metadata
library_name: mlx
tags:
- mlx
- oq
- quantized
- benchmark
- performance
- mtp
- moe
- code
- agentic-coding
KAT-Coder-V2.5-Dev-oQ4e-mtp
This model was quantized using oQ (oMLX v0.5.4) mixed-precision quantization.
- Base model: Kwaipilot/KAT-Coder-V2.5-Dev
- MTP head: Qwen/Qwen3.6-35B-A3B (original MTP head grafted)
- Chat template: Qwen Fixed Chat Template (v21) — fixes KV cache optimization, thinking mode control, tool calling, and agent loop issues. Original backed up as
chat_template.jinja.bak.
Quantization details
- Model type: qwen3_5_moe
- Bits: 4
- Group size: 64
- Format: MLX safetensors
- MTP: Grafted from Qwen3.6-35B-A3B (bf16 original)
- Calibration: oQ4e (enhanced, imatrix-based)
Environment
- Hardware: M5 MacBook Air 32GB
- Inference Framework: oMLX v0.5.4
- Max Concurrent Requests: 4
- Settings:
- Thinking: Disabled
- TurboQuant KV Cache: Enabled (4-bit)
- Lightning 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 | 1180.7 | 19.88 | 867.3 tok/s | 50.7 tok/s | 3.723 | 309.4 tok/s | 21.72 GB |
| pp4096/tg128 | 4048.1 | 22.43 | 1011.8 tok/s | 44.9 tok/s | 6.926 | 609.8 tok/s | 22.47 GB |
Continuous Batching (pp1024 / tg128)
| Batch | tg TPS | Speedup | pp TPS | pp TPS/req | TTFT(ms) | E2E(s) |
|---|---|---|---|---|---|---|
| 1x | 50.7 tok/s | 1.00x | 867.3 tok/s | 867.3 tok/s | 1180.7 | 3.723 |
| 2x | 61.1 tok/s | 1.21x | 802.5 tok/s | 401.3 tok/s | 2552.0 | 6.743 |
| 4x | 86.4 tok/s | 1.70x | 790.3 tok/s | 197.6 tok/s | 5033.6 | 11.108 |
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 | 53.4 | No |
| TRUTHFULQA | 96.7% | 29 | 30 | 17.1 | No |
| GSM8K | 93.3% | 28 | 30 | 83 | No |
| MATHQA | 43.3% | 13 | 30 | 49.5 | No |
| HUMANEVAL | 90.0% | 27 | 30 | 125.9 | No |