Ornith-1.5-35B-A3B — ROCmFPX renders
MagicQuant's per-group scheme assignments for
ornith-ai/Ornith-1.5-35B-A3B
rendered into
ROCmFPX tensor types (
q*_0_rocmfpx), a quant family aimed
at AMD ROCm inference. Same search that produced the
MagicQuant GGUFs,
different render target.
Pins: MagicQuant ed17991, Foundry 2f99202.
⚠ Engine requirement — read before downloading
These files use ROCmFPX tensor types that stock llama.cpp cannot load.
They require a ROCmFPX fork build. A build that is too old fails with
invalid ggml type on load; the types are not a stock-llama.cpp feature and
no amount of rebuilding mainline will help. If you are not already running a
ROCmFPX fork, you want the MagicQuant repo linked above instead.
Files
| file | size |
|---|
Ornith-1.5-35B-A3B-ROCMFPX-MQ-Q4.gguf | 20.50 GiB |
Ornith-1.5-35B-A3B-ROCMFPX-MQ-Q6.gguf | 28.57 GiB |
mmproj-Ornith-1.5-35B-A3B-f16.gguf | 0.86 GiB |
Both passed the pipeline's perplexity smoke gate (6.55 and 6.50 respectively).
Those smoke numbers are not comparable to the MagicQuant repo's PPL table.
The smoke gate is a short run against a different corpus path than the search
used, so the scale differs for instrument reasons, not quality reasons. No
matched-instrument comparison between these ROCmFPX renders and their
MagicQuant counterparts has been run, so this repo makes no claim about
which is better. If that comparison matters to you, measure both yourself
under one instrument.
What is deliberately absent
- No Q5. The pipeline's band guard refused it: rendering MagicQuant's Q5
configuration into ROCmFPX types predicts 26.87 GiB against a 66.13 GiB
baseline — a 0.406 ratio, which is the Q6 band, not Q5. Publishing it as
"Q5" would have mislabelled it, so it was not built.
- No
Q6_0_ROCMFPX_AGENT variant. It built, then segfaulted under
perplexity evaluation (exited -11). The pipeline quarantined it
automatically and aborted before upload. It is a crash, not a quality miss,
and it is not published because it does not work.
Both absences are disclosed rather than quietly dropped, which is the point.
Notes
- Vision requires the
mmproj file alongside the model.
- Chat template embedded and verified present before upload; vocab metadata
(
tokenizer.ggml.token_type) is INT32 per spec.
- Built and measured on an AMD Strix Halo (Ryzen AI MAX+ 395, gfx1151) host.
