phaedawg commited on
Commit
5d6bd81
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1 Parent(s): 31c7e6d

Publish gemma-4-26B-A4B-it distribution-fidelity artifact (part 4)

Browse files
gemma-4-26B-A4B-it-AWQ-4bit/attribution.json CHANGED
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gemma-4-26B-A4B-it-AWQ-4bit/manifest.json CHANGED
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gemma-4-26B-A4B-it-AWQ-4bit/report.md CHANGED
@@ -18,7 +18,7 @@ Reverse direction, KLD(candidate || reference): 1.04249246.
18
  | Candidate weights SHA-256 | f1f4146421ee33ad |
19
  | Suite | gemma4-31b-it-fidelity-1024x2048-v1 |
20
  | Suite token SHA-256 | 81d66409b44937fa |
21
- | Capture manifest SHA-256 | b5ab5ede01f46551 |
22
  | Tokenizer | None |
23
  | Scored vocabulary | 262144 |
24
  | Declared vocabulary | 262144 |
@@ -31,16 +31,19 @@ Reverse direction, KLD(candidate || reference): 1.04249246.
31
  | Prefix caching | False |
32
  | max_num_seqs | 1 |
33
  | vLLM | 0.1.dev20446+gb2bc9171d |
34
- | vLLM commit | a2ae11e29e34 |
35
  | vLLM dirty digest | e3b0c44298fc1c14 |
 
36
  | Compiled extensions | f2fbc7537b0f01f6 |
37
  | FlashInfer | 0.6.17 |
38
  | torch | 2.13.0+cu132 |
39
  | Driver | 580.173.02 |
40
  | GPUs | NVIDIA RTX PRO 6000 Blackwell Workstation Edition, NVIDIA RTX PRO 6000 Blackwell Workstation Edition, NVIDIA RTX PRO 6000 Blackwell Workstation Edition, NVIDIA RTX PRO 6000 Blackwell Workstation Edition |
41
- | Laws version | 14 |
42
  | Partition | analysis |
43
 
 
 
44
  ## Routed-model intervention: QxQ and BxQ
45
 
46
  **The first axis is routing source; the second Q is the same unchanged quantized candidate in both runs.** QxQ uses the student's natural expert IDs. BxQ forces the BF16 teacher's expert IDs while the student computes its own gating weights for those experts.
@@ -52,7 +55,7 @@ Reverse direction, KLD(candidate || reference): 1.04249246.
52
  | QxQ - BxQ | paired routing-intervention delta; not additive attribution | +0.18538034 | | |
53
  | Exact repeat | two QxQ, two forced-natural, two BxQ samples | certified | | |
54
 
55
- Natural QxQ selections changed from the teacher at **62.7369%** of (token, layer) choices. BxQ protocol 5; routing trace `0fcde10d9c35222c`.
56
 
57
  Natural control used exact-repeat certification: max position delta 0.000e+00 / 0.000e+00; absolute mean delta 0.000e+00 / 0.000e+00; natural route-repeat flips 0.000%.
58
 
@@ -123,6 +126,15 @@ The same expert weights rounded through each scheme, which is the cell that disc
123
 
124
  Full cells, digests, and the deployed checkpoint's inspection are in [attribution.json](attribution.json).
125
 
 
 
 
 
 
 
 
 
