |
"name": "lookup_code",
|
|
@@ -395,7 +388,7 @@
|
|
| 395 |
}
|
| 396 |
}
|
| 397 |
],
|
| 398 |
-
"reasoning_content": "The user wants me to look up the code for label \"alpha\" using the lookup_code tool.
|
| 399 |
"content": null
|
| 400 |
},
|
| 401 |
"finish_reason": "tool_calls"
|
|
@@ -403,8 +396,8 @@
|
|
| 403 |
],
|
| 404 |
"usage": {
|
| 405 |
"prompt_tokens": 193,
|
| 406 |
-
"completion_tokens":
|
| 407 |
-
"total_tokens":
|
| 408 |
"prompt_tokens_details": {
|
| 409 |
"cached_tokens": 192,
|
| 410 |
"cache_detail": "native-glm+disk"
|
|
@@ -412,12 +405,12 @@
|
|
| 412 |
}
|
| 413 |
},
|
| 414 |
"pass": true,
|
| 415 |
-
"seconds": 1.
|
| 416 |
},
|
| 417 |
{
|
| 418 |
"name": "tool p2 think=False choice=required",
|
| 419 |
"request": {
|
| 420 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 421 |
"messages": [
|
| 422 |
{
|
| 423 |
"role": "user",
|
|
@@ -453,10 +446,10 @@
|
|
| 453 |
}
|
| 454 |
},
|
| 455 |
"response": {
|
| 456 |
-
"id": "chatcmpl-
|
| 457 |
"object": "chat.completion",
|
| 458 |
-
"created":
|
| 459 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 460 |
"choices": [
|
| 461 |
{
|
| 462 |
"index": 0,
|
|
@@ -464,7 +457,7 @@
|
|
| 464 |
"role": "assistant",
|
| 465 |
"tool_calls": [
|
| 466 |
{
|
| 467 |
-
"id": "
|
| 468 |
"type": "function",
|
| 469 |
"function": {
|
| 470 |
"name": "lookup_code",
|
|
@@ -484,12 +477,12 @@
|
|
| 484 |
}
|
| 485 |
},
|
| 486 |
"pass": true,
|
| 487 |
-
"seconds": 1.
|
| 488 |
},
|
| 489 |
{
|
| 490 |
"name": "tool p2 think=False choice=auto",
|
| 491 |
"request": {
|
| 492 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 493 |
"messages": [
|
| 494 |
{
|
| 495 |
"role": "user",
|
|
@@ -525,10 +518,10 @@
|
|
| 525 |
}
|
| 526 |
},
|
| 527 |
"response": {
|
| 528 |
-
"id": "chatcmpl-
|
| 529 |
"object": "chat.completion",
|
| 530 |
-
"created":
|
| 531 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 532 |
"choices": [
|
| 533 |
{
|
| 534 |
"index": 0,
|
|
@@ -536,7 +529,7 @@
|
|
| 536 |
"role": "assistant",
|
| 537 |
"tool_calls": [
|
| 538 |
{
|
| 539 |
-
"id": "
|
| 540 |
"type": "function",
|
| 541 |
"function": {
|
| 542 |
"name": "lookup_code",
|
|
@@ -560,12 +553,12 @@
|
|
| 560 |
}
|
| 561 |
},
|
| 562 |
"pass": true,
|
| 563 |
-
"seconds": 0.
|
| 564 |
},
|
| 565 |
{
|
| 566 |
"name": "tool p2 think=True choice=required",
|
| 567 |
"request": {
|
| 568 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 569 |
"messages": [
|
| 570 |
{
|
| 571 |
"role": "user",
|
|
@@ -601,10 +594,10 @@
|
|
| 601 |
}
|
| 602 |
},
|
| 603 |
"response": {
|
| 604 |
-
"id": "chatcmpl-
|
| 605 |
"object": "chat.completion",
|
| 606 |
-
"created":
|
| 607 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 608 |
"choices": [
|
| 609 |
{
|
| 610 |
"index": 0,
|
|
@@ -612,7 +605,7 @@
|
|
| 612 |
"role": "assistant",
|
| 613 |
"tool_calls": [
|
| 614 |
{
|
| 615 |
-
"id": "
|
| 616 |
"type": "function",
|
| 617 |
"function": {
|
| 618 |
"name": "lookup_code",
|
|
@@ -620,7 +613,7 @@
|
|
| 620 |
}
|
| 621 |
}
|
| 622 |
],
|
| 623 |
-
"reasoning_content": "The user wants the secret code for the label 'alpha'. I
|
| 624 |
"content": null
|
| 625 |
},
|
| 626 |
"finish_reason": "tool_calls"
|
|
@@ -628,21 +621,17 @@
|
|
| 628 |
],
|
| 629 |
"usage": {
|
| 630 |
"prompt_tokens": 200,
|
| 631 |
-
"completion_tokens":
|
| 632 |
-
"total_tokens":
|
| 633 |
-
"prompt_tokens_details": {
|
| 634 |
-
"cached_tokens": 199,
|
| 635 |
-
"cache_detail": "native-glm+disk"
|
| 636 |
-
}
|
| 637 |
}
|
| 638 |
},
|
| 639 |
"pass": true,
|
| 640 |
-
"seconds":
|
| 641 |
},
|
| 642 |
{
|
| 643 |
"name": "tool p2 think=True choice=auto",
|
| 644 |
"request": {
|
| 645 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 646 |
"messages": [
|
| 647 |
{
|
| 648 |
"role": "user",
|
|
@@ -678,10 +667,10 @@
|
|
| 678 |
}
|
| 679 |
},
|
| 680 |
"response": {
|
| 681 |
-
"id": "chatcmpl-
|
| 682 |
"object": "chat.completion",
|
| 683 |
-
"created":
|
| 684 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 685 |
"choices": [
|
| 686 |
{
|
| 687 |
"index": 0,
|
|
@@ -689,7 +678,7 @@
|
|
| 689 |
"role": "assistant",
|
| 690 |
"tool_calls": [
|
| 691 |
{
|
| 692 |
-
"id": "
|
| 693 |
"type": "function",
|
| 694 |
"function": {
|
| 695 |
"name": "lookup_code",
|
|
@@ -697,7 +686,7 @@
|
|
| 697 |
}
|
| 698 |
}
|
| 699 |
],
|
| 700 |
-
"reasoning_content": "The user wants the secret code for the label 'alpha'. I
|
| 701 |
"content": null
|
| 702 |
},
|
| 703 |
"finish_reason": "tool_calls"
|
|
@@ -705,8 +694,8 @@
|
|
| 705 |
],
|
| 706 |
"usage": {
|
| 707 |
"prompt_tokens": 200,
|
| 708 |
-
"completion_tokens":
|
| 709 |
-
"total_tokens":
|
| 710 |
"prompt_tokens_details": {
|
| 711 |
"cached_tokens": 199,
|
| 712 |
"cache_detail": "native-glm+disk"
|
|
@@ -714,12 +703,12 @@
|
|
| 714 |
}
|
| 715 |
},
|
| 716 |
"pass": true,
|
| 717 |
-
"seconds": 1.
