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ornith-1.0-35b-abliterated-mxfp4-vision-mtplx

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Shiftedx/ornith-1.0-35b-abliterated-mxfp4-vision-mtplx is an uncensored open-source model hosted on Hugging Face.

Image-Text-to-TextMLX LMsafetensorsLicense: other35Bmlxqwen3_5_moemtplxmxfp4apple-siliconlocal-inferenceprivacyvisionabliteratedconversational4-bit
README.md说明 / 使用方法

license: other base_model: deepreinforce-ai/Ornith-1.0-35B library_name: mlx pipeline_tag: image-text-to-text tags:

  • mlx
  • mtplx
  • mxfp4
  • qwen3_5_moe
  • apple-silicon
  • local-inference
  • privacy
  • vision
  • abliterated

Ornith 1.0 35B Abliterated MXFP4 Vision MTPLX

Vision-enabled MXFP4 MLX build of deepreinforce-ai/Ornith-1.0-35B, packaged for MTPLX native-MTP inference on Apple Silicon.

This is intended for local, private inference. The package contains model files only: no hosted endpoint, telemetry, prompt logs, or external service requirement.

Notes

  • Includes the Ornith vision tower and processor files.
  • Optimized for MTPLX MTP serving, not LM Studio indexing.
  • Uses a compatible prequantized q5/g64 MTP sidecar; recommended draft depth is 2.
  • Chat template defaults to thinking off unless enable_thinking=true is passed explicitly.
  • Abliteration metadata is included for transparency; no source direction file is required for inference.

Local Validation

Hardware reference: Apple M4 Max Apple Silicon with 64 GB unified memory.

CheckResult
API healthPass
Text JSON smokePass
Executable code smoke3/3
Vision smokePass
Mean decode speed158.0 tok/s
Accepted draft ratio92.3%

The image smoke identified HUNTER and a living room scene. These are lightweight local checks, not public leaderboard scores.

Recommended MTPLX Settings

Use depth 2, profile sustained, tokenizer chat template, MTP enabled, and thinking disabled by default.

Shiftedx Bench post-publication qualification

This table was generated from the frozen lightweight quant gate after the model weights were published. Categories remain separate; the benchmark does not produce a composite intelligence score.

LanePassedAccuracyMean wall timeMean decodePeak active memory
Quality5/1050.0%9.60 s160.47 tok/s35.28 GiB
Long context1/156.7%36.35 s131.56 tok/s37.96 GiB
Tool calling5/683.3%1.32 s131.81 tok/s36.45 GiB
Agentic1/250.0%3.30 s— tok/s—
Vision0/40.0%1.72 s165.93 tok/s35.15 GiB
  • Tested model revision: afed7f14a357c9db38bf67eb5b7c66b6152157f5
  • Benchmark: Shiftedx Bench v0.3.0
  • Context lengths represented: 4,096, 16,384, 65,536, 131,072 prompt tokens; effective tested context: not established at the benchmark's 90% threshold
  • Runtime contract: MTPLX 2.7.1 sustained; thinking on/medium; sampler temperature=0.2, top_p=0.95, top_k=20; Hermes hybrid routing with native explicit-parallel calls; KV cache off; MTP depth 2
  • Host: Apple M4 Max, 64 GiB unified memory
  • Total measured request wall time: 662.69 seconds
  • 260,096-token status: not run; it is outside the lightweight quant gate.

Scores are specific to the linked model revision, benchmark revision, runtime contract, and host. Changing weight precision, KV-cache precision, reasoning mode, template, or speculative depth creates a different benchmark candidate.

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来源与版本

作者
Shiftedx
最近更新
2026/08/20
最新创建
2026/07/05
HF 趋势
未知
数据快照
2026/09/17
版本
未知
许可证
other