 
126
  ## Routing divergence
127
 
128
  This is the observed selection divergence in the normal QxQ run, not the BxQ intervention and not a QDQ router-weight cell. It compares the student's natural expert IDs with the teacher's recorded IDs over 30 routed layers, 8 experts per token.
@@ -230,15 +242,15 @@ Zero baseline: reference against itself scored **0.00000000** over 2047 position
230
  | 2 | Determinism | PASS | eager enforced; prefix caching off, max_num_seqs=1 |
231
  | 3 | Frozen input | PASS | token hash matches suite gemma4-31b-it-fidelity-1024x2048-v1 [analysis]: 81d66409b44937fa |
232
  | 4 | Real vocabulary | PASS | scored 262144 real tokens of 262144 declared (0 padding rows) |
233
- | 5 | Manifest binding | PASS | all bound fields present; manifest b5ab5ede01f46551b1932e913620d9554df5f97dd7c5e2bcca05f61db68725ef |
234
- | 6 | Provenance | PASS | torch 2.13.0+cu132, vLLM 0.1.dev20446+gb2bc9171d @ a2ae11e29e34, driver 580.173.02, 4 GPU(s) |
235
  | 7 | Storage integrity | PASS | hidden storage with bitwise-exact replay |
236
  | 8 | Head transparency | PASS | trunk 1.02626820, deployed 1.02626820, delta -2.4355184535806984e-11 |
237
  | 9 | Tail and depth disclosure | PASS | mean 1.02626820, median 0.24318366, max 43.06172943, 4 depth buckets |
238
  | 10 | Comparability | PASS | comparability key fully resolved |
239
  | 11 | Freeze before qualification | NOT_APPLICABLE | partition is 'analysis' |
240
  | 12 | Reusable reference | PASS | suite, reference, head, and checksums present; published reference matches the scored capture on every bound field |
241
- | 14 | Routed-model intervention | PASS | QxQ 1.02626820, BxQ 0.84088786, QxQ - BxQ +0.18538034; natural selections changed at 62.737% of (token, layer) choices; trace 0fcde10d9c35222c |
242
  | 15 | Domain disclosure | PASS | 10 domains disclosed; weakest other_multilingual at 1.36233317, strongest code_docs_issues at 0.74656348, spread 1.8x |
243
  | 16 | Candidate weight binding | PASS | scored weights f1f4146421ee33ad as inspected |
244
  | 17 | Substitution disclosure | PASS | every scored layer used the checkpoint's own quantization parameters |
@@ -252,7 +264,7 @@ Zero baseline: reference against itself scored **0.00000000** over 2047 position
252
  | Platform | Linux-6.8.0-137-generic-x86_64-with-glibc2.39 |
253
  | Python | 3.12.3 |
254
  | vLLM | 0.1.dev20446+gb2bc9171d |
255
- | vLLM commit | a2ae11e29e34294cfaa4d768f1a1d8d8199d1d61 |
256
  | torch | 2.13.0+cu132 |
257
  | torch CUDA runtime | 13.2 |
258
  | cuDNN | 9.20.0 (92000) |
@@ -260,7 +272,7 @@ Zero baseline: reference against itself scored **0.00000000** over 2047 position
260
  | CUDA arch list | sm_75, sm_80, sm_86, sm_90, sm_100, sm_120 |
261
  | nvcc | Cuda compilation tools, release 13.0, V13.0.88 |
262
  | gcc | gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0 |
263
- | glibc / ldd | ldd (Ubuntu GLIBC 2.39-0ubuntu8.8) 2.39 |
264
  | NVIDIA driver | 580.173.02 |
265
  | float32 matmul precision | highest |
266
  | TF32 (matmul / cuDNN) | False / True |
@@ -287,6 +299,11 @@ Credential values are never published. Set but redacted: `HF_TOKEN`.
287
  | `CUDA_HOME` | `/usr/local/cuda-13.0` |
288
  | `HF_TOKEN` | `<redacted>` |
289
  | `NCCL_DETERMINISTIC` | `1` |
 
 
 
 
 
