Model benchmarks
huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUF local LLM performance
As of October 2026, huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUF runs at up to 53.1 tok/s for local inference (best of 4 community benchmark runs across 1 GPU).
Model size
35B
Peak speed
53.1 tok/s
Average speed
51.7 tok/s
Avg PP
835.2 tok/s
Min memory
n/a
Max context
8,192 tokens
Avg output / run
8,104 tokens
Avg runtime / run
2m 56s
Avg quality
70.7
Benchmark runs
4
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 4 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 | 59.8 | 70.7 | 78.4 |
| Agent Workflow | 38.4 | 68.6 | 83.9 |
| Code Generation | 66.0 | 69.5 | 72.9 |
| Role Play & Narrative | 65.7 | 74.4 | 82.1 |
| Research & Analysis | 60.4 | 70.3 | 82.1 |
Performance by hardware and tool
Every hardware/tool/quantization combination huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUF has been benchmarked on, ranked by peak token generation speed. Last updated October 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 3070 Ti | Unsloth Studio | Q5_K | 53.1 tok/s | 51.7 tok/s | n/a | 8,192 tokens | 70.7 | 4 |
Benchmark runs
All 4 huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUF good for coding?
- In our benchmarks, huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUF scores 69.5/100 for coding. It runs at about 51.7 tok/s, so if you want more speed, local-qwen is faster (~60.2 tok/s) and still scores well for coding (84.8/100).
- Is huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUF good for agentic (tool-using) tasks?
- In our benchmarks, huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUF scores 68.6/100 for agentic workflows. It runs at about 51.7 tok/s, so if you want more speed, granite-4.2-8b-Q4_K_L is faster (~71.6 tok/s) and still scores well for agentic workflows (92.9/100).
- How fast is huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUF for local inference?
- Across 4 community benchmark runs, huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUF reaches up to 53.1 tok/s and averages 51.7 tok/s, with the fastest results on NVIDIA GeForce RTX 3070 Ti.
- Which tools have been used to run huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUF?
- Benchmarks were submitted using Unsloth Studio. Results are community-contributed and updated as new runs arrive.