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---
base_model: microsoft/FastContext-1.0-4B-SFT
license: mit
library_name: gguf
tags:
- gguf
- rocmfp4
- qwen3
- fastcontext
- subagent
- repository-exploration
- coder
- agentic
- imatrix
- strix-halo
- amd
- rocm
- vulkan
language:
- en
base_model_relation: quantized
---

<div style="border:2px solid currentColor; font-family:ui-monospace,'SF Mono','Cascadia Mono',Consolas,'Liberation Mono',monospace;">
  <div style="border-bottom:1px solid currentColor; padding:6px 12px; font-size:11px; letter-spacing:3px; text-transform:uppercase; opacity:0.7; text-align:center;">PLUNDERSTRUCK // ROCmFP4 QUANTIZED MODEL // STRIX HALO · gfx1151</div>
  <div style="padding:14px; display:flex; flex-wrap:wrap; align-items:center; justify-content:center; gap:18px;">
<pre style="margin:0; flex:0 0 auto; font-family:ui-monospace,'SF Mono','Cascadia Mono',Consolas,monospace; font-size:5px; line-height:1.1; letter-spacing:0;">
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</pre>
    <div style="flex:0 0 auto; font-size:30px; font-weight:300; opacity:0.55; padding:0 2px;">+</div>
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</pre>
    <div style="flex:0 1 auto; max-width:100%; text-align:center;">
      <div style="font-size:23px; font-weight:800; letter-spacing:1px;">FASTCONTEXT-1.0-4B</div>
      <div style="font-size:12.5px; letter-spacing:1px; opacity:0.8; margin-top:5px;"><span style="white-space:nowrap;">4-BIT ROCmFP4</span> · <span style="white-space:nowrap;">QWEN3 DENSE 4B</span> · <span style="white-space:nowrap;">REPO-EXPLORATION SUBAGENT</span> · <span style="white-space:nowrap;">CODE-WEIGHTED IMATRIX</span> · <span style="white-space:nowrap;">SINGLE AMD APU</span></div>
    </div>
  </div>
  <table style="display:table; table-layout:fixed; width:100%; margin:0; border-collapse:collapse; border-radius:0; font-family:ui-monospace,'SF Mono',Consolas,monospace; font-size:12px;">
    <tr>
      <td style="border-top:1px solid currentColor; border-right:1px solid currentColor; padding:8px 12px;"><div style="font-size:10px; letter-spacing:1px; opacity:0.6;">FORMAT</div><div style="font-weight:700;">ROCmFP4 4-BIT</div></td>
      <td style="border-top:1px solid currentColor; border-right:1px solid currentColor; padding:8px 12px;"><div style="font-size:10px; letter-spacing:1px; opacity:0.6;">PRECISION</div><div style="font-weight:700;">~4.5 BPW</div></td>
      <td style="border-top:1px solid currentColor; border-right:1px solid currentColor; padding:8px 12px;"><div style="font-size:10px; letter-spacing:1px; opacity:0.6;">ARCH</div><div style="font-weight:700;">QWEN3 DENSE</div></td>
      <td style="border-top:1px solid currentColor; padding:8px 12px;"><div style="font-size:10px; letter-spacing:1px; opacity:0.6;">CONTEXT</div><div style="font-weight:700;">256 K</div></td>
    </tr>
    <tr>
      <td style="border-top:1px solid currentColor; border-right:1px solid currentColor; padding:8px 12px;"><div style="font-size:10px; letter-spacing:1px; opacity:0.6;">PARAMS</div><div style="font-weight:700;">4B DENSE</div></td>
      <td style="border-top:1px solid currentColor; border-right:1px solid currentColor; padding:8px 12px;"><div style="font-size:10px; letter-spacing:1px; opacity:0.6;">DRAFT</div><div style="font-weight:700;">NO MTP</div></td>
      <td style="border-top:1px solid currentColor; border-right:1px solid currentColor; padding:8px 12px;"><div style="font-size:10px; letter-spacing:1px; opacity:0.6;">BACKEND</div><div style="font-weight:700;">VULKAN0</div></td>
      <td style="border-top:1px solid currentColor; padding:8px 12px;"><div style="font-size:10px; letter-spacing:1px; opacity:0.6;">LICENSE</div><div style="font-weight:700;">MIT</div></td>
    </tr>
  </table>
</div>