290
  | `VLLM_BATCH_INVARIANT` | `1` |
291
  | `VLLM_MARLIN_USE_ATOMIC_ADD` | `0` |
292
  | `VLLM_MOE_USE_DEEP_GEMM` | `0` |
@@ -298,25 +315,25 @@ Paths are relative to the artifact root, the same paths `checksums.txt` uses. Ve
298
  | Path | Size | What it is |
299
  |---|---|---|
300
  | `gemma-4-26B-A4B-it-AWQ-4bit/report.md` | 22.06 KiB | This document. |
301
- | `gemma-4-26B-A4B-it-AWQ-4bit/report.json` | 566.64 KiB | Every statistic behind it, machine-readable: per-bucket means, percentiles, agreement rates, and the phase timings. |
302
- | `gemma-4-26B-A4B-it-AWQ-4bit/manifest.json` | 87.35 KiB | The capture manifest this result is bound to (Law 5). Scoring refuses to run if the live configuration differs from it. |
303
- | `gemma-4-26B-A4B-it-AWQ-4bit/compliance.json` | 378.57 KiB | The law-by-law receipt, including the comparability key. |
304
- | `baselines/self-kld.json` | 6.89 KiB | The zero-baseline proof required by Law 1: the reference scored against a capture of itself. |
305
  | `suite/suite-manifest.json` | 382.61 KiB | The frozen evaluation input's identity: token hashes per context and per partition, sources, strata, and the analysis/qualification split. |
306
  | `suite/tokens` | 17.32 MiB in 1024 files | The token IDs themselves. These are the evaluation input, not a description of it; retokenizing source text does not reproduce them. |
307
  | `suite/sources.json` | 737.48 KiB | Per-context provenance: dataset, revision, licence, source unit, and the deterministic token offset chosen within the document. |
308
  | `suite/validation/capability-overlap.json` | 1.48 KiB | The benchmark-contamination scan and every document it blocked. |
309
- | `reference/manifest.json` | 87.35 KiB | The reference capture's own manifest: geometry, vocabulary, storage mode, and a hash for every tensor file. |
310
  | `reference` | 11.62 GiB in 771 files | The reusable reference distributions. Pass this directory as `--reference-logits` to score a new candidate against the same reference without loading the reference checkpoint. |
311
  | `reference/lm_head.safetensors` | 1.38 GiB | The reference language-model head, which turns the stored hidden states back into reference logits. |
312
- | `environment/runtime.json` | 5.08 KiB | Machine-readable provenance: torch, CUDA, cuDNN, NCCL, driver, devices, and the captured environment variables. |
313
  | `environment/summary.md` | 1.10 KiB | The same provenance as prose, plus an index of every captured file. |
314
  | `environment/toolchain-nvcc.txt` | 243 B | `nvcc --version` verbatim; `toolchain-gcc.txt` and `toolchain-ldd.txt` sit beside it. |
315
  | `environment/gpu-smi-query.txt` | 54.73 KiB | `nvidia-smi -q` verbatim: ECC state, persistence mode, clocks, and throttle reasons, any of which can move a bitwise result. |
316
  | `environment/pip-freeze.txt` | 4.47 KiB | Every installed package version in the scoring environment. |
317
  | `environment/models` | 28.70 KiB in 7 files | Checkpoint fingerprints: file listing, sizes, config and tokenizer hashes, and `config.json` verbatim for each model scored. |
318
  | `checksums.txt` | 1.13 MiB | `sha256sum --check` compatible over every other file here. This is authoritative for integrity (Law 12). |
319
- | `LAWS.md` | 38.37 KiB | The laws this artifact was produced under, including the override procedure. |
320
 
321
  ## Scope
322
 
 
18
  | Candidate weights SHA-256 | f1f4146421ee33ad |
19
  | Suite | gemma4-31b-it-fidelity-1024x2048-v1 |
20
  | Suite token SHA-256 | 81d66409b44937fa |
21
+ | Capture manifest SHA-256 | fbc447717db774ab |
22
  | Tokenizer | None |
23
  | Scored vocabulary | 262144 |
24
  | Declared vocabulary | 262144 |
 
31
  | Prefix caching | False |
32
  | max_num_seqs | 1 |
33
  | vLLM | 0.1.dev20446+gb2bc9171d |
34
+ | vLLM commit | 60071d1ab732 |
35
  | vLLM dirty digest | e3b0c44298fc1c14 |
36
+ | Numerics digest | 251a9225b37415b9 |
37
  | Compiled extensions | f2fbc7537b0f01f6 |
38
  | FlashInfer | 0.6.17 |
39
  | torch | 2.13.0+cu132 |
40
  | Driver | 580.173.02 |
41
  | GPUs | NVIDIA RTX PRO 6000 Blackwell Workstation Edition, NVIDIA RTX PRO 6000 Blackwell Workstation Edition, NVIDIA RTX PRO 6000 Blackwell Workstation Edition, NVIDIA RTX PRO 6000 Blackwell Workstation Edition |
42
+ | Laws version | 15 |
43
  | Partition | analysis |
44
 
45
+ The commit says when this number was taken. The numerics digest says what took it: a hash of the runtime and the scorer, which moves only when code that can change a logit changes. Comparability is bounded by the digest, so a result stays current across commits that cannot reach a number, and two results carrying the same digest were computed by the same code whatever their commits say.
46
+
47
  ## Routed-model intervention: QxQ and BxQ
48
 
49
  **The first axis is routing source; the second Q is the same unchanged quantized candidate in both runs.** QxQ uses the student's natural expert IDs. BxQ forces the BF16 teacher's expert IDs while the student computes its own gating weights for those experts.
 
