ornith-1.5-9b-attention8-bf16recurrence-vision-mlx
Attention-8 + BF16-recurrence MLX hybrid with the parent model's BF16 vision tower. Built from Ornith-1.5-9B revision 98db59b for Apple Silicon.
Format
- Size: 8.87 GB
- Language trunk: 130 affine-8 modules, 72 affine-4 modules, 48 recurrent-input modules in BF16
- Vision: 333 same-parent BF16 tensors
- Context metadata: 262,144 tokens
- Runtime: autoregressive MLX-LM/MLX-VLM
- Native MTP: unavailable; the upstream checkpoint contains no
mtp.*tensors
Exact precision and conversion records are included in BUILD_RECIPE.json and conversion_receipt.json. Immutable weight revision: c35e08d.
Usage
python -m mlx_vlm.generate \
--model Shiftedx/ornith-1.5-9b-attention8-bf16recurrence-vision-mlx \
--image image.jpg \
--prompt "Describe this image." \
--max-tokens 256
Qualification
ShiftedX Bench v0.3.0 commit 3bbb0bfa01e33503163cb34ef52b4d507e456265, Apple M4 Max / 64 GiB, thinking enabled, medium reasoning, temperature 1, top-p 0.95, top-k 20, KV cache off:
| Lane | Result | Mean decode | Peak active memory |
|---|---|---|---|
| Quality | 4/10 | 52.2 tok/s | 8.28 GB |
| Long context | 2/15 | 46.0 tok/s | 7.93 GB |
| Tools | 6/6 | 53.8 tok/s | 9.38 GB |
| Agentic | 1/2 | — | — |
| Vision, native MLX-VLM | 2/4 strict; 4/4 semantic | — | — |
Text lanes used MTPLX 2.7.1 in stock autoregressive mode. Vision used native MLX-VLM because MTPLX AR rejects image content. The two strict vision misses were correct answers wrapped in Markdown fences. Structural loading and deterministic text/vision smokes passed. Quantization can change behavior; see the parent model card for intended use and license details.