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Ornith-1.0-35B-oQ2
mlx-works/Ornith-1.0-35B-oQ2
Ornith-1.0-35B-oQ2 is a machine learning model from mlx-works. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for mlx.
This model was quantized using oQ (oMLX v0.5.3) mixed-precision quantization.
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34.7B
12.3 GB on disk
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Repo makeup
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.safetensors12.3 GB · 100%
Parameter types
How the weights are stored.
U3234.6B · 100%
Model card
From the Hugging Face model README
Ornith-1.0-35B-oQ2
This model was quantized using oQ (oMLX v0.5.3) mixed-precision quantization.
Base model: Ornith-1.0-35B
Quantization details
- Model type: qwen3_5_moe
- Bits: 2
- Group size: 64
- Format: MLX safetensors
Environment
- Hardware: M5 MacBook Air 32GB
- Inference Framework: oMLX v0.5.3
- Max Concurrent Requests: 4
- Settings:
- Thinking: Disabled
- TurboQuant KV Cache: Enabled
Performance Benchmarks
Note: Results are for reference only and may vary depending on hardware, software configuration, and workload.
Single Request Results
| Test | TTFT(ms) | TPOT(ms) | pp TPS | tg TPS | E2E(s) | Throughput | Peak Mem |
|---|---|---|---|---|---|---|---|
| pp1024/tg128 | 1063.3 | 20.83 | 963.0 tok/s | 48.4 tok/s | 3.722 | 309.5 tok/s | 12.62 GB |
| pp4096/tg128 | 3662.7 | 21.71 | 1118.3 tok/s | 46.4 tok/s | 6.435 | 656.4 tok/s | 13.36 GB |
Continuous Batching (pp1024 / tg128)
| Batch | tg TPS | Speedup | pp TPS | pp TPS/req | TTFT(ms) | E2E(s) |
|---|---|---|---|---|---|---|
| 1x | 48.4 tok/s | 1.00x | 963.0 tok/s | 963.0 tok/s | 1063.3 | 3.722 |
| 2x | 67.2 tok/s | 1.39x | 871.7 tok/s | 435.9 tok/s | 2349.2 | 6.159 |
| 4x | 100.6 tok/s | 2.08x | 868.4 tok/s | 217.1 tok/s | 4569.1 | 9.804 |
Intelligence Benchmark
Note: Each benchmark round tests only 30 questions. Results are for reference only.
| Benchmark | Accuracy | Correct | Total | Time(s) | Think |
|---|---|---|---|---|---|
| MMLU | 70.0% | 21 | 30 | 33 | No |
| TRUTHFULQA | 76.7% | 23 | 30 | 15.3 | No |
| GSM8K | 96.7% | 29 | 30 | 100.3 | No |
| MATHQA | 16.7% | 5 | 30 | 69.6 | No |
| HUMANEVAL | 83.3% | 25 | 30 | 172.8 | No |
- Library
- mlx
- Type
- qwen3_5_moe
- Created
- Jul 20, 2026
- Updated
- Jul 26, 2026