Model benchmarks
Tiel-Coder-35B-A3B-MLX-oQ4e-MTP local LLM performance
As of September 2026, Tiel-Coder-35B-A3B-MLX-oQ4e-MTP runs at up to 126.6 tok/s for local inference (best of 5 community benchmark runs across 1 GPU).
Model size
35B
Peak speed
126.6 tok/s
Average speed
123.7 tok/s
Avg PP
1660.1 tok/s
Min memory
21.0 GB
Max context
262,144 tokens
Avg output / run
26,240 tokens
Avg runtime / run
3m 39s
Avg quality
82.1
Benchmark runs
5
GPUs tested
1
Quality by task
Average LLM-judged quality (0–100) with the run-to-run spread shown as a P5–P95 band, overall and for each benchmark task, across all 5 runs. The low and high columns show how much the judge’s score varies between runs, and need at least two runs to display.
| Task | P5 (low) | Avg | P95 (high) |
|---|---|---|---|
| Overall | 79.9 | 82.1 | 83.4 |
| Agent Workflow | 78.4 | 84.4 | 89.4 |
| Code Generation | 71.9 | 76.3 | 81.2 |
| Role Play & Narrative | 72.4 | 82.3 | 87.5 |
| Research & Analysis | 83.0 | 85.3 | 89.1 |
Performance by hardware and tool
Every hardware/tool/quantization combination Tiel-Coder-35B-A3B-MLX-oQ4e-MTP has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| Apple M5 Max | oMLX | — | 126.6 tok/s | 123.7 tok/s | 21.0 GB | 262,144 tokens | 82.1 | 5 |
Benchmark runs
All 5 Tiel-Coder-35B-A3B-MLX-oQ4e-MTP runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- How fast is Tiel-Coder-35B-A3B-MLX-oQ4e-MTP for local inference?
- Across 5 community benchmark runs, Tiel-Coder-35B-A3B-MLX-oQ4e-MTP reaches up to 126.6 tok/s and averages 123.7 tok/s, with the fastest results on Apple M5 Max.
- How much memory does Tiel-Coder-35B-A3B-MLX-oQ4e-MTP need?
- The leanest observed configuration used about 21.0 GB of memory.
- Which tools have been used to run Tiel-Coder-35B-A3B-MLX-oQ4e-MTP?
- Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.