55
  | QxQ - BxQ | paired routing-intervention delta; not additive attribution | +0.18538034 | | |
56
  | Exact repeat | two QxQ, two forced-natural, two BxQ samples | certified | | |
57
 
58
+ Natural QxQ selections changed from the teacher at **62.7369%** of (token, layer) choices. BxQ protocol 5; routing trace `c4a98d392c393b11`.
59
 
60
  Natural control used exact-repeat certification: max position delta 0.000e+00 / 0.000e+00; absolute mean delta 0.000e+00 / 0.000e+00; natural route-repeat flips 0.000%.
61
 
 
126
 
127
  Full cells, digests, and the deployed checkpoint's inspection are in [attribution.json](attribution.json).
128
 
129
+ ## Expert kernels: declared against built
130
+
131
+ | Property | Value |
132
+ |---|---|
133
+ | Declared for its experts | `unquantized` |
134
+ | Expert implementation built | `MarlinExperts` |
135
+ | Expert kernel built | `FusedMoEKernel` |
136
+ | Expert layers carrying an activation scale | 0 of 30 |
137
+
138
  ## Routing divergence
139
 
140
  This is the observed selection divergence in the normal QxQ run, not the BxQ intervention and not a QDQ router-weight cell. It compares the student's natural expert IDs with the teacher's recorded IDs over 30 routed layers, 8 experts per token.
 
242
  | 2 | Determinism | PASS | eager enforced; prefix caching off, max_num_seqs=1 |
243
  | 3 | Frozen input | PASS | token hash matches suite gemma4-31b-it-fidelity-1024x2048-v1 [analysis]: 81d66409b44937fa |
244
  | 4 | Real vocabulary | PASS | scored 262144 real tokens of 262144 declared (0 padding rows) |
245
+ | 5 | Manifest binding | PASS | all bound fields present; manifest fbc447717db774ab70ec4c9af8b197f0152475cfa119698fb5c2ee50b5dd1c07 |
246
+ | 6 | Provenance | PASS | torch 2.13.0+cu132, vLLM 0.1.dev20446+gb2bc9171d @ 60071d1ab732, driver 580.173.02, 4 GPU(s) |
247
  | 7 | Storage integrity | PASS | hidden storage with bitwise-exact replay |
248
  | 8 | Head transparency | PASS | trunk 1.02626820, deployed 1.02626820, delta -2.4355184535806984e-11 |
249
  | 9 | Tail and depth disclosure | PASS | mean 1.02626820, median 0.24318366, max 43.06172943, 4 depth buckets |
250
  | 10 | Comparability | PASS | comparability key fully resolved |
251
  | 11 | Freeze before qualification | NOT_APPLICABLE | partition is 'analysis' |
252
  | 12 | Reusable reference | PASS | suite, reference, head, and checksums present; published reference matches the scored capture on every bound field |
253
+ | 14 | Routed-model intervention | PASS | QxQ 1.02626820, BxQ 0.84088786, QxQ - BxQ +0.18538034; natural selections changed at 62.737% of (token, layer) choices; trace c4a98d392c393b11 |
254
  | 15 | Domain disclosure | PASS | 10 domains disclosed; weakest other_multilingual at 1.36233317, strongest code_docs_issues at 0.74656348, spread 1.8x |
255
  | 16 | Candidate weight binding | PASS | scored weights f1f4146421ee33ad as inspected |
256
  | 17 | Substitution disclosure | PASS | every scored layer used the checkpoint's own quantization parameters |
 
264
  | Platform | Linux-6.8.0-137-generic-x86_64-with-glibc2.39 |
265
  | Python | 3.12.3 |
266
  | vLLM | 0.1.dev20446+gb2bc9171d |
267
+ | vLLM commit | 60071d1ab73229321712254b1350dcaaac1c125a |
268
  | torch | 2.13.0+cu132 |
269
  | torch CUDA runtime | 13.2 |
270
  | cuDNN | 9.20.0 (92000) |
 
272
  | CUDA arch list | sm_75, sm_80, sm_86, sm_90, sm_100, sm_120 |
273
  | nvcc | Cuda compilation tools, release 13.0, V13.0.88 |
274
  | gcc | gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0 |
275
+ | glibc / ldd | ldd (Ubuntu GLIBC 2.39-0ubuntu8.9) 2.39 |
276
  | NVIDIA driver | 580.173.02 |
277
  | float32 matmul precision | highest |
278
  | TF32 (matmul / cuDNN) | False / True |
 
