Sign up

Shiftedx/ornith-1.5-35b-a3b-attention8-bf16recurrence-vision-mtplx

🤗 Hugging Face sourceimage-text-to-textmit35.1B params70 GBsafetensors✓ Checksums witnessedupdated today
No torrent yet →

Ornith 1.5 35B-A3B — MLX Vision + Native MTP

Hybrid MLX quant of ornith-ai/Ornith-1.5-35B-A3B, pinned to revision 10fbf86fed7ecee4a061f8b499a618f46001cac1.

Artifact

  • 4-bit affine expert body with 8-bit attention, routing, embeddings, LM head, and late-layer projections
  • 60 recurrent tensors retained in BF16
  • 333 native BF16 vision tensors
  • 785 native BF16 MTP tensors in mtp/weights.safetensors
  • Recommended runtime: MTPLX 2.9.1, MLX 0.32.1, MLX-LM 0.31.3
  • Recommended speculative depth: D3

Run

mtplx serve \
  --model Shiftedx/ornith-1.5-35b-a3b-attention8-bf16recurrence-vision-mtplx \
  --profile sustained \
  --depth 3 \
  --mtp \
  --reasoning off

Local qualification

Tested on an M4 Max with 64 GB unified memory.

Gate Result
Executable Python tasks 8/8
Text exact-output smoke pass
Vision smoke pass
MTP tensor gate 785/785 exact

The final three-prompt, 512-token MTPLX sweep selected D3 at 109.0 decode tok/s. D1, D2, and D3 all passed the quality gate. Fans remained on automatic, so treat the speed as a host-specific measurement rather than a universal benchmark.

Notes

Vision requires a compatible MLX-VLM or MTPLX runtime. Review generated code and tool calls before execution. The parent model and this derivative use the upstream MIT license; see the parent repository for original training and architecture details.