|
| 718 |
},
|
| 719 |
{
|
| 720 |
"name": "tool result round trip",
|
| 721 |
"request": {
|
| 722 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 723 |
"messages": [
|
| 724 |
{
|
| 725 |
"role": "user",
|
|
@@ -729,7 +718,7 @@
|
|
| 729 |
"role": "assistant",
|
| 730 |
"tool_calls": [
|
| 731 |
{
|
| 732 |
-
"id": "
|
| 733 |
"type": "function",
|
| 734 |
"function": {
|
| 735 |
"name": "lookup_code",
|
|
@@ -741,7 +730,7 @@
|
|
| 741 |
},
|
| 742 |
{
|
| 743 |
"role": "tool",
|
| 744 |
-
"tool_call_id": "
|
| 745 |
"content": "{\"code\": \"BLUE-CEDAR\"}"
|
| 746 |
}
|
| 747 |
],
|
|
@@ -773,10 +762,10 @@
|
|
| 773 |
}
|
| 774 |
},
|
| 775 |
"response": {
|
| 776 |
-
"id": "chatcmpl-
|
| 777 |
"object": "chat.completion",
|
| 778 |
-
"created":
|
| 779 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 780 |
"choices": [
|
| 781 |
{
|
| 782 |
"index": 0,
|
|
@@ -803,12 +792,12 @@
|
|
| 803 |
"context_exhaustion": null
|
| 804 |
},
|
| 805 |
"pass": true,
|
| 806 |
-
"seconds": 1.
|
| 807 |
},
|
| 808 |
{
|
| 809 |
"name": "reasoning_effort=low",
|
| 810 |
"request": {
|
| 811 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 812 |
"messages": [
|
| 813 |
{
|
| 814 |
"role": "user",
|
|
@@ -820,18 +809,18 @@
|
|
| 820 |
"reasoning_effort": "low"
|
| 821 |
},
|
| 822 |
"response": {
|
| 823 |
-
"id": "chatcmpl-
|
| 824 |
"object": "chat.completion",
|
| 825 |
-
"created":
|
| 826 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 827 |
"choices": [
|
| 828 |
{
|
| 829 |
"index": 0,
|
| 830 |
"message": {
|
| 831 |
"role": "assistant",
|
| 832 |
-
"content": "No
|
| 833 |
"tool_calls": null,
|
| 834 |
-
"reasoning_content": "221 = 13 \u00d7 17
|
| 835 |
},
|
| 836 |
"logprobs": null,
|
| 837 |
"finish_reason": "stop"
|
|
@@ -839,23 +828,20 @@
|
|
| 839 |
],
|
| 840 |
"usage": {
|
| 841 |
"prompt_tokens": 30,
|
| 842 |
-
"completion_tokens":
|
| 843 |
-
"total_tokens":
|
| 844 |
-
"prompt_tokens_details":
|
| 845 |
-
"cached_tokens": 29,
|
| 846 |
-
"cache_detail": "native-glm+disk"
|
| 847 |
-
}
|
| 848 |
},
|
| 849 |
"warnings": null,
|
| 850 |
"context_exhaustion": null
|
| 851 |
},
|
| 852 |
"pass": true,
|
| 853 |
-
"seconds": 1.