299
  | `CUDA_HOME` | `/usr/local/cuda-13.0` |
300
  | `HF_TOKEN` | `<redacted>` |
301
  | `NCCL_DETERMINISTIC` | `1` |
302
+ | `PYTORCH_NVML_BASED_CUDA_CHECK` | `1` |
303
+ | `TORCHINDUCTOR_CACHE_DIR` | `/tmp/torchinductor_phaedawg` |
304
+ | `TORCHINDUCTOR_COMPILE_THREADS` | `1` |
305
+ | `TRITON_CACHE_AUTOTUNING` | `1` |
306
+ | `TRITON_PTXAS_BLACKWELL_PATH` | `/usr/local/cuda-13.0/bin/ptxas` |
307
  | `VLLM_BATCH_INVARIANT` | `1` |
308
  | `VLLM_MARLIN_USE_ATOMIC_ADD` | `0` |
309
  | `VLLM_MOE_USE_DEEP_GEMM` | `0` |
 
315
  | Path | Size | What it is |
316
  |---|---|---|
317
  | `gemma-4-26B-A4B-it-AWQ-4bit/report.md` | 22.06 KiB | This document. |
318
+ | `gemma-4-26B-A4B-it-AWQ-4bit/report.json` | 566.81 KiB | Every statistic behind it, machine-readable: per-bucket means, percentiles, agreement rates, and the phase timings. |
319
+ | `gemma-4-26B-A4B-it-AWQ-4bit/manifest.json` | 87.44 KiB | The capture manifest this result is bound to (Law 5). Scoring refuses to run if the live configuration differs from it. |
320
+ | `gemma-4-26B-A4B-it-AWQ-4bit/compliance.json` | 378.60 KiB | The law-by-law receipt, including the comparability key. |
321
+ | `baselines/self-kld.json` | 7.05 KiB | The zero-baseline proof required by Law 1: the reference scored against a capture of itself. |
322
  | `suite/suite-manifest.json` | 382.61 KiB | The frozen evaluation input's identity: token hashes per context and per partition, sources, strata, and the analysis/qualification split. |
323
  | `suite/tokens` | 17.32 MiB in 1024 files | The token IDs themselves. These are the evaluation input, not a description of it; retokenizing source text does not reproduce them. |
324
  | `suite/sources.json` | 737.48 KiB | Per-context provenance: dataset, revision, licence, source unit, and the deterministic token offset chosen within the document. |
325
  | `suite/validation/capability-overlap.json` | 1.48 KiB | The benchmark-contamination scan and every document it blocked. |
326
+ | `reference/manifest.json` | 87.44 KiB | The reference capture's own manifest: geometry, vocabulary, storage mode, and a hash for every tensor file. |
327
  | `reference` | 11.62 GiB in 771 files | The reusable reference distributions. Pass this directory as `--reference-logits` to score a new candidate against the same reference without loading the reference checkpoint. |
328
  | `reference/lm_head.safetensors` | 1.38 GiB | The reference language-model head, which turns the stored hidden states back into reference logits. |
329
+ | `environment/runtime.json` | 5.42 KiB | Machine-readable provenance: torch, CUDA, cuDNN, NCCL, driver, devices, and the captured environment variables. |
330
  | `environment/summary.md` | 1.10 KiB | The same provenance as prose, plus an index of every captured file. |
331
  | `environment/toolchain-nvcc.txt` | 243 B | `nvcc --version` verbatim; `toolchain-gcc.txt` and `toolchain-ldd.txt` sit beside it. |
332
  | `environment/gpu-smi-query.txt` | 54.73 KiB | `nvidia-smi -q` verbatim: ECC state, persistence mode, clocks, and throttle reasons, any of which can move a bitwise result. |
333
  | `environment/pip-freeze.txt` | 4.47 KiB | Every installed package version in the scoring environment. |
334
  | `environment/models` | 28.70 KiB in 7 files | Checkpoint fingerprints: file listing, sizes, config and tokenizer hashes, and `config.json` verbatim for each model scored. |
335
  | `checksums.txt` | 1.13 MiB | `sha256sum --check` compatible over every other file here. This is authoritative for integrity (Law 12). |
336
+ | `LAWS.md` | 40.20 KiB | The laws this artifact was produced under, including the override procedure. |
337
 