<div style="border:2px solid #dc2626; padding:10px 13px; font-family:ui-monospace,'SF Mono',Consolas,monospace; font-size:12.5px; margin:14px 0;">
<b style="color:#dc2626; letter-spacing:1px;">⚠ REQUIRES THE ROCmFP4 FORK</b><br>
The custom <code>q4_0_rocmfp4</code> / <code>q4_0_rocmfp4_fast</code> tensor types <b>will not load in stock llama.cpp, LM Studio, or Ollama</b>. Build/run with <a href="https://github.com/charlie12345/ROCmFPX">charlie12345/ROCmFPX</a> · branch <code>mtp-rocmfp4-strix</code>.
</div>

<div style="border:1px solid currentColor; padding:8px 13px; font-family:ui-monospace,'SF Mono',Consolas,monospace; font-size:12px; margin:14px 0; opacity:0.85;">
<b>NOTE //</b> Ignore HuggingFace's auto-detected "F16"/16-bit badge — its parser can't read ROCmFP4 and mislabels the file. These are <b>~4.5 bpw 4-bit</b> ROCmFP4 files; pick by filename in <i>Files and versions</i>.
</div>

Experimental **AMD Strix Halo (gfx1151)** quant of [**microsoft/FastContext-1.0-4B-SFT**](https://huggingface.co/microsoft/FastContext-1.0-4B-SFT) — Microsoft's **repository-exploration subagent** for coding agents. Instead of one model both exploring the repo and solving the task, FastContext is invoked on demand by a main agent, fires **parallel read-only tool calls** (READ / GLOB / GREP), and returns **compact file paths + line ranges** as focused context. Architecturally it's a plain **Qwen3 dense 4B** (`Qwen3ForCausalLM`, 36 layers, hidden 2560, 256K context, MIT-licensed), here in the custom **ROCmFP4** 4-bit format, **imatrix-quantized**.

<div style="font-family:ui-monospace,'SF Mono',Consolas,monospace; font-weight:800; font-size:14px; letter-spacing:2px; text-transform:uppercase; border-bottom:2px solid currentColor; padding-bottom:5px; margin:26px 0 12px;"><span style="color:#ea580c;">01</span> · FILES</div>

<div style="overflow:hidden; border-radius:0;">
<table style="width:100%; border-collapse:collapse; border-radius:0; font-family:ui-monospace,'SF Mono',Consolas,monospace; font-size:12.5px;">
<thead><tr>
<th style="border:1px solid currentColor; padding:7px 10px; text-align:left; text-transform:uppercase; font-size:10px; letter-spacing:1px;">File</th>
<th style="border:1px solid currentColor; padding:7px 10px; text-align:left; text-transform:uppercase; font-size:10px; letter-spacing:1px;">Body</th>
<th style="border:1px solid currentColor; padding:7px 10px; text-align:left; text-transform:uppercase; font-size:10px; letter-spacing:1px;">Size</th>
<th style="border:1px solid currentColor; padding:7px 10px; text-align:left; text-transform:uppercase; font-size:10px; letter-spacing:1px;">Pick if</th>
</tr></thead>
<tbody>
<tr><td style="border:1px solid currentColor; padding:7px 10px;"><code>…-STRIX-embF16-imatrix.gguf</code> ★</td><td style="border:1px solid currentColor; padding:7px 10px;">fast</td><td style="border:1px solid currentColor; padding:7px 10px;">2.7 GB</td><td style="border:1px solid currentColor; padding:7px 10px;"><b>the speed build</b> — best speed/quality balance: f16 tied embeddings/head on the fast single-scale body</td></tr>
<tr><td style="border:1px solid currentColor; padding:7px 10px;"><code>…-Q6_0_ROCMFPX_AGENT-bm25imatrix.gguf</code></td><td style="border:1px solid currentColor; padding:7px 10px;">Q6 · agent</td><td style="border:1px solid currentColor; padding:7px 10px;">3.8 GB</td><td style="border:1px solid currentColor; padding:7px 10px;"><b>the fidelity build</b> — 6-bit ROCmFPX body on the <b>agent</b> profile (structured-output tensors protected: Q6/Q5_K attention, more FFN-down) + bm25 imatrix; closest to BF16 for tool-call/code work</td></tr>
</tbody>
</table>
</div>