|
| 854 |
},
|
| 855 |
{
|
| 856 |
"name": "reasoning_effort=high",
|
| 857 |
"request": {
|
| 858 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 859 |
"messages": [
|
| 860 |
{
|
| 861 |
"role": "user",
|
|
@@ -867,18 +853,18 @@
|
|
| 867 |
"reasoning_effort": "high"
|
| 868 |
},
|
| 869 |
"response": {
|
| 870 |
-
"id": "chatcmpl-
|
| 871 |
"object": "chat.completion",
|
| 872 |
-
"created":
|
| 873 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 874 |
"choices": [
|
| 875 |
{
|
| 876 |
"index": 0,
|
| 877 |
"message": {
|
| 878 |
"role": "assistant",
|
| 879 |
-
"content": "No. 221 is not prime because it
|
| 880 |
"tool_calls": null,
|
| 881 |
-
"reasoning_content": "221 = 13 \u00d7 17
|
| 882 |
},
|
| 883 |
"logprobs": null,
|
| 884 |
"finish_reason": "stop"
|
|
@@ -886,23 +872,20 @@
|
|
| 886 |
],
|
| 887 |
"usage": {
|
| 888 |
"prompt_tokens": 30,
|
| 889 |
-
"completion_tokens":
|
| 890 |
-
"total_tokens":
|
| 891 |
-
"prompt_tokens_details":
|
| 892 |
-
"cached_tokens": 29,
|
| 893 |
-
"cache_detail": "native-glm+disk"
|
| 894 |
-
}
|
| 895 |
},
|
| 896 |
"warnings": null,
|
| 897 |
"context_exhaustion": null
|
| 898 |
},
|
| 899 |
"pass": true,
|
| 900 |
-
"seconds":
|
| 901 |
},
|
| 902 |
{
|
| 903 |
"name": "reasoning_effort=max",
|
| 904 |
"request": {
|
| 905 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 906 |
"messages": [
|
| 907 |
{
|
| 908 |
"role": "user",
|
|
@@ -914,18 +897,18 @@
|
|
| 914 |
"reasoning_effort": "max"
|
| 915 |
},
|
| 916 |
"response": {
|
| 917 |
-
"id": "chatcmpl-
|
| 918 |
"object": "chat.completion",
|
| 919 |
-
"created":
|
| 920 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 921 |
"choices": [
|
| 922 |
{
|
| 923 |
"index": 0,
|
| 924 |
"message": {
|
| 925 |
"role": "assistant",
|
| 926 |
-
"content": "No
|
| 927 |
"tool_calls": null,
|
| 928 |
-
"reasoning_content": "The user asks
|
| 929 |
},
|
| 930 |
"logprobs": null,
|
| 931 |
"finish_reason": "stop"
|
|
@@ -933,23 +916,20 @@
|
|
| 933 |
],
|
| 934 |
"usage": {
|
| 935 |
"prompt_tokens": 30,
|
| 936 |
-
"completion_tokens":
|
| 937 |
-
"total_tokens":
|
| 938 |
-
"prompt_tokens_details":
|
| 939 |
-
"cached_tokens": 29,
|
| 940 |
-
"cache_detail": "native-glm+disk"
|
| 941 |
-
}
|
| 942 |
},
|
| 943 |
"warnings": null,
|
| 944 |
"context_exhaustion": null
|
| 945 |
},
|
| 946 |
"pass": true,
|
| 947 |
-
"seconds": 3.
|
| 948 |
},
|
| 949 |
{
|
| 950 |
"name": "image colors/shapes",
|
| 951 |
"request": {
|
| 952 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 953 |
"messages": [
|
| 954 |
{
|
| 955 |
"role": "user",
|
|
@@ -974,16 +954,16 @@
|
|
| 974 |
}
|
| 975 |
},
|
| 976 |
"response": {
|
| 977 |
-
"id": "chatcmpl-
|
| 978 |
"object": "chat.completion",
|
| 979 |
-
"created":
|
| 980 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 981 |
"choices": [
|
| 982 |
{
|
| 983 |
"index": 0,
|
| 984 |
"message": {
|
| 985 |
"role": "assistant",
|
| 986 |
-
"content": "The user wants me to describe the visible colors and shapes in the
|
| 987 |
"tool_calls": null,
|
| 988 |
"reasoning_content": null
|
| 989 |
},
|
|
@@ -993,23 +973,20 @@
|
|
| 993 |
],
|
| 994 |
"usage": {
|
| 995 |
"prompt_tokens": 124,
|
| 996 |
-
"completion_tokens":
|
| 997 |
-
"total_tokens":
|
| 998 |
-
"prompt_tokens_details":
|
| 999 |
-
"cached_tokens": 123,
|
| 1000 |
-
"cache_detail": "native-glm+disk"
|
| 1001 |
-
}
|
| 1002 |
},
|
| 1003 |
"warnings": null,
|
| 1004 |
"context_exhaustion": null
|
| 1005 |
},
|
| 1006 |
"pass": true,
|
| 1007 |
-
"seconds": 7.
