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AtomicChat/
Ornith-35B-MLX-6bit

Name: Ornith-35B-MLX-6bit
Availability: InStock

deepreinforce-ai/Ornith-1.0-35B

quantized

mit

6-bit

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Base model: deepreinforce-ai/Ornith-1.0-35B

Ornith 1.0 35B, self-quantized to MLX by Atomic Chat. Built straight from DeepReinforce's original weights with a per-tensor importance matrix, so this is not a repack of somebody else's files. Runs fully offline.

Highlights

0.0B parameters: the weights this repo quantizes.
Context length: 262,144 tokens (256K), as published by DeepReinforce.
40 layers: Mixture-of-Experts.
Modalities: Text, Image.
Full imatrix ladder: every quant is calibrated with an importance matrix.
State-of-the-Art Coding Agents: Available in 9B-Dense, 31B-Dense, 35B-MoE, and 397B-MoE (post-trained on top of Gemma 4 and Qwen 3.5), achieving state-of-the-art performance among open-source models of comparable size on coding benchmarks such as Terminal-Bench 2.1, SWE-Bench, NL2Repo and OpenClaw.
Self-Improving Training Framework: Ornith-1.0 employs RL to learn to generate not only solution rollouts, but also the scallfold that drive those rollouts. By jointly optimizing the scaffold and the resulting solution, the model discovers better search trajectories and generates higher-quality solutions.

[!NOTE] These MLXs are self-quantized from the original weights, not a repack. The importance matrix keeps low-bit quants closer to the full-precision model.

Model Overview

Property	Value
Base model	`deepreinforce-ai/Ornith-1.0-35B`
Parameters	0.0B
Layers	40
Experts	256 routed (top-8)
Context length	262,144 tokens (256K)
Vocabulary	248,320
Modalities	Text, Image
Architecture	Mixture-of-Experts, 256 experts (top-8), 16 attention heads over 2 KV heads, `Qwen3_5MoeForConditionalGeneration`
This repo	MLX weights

Get started

Atomic Chat: search AtomicChat/ornith-35b-MLX-6bit and hit Use this model.
mlx-lm: mlx_lm.generate --model AtomicChat/ornith-35b-MLX-6bit --prompt "Hello" --max-tokens 512
Server: mlx_lm.server --model AtomicChat/ornith-35b-MLX-6bit --port 8080

Best practices

Parameter	Value
temperature	1.0
top_p	1.0
top_k	20

DeepReinforce's recommended sampling configuration for deepreinforce-ai/Ornith-1.0-35B.

How these were made

Download deepreinforce-ai/Ornith-1.0-35B (original weights).
Convert and quantize with mlx_lm.convert on our pipeline.

License

Original model by DeepReinforce, released under the MIT license. Full terms: MIT. Quantized by Atomic Chat.

AtomicChat/Ornith-35B-MLX-6bit