⚠️ STOCK
llama.cppWILL NOT LOAD THIS MODEL🚀 37.86 tok/s on a 119B MoE — 63.07 GiB, 7 GiB smaller than UD-Q4_K_XL.
Mistral-Small-4-119B-A6.5B — ROCmFP4 (tier 102 COHERENT) GGUF
A 4-bit ROCmFP4 quantization for AMD gfx1151 (Ryzen AI MAX+ 395 / Strix Halo), quantized from BF16 (222 GiB) — a lossless source, not a requantization of a lower-bit build.
| File | Mistral-Small-4-119B-2603-Q4_0_ROCMFP4_COHERENT.gguf (sharded) |
| Size | 63.07 GiB |
| BPW | 4.55 |
| ftype | Q4_0_ROCMFP4_COHERENT (102) |
⛔ Requires a llama.cpp with the ROCmFP4 quant types
Q4_0_ROCMFP4_COHERENT (ftype 102) exists only in
charlie12345/ROCmFPX, not upstream llama.cpp.
Ignore the auto-generated "Use this model" commands above.
Files — where each build lives
| build | ftype | size | where |
|---|---|---|---|
| 4-bit COHERENT (2 shards) | 102 | 63.07 GiB | in this repo |
| 8-bit plain | 111 | 114.38 GiB | in this repo · also at …-ROCmFPX-Q8_0-GGUF |
| 8-bit AGENT | 115 | 116.15 GiB | ➡️ …-ROCmFPX-Q8_0-AGENT-GGUF |
The AGENT build is hosted in its own repo rather than mirrored here — at ~116 GiB the duplication is not worth it, and (see the warning above) neither 8-bit build fits in GPU memory on a 128 GB Strix Halo. For a single Strix Halo, use the 4-bit build in this repo.
The separate per-quant repos exist so a user searching HF for a specific quant finds it directly.
All quant variants
| variant | ftype | size | bpw | GPU on 128 GB Strix Halo | decode |
|---|---|---|---|---|---|
| 4-bit COHERENT | 102 | 63.07 GiB | 4.55 | ✅ fits | 37.86 tok/s |
| 8-bit AGENT | 115 | 116.15 GiB | 8.39 | ⛔ does not fit | not measurable on this box |
| 8-bit plain | 111 | 114.38 GiB | 8.26 | ⛔ does not fit | not measurable on this box |
Repos: 4-bit · 8-bit AGENT · 8-bit plain
Measured
Ryzen AI MAX+ 395 (gfx1151, 128 GB unified, ROCm 7.2.4). Median of 3+, warm-up discarded, otherwise-idle box. Correctness at the model's official sampling.
| build | size | decode (median) | range |
|---|---|---|---|
| this build | 63.07 GiB | 37.86 | [37.83 – 38.65] (tight) |
| UD-Q4_K_XL | 70 GiB | 18.75 | [15.99 – 34.30] (wide) |
Ranges disjoint (34.30 < 37.83). The median ratio looks like +102%, but the baseline's own variance is large — we report the win without leaning on that headline number. Note the baseline is UD-Q4_K_XL, not Q4_K_M.
Correctness: 17×23 ⇒ ✅ 391 · capital of Japan ⇒ ✅ Tokyo · days in 2024 ⇒ ✅ 366
Per-tensor types (audited in the finished file)
output.weight Q6_K · token_embd Q6_K · shexp 108× Q8_0 (shared-expert protection) · router 36× F32 · norms 145× F32 · bulk TYPE_100 (288)
119B total / 6.5B active. Built with --tensor-type shexp=q8_0; shared experts are dense (they see every token) so their error is systematic, not averaged.
What was NOT measured
- No perplexity run, and no quality A/B against the baseline or the source. The checks above are memorized-fact prompts — necessary but not sufficient; a damaged model can pass them.
- No long-context testing.
- No tool-calling evaluation.
Base model licence inherited; credit for the model goes to its authors.