|
| 1008 |
},
|
| 1009 |
{
|
| 1010 |
"name": "video motion direction",
|
| 1011 |
"request": {
|
| 1012 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 1013 |
"messages": [
|
| 1014 |
{
|
| 1015 |
"role": "user",
|
|
@@ -1034,16 +1011,16 @@
|
|
| 1034 |
}
|
| 1035 |
},
|
| 1036 |
"response": {
|
| 1037 |
-
"id": "chatcmpl-
|
| 1038 |
"object": "chat.completion",
|
| 1039 |
-
"created":
|
| 1040 |
-
"model": "glm53-jangtq/GLM-5.3-Flash-
|
| 1041 |
"choices": [
|
| 1042 |
{
|
| 1043 |
"index": 0,
|
| 1044 |
"message": {
|
| 1045 |
"role": "assistant",
|
| 1046 |
-
"content": "The user wants to know the direction
|
| 1047 |
"tool_calls": null,
|
| 1048 |
"reasoning_content": null
|
| 1049 |
},
|
|
@@ -1053,17 +1030,14 @@
|
|
| 1053 |
],
|
| 1054 |
"usage": {
|
| 1055 |
"prompt_tokens": 589,
|
| 1056 |
-
"completion_tokens":
|
| 1057 |
-
"total_tokens":
|
| 1058 |
-
"prompt_tokens_details":
|
| 1059 |
-
"cached_tokens": 588,
|
| 1060 |
-
"cache_detail": "native-glm+disk"
|
| 1061 |
-
}
|
| 1062 |
},
|
| 1063 |
"warnings": null,
|
| 1064 |
"context_exhaustion": null
|
| 1065 |
},
|
| 1066 |
"pass": true,
|
| 1067 |
-
"seconds":
|
| 1068 |
}
|
| 1069 |
]
|
|
|
|
| 2 |
{
|
| 3 |
"name": "math thinking_on",
|
| 4 |
"request": {
|
| 5 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 6 |
"messages": [
|
| 7 |
{
|
| 8 |
"role": "system",
|
|
|
|
| 20 |
}
|
| 21 |
},
|
| 22 |
"response": {
|
| 23 |
+
"id": "chatcmpl-ba6a7cbe",
|
| 24 |
"object": "chat.completion",
|
| 25 |
+
"created": 1790717259,
|
| 26 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 27 |
"choices": [
|
| 28 |
{
|
| 29 |
"index": 0,
|
| 30 |
"message": {
|
| 31 |
"role": "assistant",
|
| 32 |
+
"content": "17 \u00d7 19 = **323**\n\nA quick way to see this: 17 \u00d7 20 = 340, then subtract one 17 to get 340 \u2212 17 = 323.",
|
| 33 |
"tool_calls": null,
|
| 34 |
"reasoning_content": "17 \u00d7 19 = 17 \u00d7 20 - 17 = 340 - 17 = 323"
|
| 35 |
},
|
|
|
|
| 39 |
],
|
| 40 |
"usage": {
|
| 41 |
"prompt_tokens": 28,
|
| 42 |
+
"completion_tokens": 67,
|
| 43 |
+
"total_tokens": 95,
|
| 44 |
+
"prompt_tokens_details": null
|
|
|
|
|
|
|
|
|
|
| 45 |
},
|
| 46 |
"warnings": null,
|
| 47 |
"context_exhaustion": null
|
| 48 |
},
|
| 49 |
"pass": true,
|
| 50 |
+
"seconds": 3.0335948749561794
|
| 51 |
},
|
| 52 |
{
|
| 53 |
"name": "math followup thinking_off",
|
| 54 |
"request": {
|
| 55 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 56 |
"messages": [
|
| 57 |
{
|
| 58 |
"role": "system",
|
|
|
|
| 64 |
},
|
| 65 |
{
|
| 66 |
"role": "assistant",
|
| 67 |
+
"content": "17 \u00d7 19 = **323**\n\nA quick way to see this: 17 \u00d7 20 = 340, then subtract one 17 to get 340 \u2212 17 = 323.",
|
| 68 |
"tool_calls": null,
|
| 69 |
"reasoning_content": "17 \u00d7 19 = 17 \u00d7 20 - 17 = 340 - 17 = 323"
|
| 70 |
},
|
|
|
|
| 80 |
}
|
| 81 |
},
|
| 82 |
"response": {
|
| 83 |
+
"id": "chatcmpl-691e6a01",
|
| 84 |
"object": "chat.completion",
|
| 85 |
+
"created": 1790717260,
|
| 86 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 87 |
"choices": [
|
| 88 |
{
|
| 89 |
"index": 0,
|
|
|
|
| 98 |
}
|
| 99 |
],
|
| 100 |
"usage": {
|
| 101 |
+
"prompt_tokens": 83,
|
| 102 |
"completion_tokens": 10,
|
| 103 |
+
"total_tokens": 93,
|
| 104 |
"prompt_tokens_details": null
|
| 105 |
},
|
| 106 |
"warnings": null,
|
| 107 |
"context_exhaustion": null
|
| 108 |
},
|
| 109 |
"pass": true,
|
| 110 |
+
"seconds": 1.2121696670074016
|
| 111 |
},
|
| 112 |
{
|
| 113 |
"name": "tool p1 think=False choice=required",
|
| 114 |
"request": {
|
| 115 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 116 |
"messages": [
|
| 117 |
{
|
| 118 |
"role": "user",
|
|
|
|
| 148 |
}
|
| 149 |
},
|
| 150 |
"response": {
|
| 151 |
+
"id": "chatcmpl-1c5a9421",
|
| 152 |
"object": "chat.completion",
|
| 153 |
+
"created": 1790717261,
|
| 154 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 155 |
"choices": [
|
| 156 |
{
|
| 157 |
"index": 0,
|
|
|
|
| 159 |
"role": "assistant",
|
| 160 |
"tool_calls": [
|
| 161 |
{
|
| 162 |
+
"id": "call_df3410cb",
|
| 163 |
"type": "function",
|
| 164 |
"function": {
|
| 165 |
"name": "lookup_code",
|
|
|
|
| 179 |
}
|
| 180 |
},
|
| 181 |
"pass": true,
|
| 182 |
+
"seconds": 1.5101636670297012
|
| 183 |
},
|
| 184 |
{
|
| 185 |
"name": "tool p1 think=False choice=auto",
|
| 186 |
"request": {
|
| 187 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 188 |
"messages": [
|
| 189 |
{
|
| 190 |
"role": "user",
|
|
|
|
| 220 |
}
|
| 221 |
},
|
| 222 |
"response": {
|
| 223 |
+
"id": "chatcmpl-51e2f985",
|
| 224 |
"object": "chat.completion",
|
| 225 |
+
"created": 1790717262,
|
| 226 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 227 |
"choices": [
|
| 228 |
{
|
| 229 |
"index": 0,
|
|
|
|
| 231 |
"role": "assistant",
|
| 232 |
"tool_calls": [
|
| 233 |
{
|
| 234 |
+
"id": "call_578fcc8c",
|
| 235 |
"type": "function",
|
| 236 |
"function": {
|
| 237 |
"name": "lookup_code",
|
|
|
|
| 255 |
}
|
| 256 |
},
|
| 257 |
"pass": true,
|
| 258 |
+
"seconds": 0.52547091699671
|
| 259 |
},
|
| 260 |
{
|
| 261 |
"name": "tool p1 think=True choice=required",
|
| 262 |
"request": {
|
| 263 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 264 |
"messages": [
|
| 265 |
{
|
| 266 |
"role": "user",
|
|
|
|
| 296 |
}
|
| 297 |
},
|
| 298 |
"response": {
|
| 299 |
+
"id": "chatcmpl-9a22428f",
|
| 300 |
"object": "chat.completion",
|
| 301 |
+
"created": 1790717264,
|
| 302 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 303 |
"choices": [
|
| 304 |
{
|
| 305 |
"index": 0,
|
|
|
|
| 307 |
"role": "assistant",
|
| 308 |
"tool_calls": [
|
| 309 |
{
|
| 310 |
+
"id": "call_66cb738c",
|
| 311 |
"type": "function",
|
| 312 |
"function": {
|
| 313 |
"name": "lookup_code",
|
|
|
|
| 315 |
}
|
| 316 |
}
|
| 317 |
],
|
| 318 |
+
"reasoning_content": "The user wants me to look up the code for label \"alpha\" using the lookup_code tool.",
|
| 319 |
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|
| 320 |
},
|
| 321 |
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|
|
|
| 323 |
],
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| 324 |
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| 325 |
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| 326 |
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| 327 |
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|
|
|
|
| 328 |
}
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| 329 |
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| 330 |
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|
| 331 |
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| 332 |
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| 333 |
