mlx-optiq
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Ornith-1.0-35B-OptiQ-4bit

deepreinforce-ai/Ornith-1.0-35B, quantized with OptiQ by npario for Apple Silicon; mixture-of-experts, takes images.

communityvisionMoE
On disk23.1 GB
Memoryabout 28 GB
Parent score77.42 Qwen3.5-35B-A3B-OptiQ-4bit
Imagesyes

This model reuses the per-layer bit allocation of Qwen3.5-35B-A3B-OptiQ-4bit, whose measured Capability Score is 77.42.

The parent's Capability Score breakdown

This model has no Capability Score of its own. The chart shows the six metrics behind its parent Qwen3.5-35B-A3B-OptiQ-4bit's score of 77.42, taken from the parent's model card and compared with uniform 4-bit.

  • Qwen3.5-35B-A3B-OptiQ-4bit
  • Uniform 4-bit
The parent's Capability Score breakdown: Qwen3.5-35B-A3B-OptiQ-4bitMMLU: Qwen3.5-35B-A3B-OptiQ-4bit 86.7, Uniform 4-bit 85.9; GSM8K: Qwen3.5-35B-A3B-OptiQ-4bit 89.9, Uniform 4-bit 87.5; IFEval: Qwen3.5-35B-A3B-OptiQ-4bit 71.9, Uniform 4-bit 73.2; BFCL-V3: Qwen3.5-35B-A3B-OptiQ-4bit 93.0, Uniform 4-bit 89.5; HumanEval: Qwen3.5-35B-A3B-OptiQ-4bit 89.0, Uniform 4-bit 88.4; HashHop: Qwen3.5-35B-A3B-OptiQ-4bit 34.0, Uniform 4-bit 37.0MMLU86.785.9GSM8K89.987.5IFEval71.973.2BFCL-V393.089.5HumanEval89.088.4HashHop34.037.0

Use it

Install

pip install mlx-optiq

Serve it

An OpenAI- and Anthropic-compatible server on this Mac. Every app below can use it.

optiq serve --model npario/Ornith-1.0-35B-OptiQ-4bit

OptiQ Code

The terminal coding agent uses whatever model optiq serve is running.

optiq serve --model npario/Ornith-1.0-35B-OptiQ-4bit
optiq code

OptiQ Lab

optiq lab --model npario/Ornith-1.0-35B-OptiQ-4bit

Claude Code

optiq run claude -m npario/Ornith-1.0-35B-OptiQ-4bit

Codex

optiq run codex -m npario/Ornith-1.0-35B-OptiQ-4bit

OpenCode

optiq run opencode -m npario/Ornith-1.0-35B-OptiQ-4bit

Mistral Vibe

optiq run vibe -m npario/Ornith-1.0-35B-OptiQ-4bit

Hermes Agent

optiq run hermes -m npario/Ornith-1.0-35B-OptiQ-4bit

OpenClaw

optiq run openclaw -m npario/Ornith-1.0-35B-OptiQ-4bit

optiq run starts optiq serve if it is not running, sets the agent up for this session only, and stops the server when the agent exits.

mlx-lm, text only

from mlx_lm import load, generate

model, tokenizer = load("npario/Ornith-1.0-35B-OptiQ-4bit")
print(generate(model, tokenizer, prompt="Hello", max_tokens=256))

Details

FamilyQwen · Qwen docs
ArchitectureQwen3.5 MoE
Base modeldeepreinforce-ai/Ornith-1.0-35B
Size on disk23.1 GB
Memory neededabout 28 GB
Imagesyes, through optiq serve and the Lab
Family referenceThis model reuses the per-layer bit allocation of Qwen3.5-35B-A3B-OptiQ-4bit, whose measured Capability Score is 77.42.
Downloads24 in the last month
Updated2026-08-10
Hugging Facenpario/Ornith-1.0-35B-OptiQ-4bit