metadata
library_name: mlx
tags:
- mlx
- oq
- quantized
- benchmark
- performance
- mtp
- moe
- code
- agentic-coding
KAT-Coder-V2.5-Dev-oQ2e-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: 2
- Group size: 64
- Format: MLX safetensors
- MTP: Grafted from Qwen3.6-35B-A3B (bf16 original)
- Calibration: oQ2e (enhanced, imatrix-based)
Environment
- Hardware: M5 MacBook Air 32GB
- Inference Framework: oMLX v0.5.4
- Max Concurrent Requests: 4
- Settings:
- Thinking: Disabled
- 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 | 1119.8 | 17.25 | 914.4 tok/s | 58.4 tok/s | 3.330 | 346.0 tok/s | 14.20 GB |
| pp4096/tg128 | 4040.2 | 21.25 | 1013.8 tok/s | 47.4 tok/s | 6.754 | 625.4 tok/s | 14.94 GB |
Continuous Batching (pp1024 / tg128)
| Batch | tg TPS | Speedup | pp TPS | pp TPS/req | TTFT(ms) | E2E(s) |
|---|---|---|---|---|---|---|
| 1x | 58.4 tok/s | 1.00x | 914.4 tok/s | 914.4 tok/s | 1119.8 | 3.330 |
| 2x | 79.3 tok/s | 1.36x | 825.0 tok/s | 412.5 tok/s | 2482.5 | 5.711 |
| 4x | 112.2 tok/s | 1.92x | 827.0 tok/s | 206.8 tok/s | 4815.5 | 9.517 |
Intelligence Benchmark
Note: Each benchmark round tests only 30 questions. Results are for reference only.
| Benchmark | Accuracy | Correct | Total | Time(s) | Think |
|---|---|---|---|---|---|
| MMLU | 73.3% | 22 | 30 | 36.3 | No |
| TRUTHFULQA | 86.7% | 26 | 30 | 15.5 | No |
| GSM8K | 96.7% | 29 | 30 | 76.7 | No |
| MATHQA | 13.3% | 4 | 30 | 76.2 | No |
| HUMANEVAL | 90.0% | 27 | 30 | 118.5 | No |