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| 334 |
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| 339 |
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| 369 |
}
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| 372 |
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| 380 |
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| 381 |
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|
| 382 |
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|
| 383 |
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"id": "call_73463e23",
|
| 384 |
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| 385 |
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|
| 386 |
"name": "lookup_code",
|
|
|
|
| 388 |
}
|
| 389 |
}
|
| 390 |
],
|
| 391 |
+
"reasoning_content": "The user wants me to look up the code for label \"alpha\" using the lookup_code tool.",
|
| 392 |
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|
| 393 |
},
|
| 394 |
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|
|
|
| 396 |
],
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| 397 |
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| 398 |
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|
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| 405 |
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| 408 |
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| 413 |
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"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
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| 414 |
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| 416 |
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|
|
| 446 |
}
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},
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"id": "chatcmpl-13ea203c",
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"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
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{
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| 457 |
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|
| 460 |
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"id": "call_b288f0bc",
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|
| 463 |
"name": "lookup_code",
|
|
|
|
| 477 |
}
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| 478 |
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| 479 |
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|
| 480 |
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"seconds": 1.5650544160162099
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| 481 |
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| 482 |
{
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| 485 |
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"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
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| 486 |
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{
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| 488 |
"role": "user",
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|
|
|
| 518 |
}
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| 519 |
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| 521 |
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"id": "chatcmpl-634e136e",
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| 522 |
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|
|
| 529 |
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{
|
| 532 |
+
"id": "call_4be64d92",
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| 533 |
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| 534 |
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|
| 535 |
"name": "lookup_code",
|
|
|
|
| 553 |
}
|
| 554 |
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| 555 |
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|
| 556 |
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"seconds": 0.5339888340095058
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| 558 |
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|
| 561 |
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"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
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| 562 |
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| 563 |
{
|
| 564 |
"role": "user",
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|
|
|
| 594 |
}
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| 595 |
},
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| 596 |
"response": {
|
| 597 |
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"id": "chatcmpl-4e39f975",
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| 598 |
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| 599 |
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"created": 1790717270,
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| 600 |
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"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
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| 601 |
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| 603 |
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|
|
| 605 |
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| 607 |
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|
| 608 |
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"id": "call_7e5a7b23",
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| 611 |
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|
|
|
|
| 613 |
}
|
| 614 |
}
|
| 615 |
],
|
| 616 |
+
"reasoning_content": "The user wants me to look up the secret code for the label 'alpha'. I need to call the lookup_code tool with label 'alpha'.",
|
| 617 |
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|
| 618 |
},
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| 619 |
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|
|
|
| 621 |
],
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| 622 |
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| 624 |
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| 625 |
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"total_tokens": 241
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|
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|
|
|
| 626 |
}
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| 627 |
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| 628 |
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| 629 |
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"seconds": 2.620424250024371
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"name": "tool p2 think=True choice=auto",
