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Qwythos-9B-v2-oQ4-mtp
mlx-works/Qwythos-9B-v2-oQ4-mtp
Qwythos-9B-v2-oQ4-mtp 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 v0.5.1) mixed-precision quantization.
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.safetensors5.5 GB · 100%
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U329.2B · 100%
Model card
From the Hugging Face model README
Qwythos-9B-v2-oQ4-mtp
This model was quantized using oQ (oMLX v0.5.1) mixed-precision quantization.
Quantization details
- Model type: qwen3_5
- Bits: 4
- Group size: 64
- Format: MLX safetensors
Environment
- Hardware: M5 MacBook Air 32GB
- Inference Framework: oMLX v0.5.1
- Settings:
- Thinking: Disabled
- Chat template parameter: enable_thinking=false (forced)
- TurboQuant KV Cache: Disabled (if enable: reduces speed)
- Native MTP: Enabled (key speed improvement)
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 | 1496.9 | 21.44 | 684.1 tok/s | 47.0 tok/s | 4.242 | 271.5 tok/s | 6.11 GB |
| pp4096/tg128 | 5907.3 | 22.32 | 693.4 tok/s | 45.2 tok/s | 8.768 | 481.7 tok/s | 6.73 GB |
Continuous Batching (pp1024 / tg128)
| Batch | tg TPS | Speedup | pp TPS | pp TPS/req | TTFT(ms) | E2E(s) |
|---|---|---|---|---|---|---|
| 1x | 47.0 tok/s | 1.00x | 684.1 tok/s | 684.1 tok/s | 1496.9 | 4.242 |
| 2x | 48.4 tok/s | 1.03x | 635.0 tok/s | 317.5 tok/s | 3225.2 | 8.519 |
| 4x | 76.4 tok/s | 1.63x | 604.0 tok/s | 151.0 tok/s | 6616.7 | 13.485 |
Intelligence Benchmark
Note: Each benchmark round tests only 30 questions. Results are for reference only.
| Benchmark | Accuracy | Correct | Total | Time(s) | Think |
|---|---|---|---|---|---|
| MMLU | 66.7% | 20 | 30 | 36.4 | No |
| TRUTHFULQA | 83.3% | 25 | 30 | 13.8 | No |
| GSM8K | 83.3% | 25 | 30 | 147.8 | No |
| MATHQA | 40.0% | 12 | 30 | 30.3 | No |
| HUMANEVAL | 80.0% | 24 | 30 | 163.5 | No |
Summary
| Benchmark | Accuracy |
|---|---|
| MMLU | 66.7% |
| TRUTHFULQA | 83.3% |
| GSM8K | 83.3% |
| MATHQA | 40.0% |
| HUMANEVAL | 80.0% |
| Average | 70.7% |
- Library
- mlx
- Type
- qwen3_5
- Created
- Jul 13, 2026
- Updated
- Jul 15, 2026