Two builds. The **★ speed build** keeps the quality lever that's actually *felt* — genuine **f16 embeddings (from BF16), which also serve as the output head since the model ties them** — on the fast single-scale `q4_0_rocmfp4_fast` body + a code-weighted imatrix (see §04): the best speed/quality balance for Strix Halo. The **Q6 · agent fidelity build** uses the 6-bit `q6_0_rocmfpx` body on the **ROCmFPX agent profile** (which protects the structured-output pathways — attention K/V at Q6_K/Q5_K, more FFN-down boosted) + a bm25-weighted imatrix: a bit larger/slower, but the closest to BF16 for precise tool-call/code output. Both have the Qwen (ChatML) chat template **baked in** — just pass `--jinja`.

<div style="border:1px solid currentColor; padding:8px 13px; font-family:ui-monospace,'SF Mono',Consolas,monospace; font-size:12px; margin:12px 0; opacity:0.85;">
<b>NOTE // TIED EMBEDDINGS.</b> FastContext has <code>tie_word_embeddings=True</code>, so there's <b>no separate output head</b> — the token-embedding tensor doubles as the lm-head. Setting <code>--token-embedding-type f16</code> therefore gives an <b>f16 embedding <i>and</i> f16 output head</b> in one (no <code>headQ6</code> variant needed — f16 already beats Q6 there).
</div>

<div style="font-family:ui-monospace,'SF Mono',Consolas,monospace; font-weight:800; font-size:14px; letter-spacing:2px; text-transform:uppercase; border-bottom:2px solid currentColor; padding-bottom:5px; margin:26px 0 12px;"><span style="color:#ea580c;">02</span> · QUICK START</div>

Run from the folder holding the `.gguf` (the Qwen ChatML template is baked in — just pass `--jinja`):

```bash
env HSA_OVERRIDE_GFX_VERSION=11.5.1 GGML_HIP_ENABLE_UNIFIED_MEMORY=1 \
llama-server \
  -m FastContext-1.0-4B-SFT-ROCmFP4-STRIX-embF16-imatrix.gguf \
  --alias fastcontext-4b \
  --host 0.0.0.0 \
  --port 8080 \
  -c 262144 \
  -ctk f16 \
  -ctv f16 \
  --temp 0.7 \
  --top-p 0.8 \
  --top-k 20 \
  -dev Vulkan0 \
  -ngl 999 \
  -fa on \
  -b 2048 \
  -ub 256 \
  -t 16 \
  -tb 16 \
  -cpent 256 \
  -ctxcp 32 \
  --cache-reuse 256 \
  --cache-ram 65536 \
  --jinja \
  --parallel 1 \
  --metrics \
  --no-mmap
```