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"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
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|
|
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| 667 |
}
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"id": "chatcmpl-f8c9455d",
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"created": 1790717272,
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"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
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|
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| 678 |
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|
| 681 |
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"id": "call_4af5a873",
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| 682 |
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| 683 |
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| 684 |
"name": "lookup_code",
|
|
|
|
| 686 |
}
|
| 687 |
}
|
| 688 |
],
|
| 689 |
+
"reasoning_content": "The user wants me to look up the secret code for the label 'alpha'. I need to call the lookup_code tool with label 'alpha'.",
|
| 690 |
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|
| 691 |
},
|
| 692 |
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|
|
|
|
| 694 |
],
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| 695 |
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| 696 |
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| 697 |
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"total_tokens": 241,
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| 699 |
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|
| 701 |
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|
|
|
|
| 703 |
}
|
| 704 |
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| 705 |
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|
| 706 |
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"seconds": 1.602398417016957
|
| 707 |
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|
| 708 |
{
|
| 709 |
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|
| 711 |
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"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 712 |
"messages": [
|
| 713 |
{
|
| 714 |
"role": "user",
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|
|
|
| 718 |
"role": "assistant",
|
| 719 |
"tool_calls": [
|
| 720 |
{
|
| 721 |
+
"id": "call_df3410cb",
|
| 722 |
"type": "function",
|
| 723 |
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|
| 724 |
"name": "lookup_code",
|
|
|
|
| 730 |
},
|
| 731 |
{
|
| 732 |
"role": "tool",
|
| 733 |
+
"tool_call_id": "call_df3410cb",
|
| 734 |
"content": "{\"code\": \"BLUE-CEDAR\"}"
|
| 735 |
}
|
| 736 |
],
|
|
|
|
| 762 |
}
|
| 763 |
},
|
| 764 |
"response": {
|
| 765 |
+
"id": "chatcmpl-7a038768",
|
| 766 |
"object": "chat.completion",
|
| 767 |
+
"created": 1790717273,
|
| 768 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 769 |
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|
| 770 |
{
|
| 771 |
"index": 0,
|
|
|
|
| 792 |
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|
| 793 |
},
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| 794 |
"pass": true,
|
| 795 |
+
"seconds": 1.1969611250096932
|
| 796 |
},
|
| 797 |
{
|
| 798 |
"name": "reasoning_effort=low",
|
| 799 |
"request": {
|
| 800 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 801 |
"messages": [
|
| 802 |
{
|
| 803 |
"role": "user",
|
|
|
|
| 809 |
"reasoning_effort": "low"
|
| 810 |
},
|
| 811 |
"response": {
|
| 812 |
+
"id": "chatcmpl-57775cd0",
|
| 813 |
"object": "chat.completion",
|
| 814 |
+
"created": 1790717275,
|
| 815 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 816 |
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|
| 817 |
{
|
| 818 |
"index": 0,
|
| 819 |
"message": {
|
| 820 |
"role": "assistant",
|
| 821 |
+
"content": "No. 221 = 13 \u00d7 17, so it's a composite number.",
|
| 822 |
"tool_calls": null,
|
| 823 |
+
"reasoning_content": "221 = 13 \u00d7 17, not prime."
|
| 824 |
},
|
| 825 |
"logprobs": null,
|
| 826 |
"finish_reason": "stop"
|
|
|
|
| 828 |
],
|
| 829 |
"usage": {
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| 830 |
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|
| 831 |
+
"completion_tokens": 33,
|
| 832 |
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"total_tokens": 63,
|
| 833 |
+
"prompt_tokens_details": null
|
|
|
|
|
|
|
|
|
|
| 834 |
},
|
| 835 |
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|
| 836 |
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|
| 837 |
},
|
| 838 |
"pass": true,
|
| 839 |
+
"seconds": 1.834579374990426
|
| 840 |
},
|
| 841 |
{
|
| 842 |
"name": "reasoning_effort=high",
|
| 843 |
"request": {
|
| 844 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 845 |
"messages": [
|
| 846 |
{
|
| 847 |
"role": "user",
|
|
|
|
| 853 |
"reasoning_effort": "high"
|
| 854 |
},
|
| 855 |
"response": {
|
| 856 |
+
"id": "chatcmpl-92e454e0",
|
| 857 |
"object": "chat.completion",
|
| 858 |
+
"created": 1790717279,
|
| 859 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 860 |
"choices": [
|
| 861 |
{
|
| 862 |
"index": 0,
|
| 863 |
"message": {
|
| 864 |
"role": "assistant",
|
| 865 |
+
"content": "No. 221 is not prime because it can be factored as 13 \u00d7 17.",
|
| 866 |
"tool_calls": null,
|
| 867 |
+
"reasoning_content": "221 = 13 \u00d7 17, not prime."
|
| 868 |
},
|
| 869 |
"logprobs": null,
|
| 870 |
"finish_reason": "stop"
|
|
|
|
| 872 |
],
|
| 873 |
"usage": {
|
| 874 |
"prompt_tokens": 30,
|
| 875 |
+
"completion_tokens": 35,
|
| 876 |
+
"total_tokens": 65,
|
| 877 |
+
"prompt_tokens_details": null
|
|
|
|
|
|
|
|
|
|
| 878 |
},
|
| 879 |
"warnings": null,
|
| 880 |
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|
| 881 |
},
|
| 882 |
"pass": true,
|
| 883 |
+
"seconds": 4.108727833954617
|
| 884 |
},
|
| 885 |
{
|
| 886 |
"name": "reasoning_effort=max",
|
| 887 |
"request": {
|
| 888 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 889 |
"messages": [
|
| 890 |
{
|
| 891 |
"role": "user",
|
|
|
|
| 897 |
"reasoning_effort": "max"
|
| 898 |
},
|
| 899 |
"response": {
|
| 900 |
+
"id": "chatcmpl-8e1e2785",
|
| 901 |
"object": "chat.completion",
|
| 902 |
+
"created": 1790717282,
|
| 903 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 904 |
"choices": [
|
| 905 |
{
|
| 906 |
"index": 0,
|
| 907 |
"message": {
|
| 908 |
"role": "assistant",
|
| 909 |
+
"content": "No. 221 is not prime because it can be factored as 13 \u00d7 17.",
|
| 910 |
"tool_calls": null,
|
| 911 |
+
"reasoning_content": "The user asks if 221 is prime. Let me check: 221 = 13 \u00d7 17. So it's not prime. Answer: No, because 221 = 13 \u00d7 17."
