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MiMo-V2.6-Distill-Qwen-9B-oQ4e
mlx-works/MiMo-V2.6-Distill-Qwen-9B-oQ4e
MiMo-V2.6-Distill-Qwen-9B-oQ4e 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) mixed-precision quantization.
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.safetensors6 GB · 100%
Parameter types
How the weights are stored.
U329B · 95%
Model card
From the Hugging Face model README
MiMo-V2.6-Distill-Qwen-9B-oQ4e
This model was quantized using oQ (oMLX) mixed-precision quantization.
Base model: XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B (SFT fine-tune of Qwen/Qwen3.5-9B)
Chat template: MiMo's own chat_template.jinja, as shipped
Quantization details
- Model type: qwen3_5
- Bits: 4
- Group size: 64
- Format: MLX safetensors
- Calibration: oQ4e (enhanced, imatrix-based; oqe_code_multilingual)
Environment
- Hardware: M5 MacBook Air 32GB
- Inference Framework: oMLX v0.7.0.dev4
- Max Concurrent Requests: 4
- Settings:
- Thinking: Disabled
- TurboQuant KV Cache: Disabled
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 | 1365.2 | 37.75 | 750.1 tok/s | 26.7 tok/s | 6.179 | 186.5 tok/s | 5.78 GB |
| pp4096/tg128 | 5270.4 | 38.67 | 777.2 tok/s | 26.1 tok/s | 10.199 | 414.2 tok/s | 6.28 GB |
Continuous Batching (pp1024 / tg128)
| Batch | tg TPS | Speedup | pp TPS | pp TPS/req | TTFT(ms) | E2E(s) |
|---|---|---|---|---|---|---|
| 1x | 26.7 tok/s | 1.00x | 750.1 tok/s | 750.1 tok/s | 1365.2 | 6.179 |
| 2x | 51.7 tok/s | 1.94x | 606.3 tok/s | 303.1 tok/s | 2680.5 | 8.333 |
| 4x | 89.0 tok/s | 3.33x | 534.8 tok/s | 133.7 tok/s | 5264.7 | 13.411 |
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 | 29.2 | No |
| TRUTHFULQA | 76.7% | 23 | 30 | 9.1 | No |
| GSM8K | 86.7% | 26 | 30 | 79.3 | No |
| MATHQA | 33.3% | 10 | 30 | 65.1 | No |
| HUMANEVAL | 80.0% | 24 | 30 | 189.8 | No |
- Library
- mlx
- Type
- qwen3_5
- Created
- Sep 22, 2026
- Updated
- Sep 23, 2026