<div style="overflow:hidden; border-radius:0;">
<table style="width:100%; border-collapse:collapse; border-radius:0; font-family:ui-monospace,'SF Mono',Consolas,monospace; font-size:12px;">
<thead><tr>
<th style="border:1px solid currentColor; padding:6px 10px; text-align:left; text-transform:uppercase; font-size:10px; letter-spacing:1px; width:40%;">Flag</th>
<th style="border:1px solid currentColor; padding:6px 10px; text-align:left; text-transform:uppercase; font-size:10px; letter-spacing:1px;">Function</th>
</tr></thead>
<tbody>
<tr><td style="border:1px solid currentColor; padding:6px 10px;"><code>HSA_OVERRIDE_GFX_VERSION=11.5.1</code></td><td style="border:1px solid currentColor; padding:6px 10px;">treat the APU as gfx1151 (Strix Halo)</td></tr>
<tr><td style="border:1px solid currentColor; padding:6px 10px;"><code>GGML_HIP_ENABLE_UNIFIED_MEMORY=1</code></td><td style="border:1px solid currentColor; padding:6px 10px;">allow use of the full 128 GB unified memory</td></tr>
<tr><td style="border:1px solid currentColor; padding:6px 10px;"><code>-dev Vulkan0</code></td><td style="border:1px solid currentColor; padding:6px 10px;">run on Vulkan — fastest backend for ROCmFP4 on Strix Halo</td></tr>
<tr><td style="border:1px solid currentColor; padding:6px 10px;"><code>-ngl 999 · -fa on</code></td><td style="border:1px solid currentColor; padding:6px 10px;">offload all layers · flash attention</td></tr>
<tr><td style="border:1px solid currentColor; padding:6px 10px;"><code>-c 262144</code></td><td style="border:1px solid currentColor; padding:6px 10px;">context length (256K)</td></tr>
<tr><td style="border:1px solid currentColor; padding:6px 10px;"><code>-b 2048 · -ub 256 · -t/-tb 16</code></td><td style="border:1px solid currentColor; padding:6px 10px;">prefill batch / micro-batch · CPU threads</td></tr>
<tr><td style="border:1px solid currentColor; padding:6px 10px;"><code>-ctk f16 · -ctv f16</code></td><td style="border:1px solid currentColor; padding:6px 10px;">f16 KV cache — how we run it (cheap on a 4B); drop to <code>q8_0</code>/<code>q4_0</code> to use less memory at deep context</td></tr>
<tr><td style="border:1px solid currentColor; padding:6px 10px;"><code>-cpent · -ctxcp · --cache-reuse · --cache-ram 65536</code></td><td style="border:1px solid currentColor; padding:6px 10px;">cross-turn KV checkpointing + 64 GB resident reuse cache</td></tr>
<tr><td style="border:1px solid currentColor; padding:6px 10px;"><code>--temp 0.7 --top-p 0.8 --top-k 20</code></td><td style="border:1px solid currentColor; padding:6px 10px;">Qwen3 recommended sampling (instruct/non-thinking)</td></tr>
<tr><td style="border:1px solid currentColor; padding:6px 10px;"><code>--jinja --parallel 1 --metrics --no-mmap</code></td><td style="border:1px solid currentColor; padding:6px 10px;">apply baked ChatML template · single slot · metrics · weights in RAM</td></tr>
</tbody>
</table>
</div>

<div style="border:1px solid currentColor; padding:8px 13px; font-family:ui-monospace,'SF Mono',Consolas,monospace; font-size:12px; margin:12px 0; opacity:0.85;">
<b>NOTE //</b> No <code>--spec-*</code> / <code>--spec-type draft-mtp</code> flags — this arch has <b>no MTP head</b> (see §04). It's already fast on its own.
</div>

<div style="font-family:ui-monospace,'SF Mono',Consolas,monospace; font-weight:800; font-size:14px; letter-spacing:2px; text-transform:uppercase; border-bottom:2px solid currentColor; padding-bottom:5px; margin:26px 0 12px;"><span style="color:#ea580c;">03</span> · USING IT AS A SUBAGENT</div>

FastContext isn't a general chat model — it's a **repository-exploration subagent** meant to be **called by your main coding agent**, not driven directly. The intended loop: the main agent delegates "find the relevant context for X" → FastContext issues **parallel read-only tool calls** (`READ`, `GLOB`, `GREP`) → returns **compact file paths + line ranges**, which the main agent folds into its own context to do the actual work. The point is to keep repo-exploration tokens *out* of the main agent's window.