|
| 912 |
},
|
| 913 |
"logprobs": null,
|
| 914 |
"finish_reason": "stop"
|
|
|
|
| 916 |
],
|
| 917 |
"usage": {
|
| 918 |
"prompt_tokens": 30,
|
| 919 |
+
"completion_tokens": 68,
|
| 920 |
+
"total_tokens": 98,
|
| 921 |
+
"prompt_tokens_details": null
|
|
|
|
|
|
|
|
|
|
| 922 |
},
|
| 923 |
"warnings": null,
|
| 924 |
"context_exhaustion": null
|
| 925 |
},
|
| 926 |
"pass": true,
|
| 927 |
+
"seconds": 3.0803108330001123
|
| 928 |
},
|
| 929 |
{
|
| 930 |
"name": "image colors/shapes",
|
| 931 |
"request": {
|
| 932 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 933 |
"messages": [
|
| 934 |
{
|
| 935 |
"role": "user",
|
|
|
|
| 954 |
}
|
| 955 |
},
|
| 956 |
"response": {
|
| 957 |
+
"id": "chatcmpl-a361db15",
|
| 958 |
"object": "chat.completion",
|
| 959 |
+
"created": 1790717289,
|
| 960 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 961 |
"choices": [
|
| 962 |
{
|
| 963 |
"index": 0,
|
| 964 |
"message": {
|
| 965 |
"role": "assistant",
|
| 966 |
+
"content": "The user wants me to describe the visible colors and shapes in the image.\nLooking at the image:\n- There is a solid blue square in the center.\n- The background is white.\n- The shape is a square (or rectangle, but it looks square).\n- The color of the square is blue (specifically, pure blue or a bright blue, like #0000FF).\n- The background color is white.\n\nLet's write a simple, clear description of the colors and shapes.Based on the image, here is a description of the visible colors and shapes:\n\n* **Shapes:** There is a single **square** in the center of the image.\n* **Colors:** \n * The square is solid **blue** (specifically a bright, pure blue).\n * The background surrounding the square is **white**.",
|
| 967 |
"tool_calls": null,
|
| 968 |
"reasoning_content": null
|
| 969 |
},
|
|
|
|
| 973 |
],
|
| 974 |
"usage": {
|
| 975 |
"prompt_tokens": 124,
|
| 976 |
+
"completion_tokens": 173,
|
| 977 |
+
"total_tokens": 297,
|
| 978 |
+
"prompt_tokens_details": null
|
|
|
|
|
|
|
|
|
|
| 979 |
},
|
| 980 |
"warnings": null,
|
| 981 |
"context_exhaustion": null
|
| 982 |
},
|
| 983 |
"pass": true,
|
| 984 |
+
"seconds": 7.025973458017688
|
| 985 |
},
|
| 986 |
{
|
| 987 |
"name": "video motion direction",
|
| 988 |
"request": {
|
| 989 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 990 |
"messages": [
|
| 991 |
{
|
| 992 |
"role": "user",
|
|
|
|
| 1011 |
}
|
| 1012 |
},
|
| 1013 |
"response": {
|
| 1014 |
+
"id": "chatcmpl-916ee30f",
|
| 1015 |
"object": "chat.completion",
|
| 1016 |
+
"created": 1790717298,
|
| 1017 |
+
"model": "glm53-jangtq/GLM-5.3-Flash-JANGH2-r2",
|
| 1018 |
"choices": [
|
| 1019 |
{
|
| 1020 |
"index": 0,
|
| 1021 |
"message": {
|
| 1022 |
"role": "assistant",
|
| 1023 |
+
"content": "The user wants to know the direction in which the colored square moves across the video.\nI will analyze the position of the square in each frame.\n- At 00:00, the square is on the left side of the screen.\n- At 00:02, the square is in the middle of the screen.\n- At 00:04, the square is still in the middle, but slightly to the right compared to 00:02.\n- At 00:06, the square is on the right side of the screen.\nThe square starts on the left and ends on the right. Therefore, it moves from left to right.Based on the video frames, the colored square starts on the left side of the screen at 00:00. By 00:02, it has moved to the center. It continues moving and is positioned on the right side of the screen by 00:06. Therefore, the square moves from left to right.",
|
| 1024 |
"tool_calls": null,
|
| 1025 |
"reasoning_content": null
|
| 1026 |
},
|
|
|
|
| 1030 |
],
|
| 1031 |
"usage": {
|
| 1032 |
"prompt_tokens": 589,
|
| 1033 |
+
"completion_tokens": 197,
|
| 1034 |
+
"total_tokens": 786,
|
| 1035 |
+
"prompt_tokens_details": null
|
|
|
|
|
|
|
|
|
|
| 1036 |
},
|
| 1037 |
"warnings": null,
|
| 1038 |
"context_exhaustion": null
|
| 1039 |
},
|
| 1040 |
"pass": true,
|
| 1041 |
+
"seconds": 9.237239582987968
|
| 1042 |
}
|
| 1043 |
]
|
evaluation/kl_vs_fp8.json
CHANGED
|
@@ -1,35 +1,35 @@
|
|
| 1 |
{
|
| 2 |
"positions": 15830,
|
| 3 |
-
"median_kl": 0.
|
| 4 |
-
"mean_kl": 0.
|
| 5 |
"kl_percentiles": {
|
| 6 |
-
"p50": 0.
|
| 7 |
-
"p75": 0.
|
| 8 |
-
"p90": 0.
|
| 9 |
-
"p95": 1.
|
| 10 |
-
"p99":
|
| 11 |
},
|
| 12 |
-
"kl_max":
|
| 13 |
-
"top1_agreement_pct": 83.
|
| 14 |
-
"ref_top1_in_top5_pct":
|
| 15 |
-
"ref_top1_in_top10_pct": 98.