338
  ## Scope
339
 
gemma-4-26B-A4B-it-FP8-dynamic/attribution/gemma-4-26B-A4B-it-qdq-experts-attention-dense_mlp-fp8_per_channel.json CHANGED
@@ -1,5 +1,5 @@
1
  {
2
- "capture_manifest_sha256": "b5ab5ede01f46551b1932e913620d9554df5f97dd7c5e2bcca05f61db68725ef",
3
  "confidence_buckets": [
4
  {
5
  "frac": 0.07217434558703795,
@@ -38,6 +38,7 @@
38
  }
39
  ],
40
  "context_length": 2048,
 
41
  "depth_buckets": [
42
  {
43
  "depth_hi": 511,
@@ -71,6 +72,7 @@
71
  "mean_kld_reverse": 0.6055071098612179,
72
  "median_kld": 0.08827311545610428,
73
  "model_runner_v2": false,
 
74
  "num_positions": 1572096,
75
  "num_rows": 768,
76
  "nvfp4_dense_scale_inspection": {
@@ -8638,10 +8640,11 @@
8638
  "NVIDIA RTX PRO 6000 Blackwell Workstation Edition"
8639
  ],
8640
  "nccl": "2.29.7",
 
8641
  "platform": "Linux-6.8.0-137-generic-x86_64-with-glibc2.39",
8642
  "python": "3.12.3",
8643
  "torch": "2.13.0+cu132",
8644
- "vllm_commit": "a2ae11e29e34294cfaa4d768f1a1d8d8199d1d61",
8645
  "vllm_dirty_digest": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855",
8646
  "vllm_tree_dirty": false
8647
  },
@@ -8744,9 +8747,9 @@
8744
  }
8745
  },
8746
  "timings": {
8747
- "routing_compare": 7.93826940888539,
8748
- "score_forward": 164.40250429091975,
8749
- "student_load": 22.570553320925683
8750
  },
8751
  "top1_agreement": 0.7729655186451718,
8752
  "topk_agreement": {
 
1
  {
2
+ "capture_manifest_sha256": "fbc447717db774ab70ec4c9af8b197f0152475cfa119698fb5c2ee50b5dd1c07",
3
  "confidence_buckets": [
4
  {
5
  "frac": 0.07217434558703795,
 
38
  }
39
  ],
40
  "context_length": 2048,
41
+ "declared_expert_activation_quant": [],
42
  "depth_buckets": [
43
  {
44
  "depth_hi": 511,
 
72
  "mean_kld_reverse": 0.6055071098612179,
73
  "median_kld": 0.08827311545610428,
74
  "model_runner_v2": false,
75
+ "moe_backend_named": null,
76
  "num_positions": 1572096,
77
  "num_rows": 768,
78
  "nvfp4_dense_scale_inspection": {
 
8640
  "NVIDIA RTX PRO 6000 Blackwell Workstation Edition"
8641
  ],
8642
  "nccl": "2.29.7",
8643
+ "numerics_digest": "251a9225b37415b91fc58d975b0670fc4b481e6f5a816b663573c42e161438f8",
8644
  "platform": "Linux-6.8.0-137-generic-x86_64-with-glibc2.39",
8645
  "python": "3.12.3",
8646
  "torch": "2.13.0+cu132",
8647
+ "vllm_commit": "60071d1ab73229321712254b1350dcaaac1c125a",
8648
  "vllm_dirty_digest": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855",
8649
  "vllm_tree_dirty": false
8650
  },
 
8747
  }
8748
  },
8749
  "timings": {
8750
+ "routing_compare": 8.198981787543744,
8751
+ "score_forward": 165.1197206461802,
8752
+ "student_load": 23.07501409109682
8753
  },
8754
  "top1_agreement": 0.7729655186451718,
8755
  "topk_agreement": {
gemma-4-26B-A4B-it-FP8-dynamic/attribution/gemma-4-26B-A4B-it-qdq-experts-fp8_per_channel.json CHANGED
@@ -1,5 +1,5 @@
1
  {
2
- "capture_manifest_sha256": "b5ab5ede01f46551b1932e913620d9554df5f97dd7c5e2bcca05f61db68725ef",
3
  "confidence_buckets": [
4
  {
5
  "frac": 0.07217434558703795,
@@ -38,6 +38,7 @@
38
  }
39
  ],
40
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