- **Chat template:** Qwen (ChatML) is baked into the GGUF — just pass `--jinja`.
- **Tool calling:** it emits structured `READ`/`GLOB`/`GREP` calls — wire those tools into your harness and use a Qwen/Hermes-style tool-call parser so they're parsed rather than printed. **See the [upstream model card](https://huggingface.co/microsoft/FastContext-1.0-4B-SFT) for the exact subagent protocol + tool schema** (it expects a specific invocation format).
- **Sampling:** temp `0.7`, top-p `0.8`, top-k `20` (Qwen3 instruct defaults) — already set in §02.

<div style="border:1px solid currentColor; padding:8px 13px; font-family:ui-monospace,'SF Mono',Consolas,monospace; font-size:12px; margin:12px 0; opacity:0.85;">
<b>NOTE //</b> It's small (4B) and fast (~68 t/s, §04) by design — a cheap, disposable explorer you can fan out in parallel next to a larger main model on the same box. The cross-turn reuse cache (<code>--cache-reuse</code> / <code>--cache-ram</code>) keeps repeated exploration over the same repo cheap.
</div>

<div style="font-family:ui-monospace,'SF Mono',Consolas,monospace; font-weight:800; font-size:14px; letter-spacing:2px; text-transform:uppercase; border-bottom:2px solid currentColor; padding-bottom:5px; margin:26px 0 12px;"><span style="color:#ea580c;">04</span> · PERFORMANCE &amp; QUALITY</div>

<div style="overflow:hidden; border-radius:0;">
<table style="width:100%; border-collapse:collapse; border-radius:0; font-family:ui-monospace,'SF Mono',Consolas,monospace; font-size:12.5px;">
<tbody>
<tr><td style="border:1px solid currentColor; padding:8px 11px; width:42%;">DECODE · short context</td><td style="border:1px solid currentColor; padding:8px 11px; font-weight:700;">~68 t/s (Vulkan / Ryzen AI Max+ 395)</td></tr>
<tr><td style="border:1px solid currentColor; padding:8px 11px;">SPECULATIVE DECODE</td><td style="border:1px solid currentColor; padding:8px 11px; font-weight:700;">none (no MTP head)</td></tr>
<tr><td style="border:1px solid currentColor; padding:8px 11px;">CONTEXT</td><td style="border:1px solid currentColor; padding:8px 11px;">256K native (dense attention)</td></tr>
<tr><td style="border:1px solid currentColor; padding:8px 11px;">QUANTIZATION</td><td style="border:1px solid currentColor; padding:8px 11px;">fast single-scale body + f16 tied emb/head + code-weighted imatrix</td></tr>
</tbody>
</table>
</div>

**This is the best speed/quality balance in ROCmFP4 — by design, not the absolute fastest.** It keeps the one quality lever that's actually *felt* — genuine **f16 embeddings**, which on this model **double as the output head** (`tie_word_embeddings=True`), so a single f16 tensor sharpens both the input and output side at near-zero decode cost (it's a lookup, not a matmul) — on top of the fast single-scale `q4_0_rocmfp4_fast` body + a code-weighted imatrix. A leaner Q5-embedding build would shave a couple tok/s but degrades that lever; we keep full f16.

We didn't re-run the entire rocmfp4 lever sweep on this 4B. We ran it exhaustively on the larger **[Qwen3.6-27B](https://huggingface.co/plunderstruck/Qwen3.6-27B-MTP-ROCmFP4-GGUF)** — KL divergence vs the BF16 reference plus `llama-bench` decode across an all-dual-scale body, selective higher-precision tensors, and full f16 embeddings. The finding there: **an all-dual-scale body and selective higher-precision tensors both cost decode speed for a KL improvement that sat inside the measurement noise**, so the fast single-scale body + f16 embeddings is the balance point. That conclusion carries to FastContext — same format, same kernels — so we ship the one build that lands on it rather than a slower variant that wins KL only inside the noise.