|
| 16 |
"flip_curve": [
|
| 17 |
[
|
| 18 |
0.0,
|
| 19 |
0.7499999403953552,
|
| 20 |
-
0.
|
| 21 |
1961
|
| 22 |
],
|
| 23 |
[
|
| 24 |
0.7499999403953552,
|
| 25 |
1.7499999403953552,
|
| 26 |
-
0.
|
| 27 |
1993
|
| 28 |
],
|
| 29 |
[
|
| 30 |
1.7499999403953552,
|
| 31 |
3.124999954365194,
|
| 32 |
-
0.
|
| 33 |
1982
|
| 34 |
],
|
| 35 |
[
|
|
@@ -41,25 +41,25 @@
|
|
| 41 |
[
|
| 42 |
4.874999938998371,
|
| 43 |
6.624999997293344,
|
| 44 |
-
0.
|
| 45 |
1979
|
| 46 |
],
|
| 47 |
[
|
| 48 |
6.624999997293344,
|
| 49 |
8.500000116902811,
|
| 50 |
-
0.
|
| 51 |
1978
|
| 52 |
],
|
| 53 |
[
|
| 54 |
8.500000116902811,
|
| 55 |
10.687500133566573,
|
| 56 |
-
0.
|
| 57 |
1979
|
| 58 |
],
|
| 59 |
[
|
| 60 |
10.687500133566573,
|
| 61 |
23.8125,
|
| 62 |
-
0.
|
| 63 |
1979
|
| 64 |
]
|
| 65 |
],
|
|
|
|
| 1 |
{
|
| 2 |
"positions": 15830,
|
| 3 |
+
"median_kl": 0.030121881710082024,
|
| 4 |
+
"mean_kl": 0.37614552186788514,
|
| 5 |
"kl_percentiles": {
|
| 6 |
+
"p50": 0.030121881710082024,
|
| 7 |
+
"p75": 0.2471745266366821,
|
| 8 |
+
"p90": 0.9753125174640521,
|
| 9 |
+
"p95": 1.9690169079681636,
|
| 10 |
+
"p99": 5.242001235392597
|
| 11 |
},
|
| 12 |
+
"kl_max": 23.99713653286548,
|
| 13 |
+
"top1_agreement_pct": 83.90397978521794,
|
| 14 |
+
"ref_top1_in_top5_pct": 96.83512318382817,
|
| 15 |
+
"ref_top1_in_top10_pct": 98.27542640555906,
|
| 16 |
"flip_curve": [
|
| 17 |
[
|
| 18 |
0.0,
|
| 19 |
0.7499999403953552,
|
| 20 |
+
0.5298317185109638,
|
| 21 |
1961
|
| 22 |
],
|
| 23 |
[
|
| 24 |
0.7499999403953552,
|
| 25 |
1.7499999403953552,
|
| 26 |
+
0.30306071249372807,
|
| 27 |
1993
|
| 28 |
],
|
| 29 |
[
|
| 30 |
1.7499999403953552,
|
| 31 |
3.124999954365194,
|
| 32 |
+
0.17507568113017155,
|
| 33 |
1982
|
| 34 |
],
|
| 35 |
[
|
|
|
|
| 41 |
[
|
| 42 |
4.874999938998371,
|
| 43 |
6.624999997293344,
|
| 44 |
+
0.07832238504295098,
|
| 45 |
1979
|
| 46 |
],
|
| 47 |
[
|
| 48 |
6.624999997293344,
|
| 49 |
8.500000116902811,
|
| 50 |
+
0.051061678463094035,
|
| 51 |
1978
|
| 52 |
],
|
| 53 |
[
|
| 54 |
8.500000116902811,
|
| 55 |
10.687500133566573,
|
| 56 |
+
0.021222839818089943,
|
| 57 |
1979
|
| 58 |
],
|
| 59 |
[
|
| 60 |
10.687500133566573,
|
| 61 |
23.8125,
|
| 62 |
+
0.007579585649317837,
|
| 63 |
1979
|
| 64 |
]
|
| 65 |
],
|
evaluation/native_transcripts_vs_bf16.json
ADDED
|
@@ -0,0 +1,611 @@
|
|
|
|
|
|
|
|
|
|
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|
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|
| 1 |
+
{
|
| 2 |
+
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evaluation/scale_correction_report.json
ADDED
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@@ -0,0 +1,884 @@
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|
evaluation/served_reasoning_matrix.json
ADDED
|
@@ -0,0 +1,786 @@
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|
| 785 |
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|
| 786 |
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]
|
jang_config.json
CHANGED
|
@@ -230,5 +230,17 @@
|
|
| 230 |
"tool_parser": "glm_xml_args",
|
| 231 |
"tool_response_role": "observation",
|
| 232 |
"family": "glm5_next"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 233 |
}
|
| 234 |
}
|
|
|
|
| 230 |
"tool_parser": "glm_xml_args",
|
| 231 |
"tool_response_role": "observation",
|
| 232 |
"family": "glm5_next"
|
| 233 |
+
},
|
| 234 |
+
"scale_correction": {
|
| 235 |
+
"revision": 2,
|
| 236 |
+
"rule": "row scale *= (<w,w>/<w,q>)^pow, clipped to [0.5, 2.0]",
|
| 237 |
+
"pow": 1.0,
|
| 238 |
+
"projections": [
|
| 239 |
+
"gate",
|
| 240 |
+
"up",
|
| 241 |
+
"down"
|
| 242 |
+
],
|
| 243 |
+
"reason": "MSE-optimal scales attenuate deep features; close-reasoning decision restored",
|
| 244 |
+
"codes_changed": false
|
| 245 |
}
|
| 246 |
}
|
model-00003-of-00019.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5446436616
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
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