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<b>WANT MAXIMUM FIDELITY INSTEAD OF SPEED?</b> Grab the <b><code>…-Q6_0_ROCMFPX_AGENT-bm25imatrix.gguf</code></b> in this repo — a 6-bit ROCmFPX body on the agent profile (structured-output tensors protected), the closest to BF16 here. If you want even higher, a <b>Q6_K / Q8 GGUF of the base</b> from <a href="https://huggingface.co/microsoft/FastContext-1.0-4B-SFT"><b>microsoft/FastContext-1.0-4B-SFT</b></a> also runs on this same fork.
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**Fast on its own.** ~68 t/s short-context decode on a Ryzen AI Max+ 395 (Vulkan0, measured `llama-bench tg128`). It's a 4B dense Qwen3 with **no MTP head**, so there's no speculative decoding — it doesn't need it, and at 4B it's a cheap explorer you can run several of in parallel.

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<b>NOTE // imatrix.</b> This build is quantized <b>with</b> an importance matrix (Kalomaze <code>groups_merged</code> + froggeric <code>code</code>/<code>technical</code>, via <a href="https://huggingface.co/datasets/froggeric/imatrix">froggeric/imatrix</a>), computed on this model's BF16. We did <b>not</b> run a separate imatrix-vs-no-imatrix ablation on this 4B; at 4+ bpw imatrix is a free polish, not a transformation. Scope note: any fidelity-vs-BF16 figures are a held-out measurement, <b>not</b> an absolute coding benchmark.
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```bash
# 0) convert the safetensors -> BF16 GGUF (plain qwen3 dense; no MTP, tied embeddings)
python convert_hf_to_gguf.py FastContext-1.0-4B-SFT/ --outtype bf16 --outfile FastContext-1.0-4B-SFT-BF16.gguf

# 1) imatrix on the BF16 (general+code: Kalomaze groups_merged + froggeric code/technical)
llama-imatrix -m FastContext-1.0-4B-SFT-BF16.gguf -f general+code-calib.txt -o fastcontext-4b.imatrix -c 512 -ngl 999

# 2) THE ONE BUILD: fast single-scale STRIX body + f16 tied emb/head + imatrix (the ★ file) — the balance point (§04).
#    tie_word_embeddings=True -> --token-embedding-type f16 also gives an f16 output head; no --output-tensor-type.
llama-quantize --token-embedding-type f16 --imatrix fastcontext-4b.imatrix \
  FastContext-1.0-4B-SFT-BF16.gguf  FastContext-1.0-4B-SFT-ROCmFP4-STRIX-embF16-imatrix.gguf  Q4_0_ROCMFP4_STRIX
```

> Experimental research build for AMD Strix Halo — hardware/driver/prompt-sensitive, may not reproduce elsewhere. Not native FP4 tensor-core execution.

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<tr><td style="border:1px solid currentColor; padding:8px 11px; width:26%;">BASE MODEL</td><td style="border:1px solid currentColor; padding:8px 11px;"><a href="https://huggingface.co/microsoft/FastContext-1.0-4B-SFT">microsoft/FastContext-1.0-4B-SFT</a> (MIT, Microsoft) · repository-exploration subagent · Qwen3 dense 4B (<code>Qwen3ForCausalLM</code>)</td></tr>
<tr><td style="border:1px solid currentColor; padding:8px 11px;">CALIBRATION</td><td style="border:1px solid currentColor; padding:8px 11px;">Kalomaze <code>groups_merged</code> + froggeric <code>code</code>/<code>technical</code> via <a href="https://huggingface.co/datasets/froggeric/imatrix">froggeric/imatrix</a></td></tr>
<tr><td style="border:1px solid currentColor; padding:8px 11px;">FORMAT + RUNTIME</td><td style="border:1px solid currentColor; padding:8px 11px;"><a href="https://github.com/charlie12345/ROCmFPX">charlie12345/ROCmFPX</a> (based on llama.cpp, MIT)</td></tr>
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</table>
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*Derivative quantization — verify the base model's license before redistribution / use.*