Model benchmarks
Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF-RVN-Q6_K-multilingual-mtp local LLM performance
As of October 2026, Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF-RVN-Q6_K-multilingual-mtp runs at up to 27.4 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
27.4 tok/s
Average speed
27.3 tok/s
Avg PP
614.8 tok/s
Min memory
33.2 GB
Max context
262,144 tokens
Avg output / run
28,920 tokens
Avg runtime / run
17m 59s
Avg quality
84.5
Benchmark runs
3
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 3 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 | 81.9 | 84.5 | 86.7 |
| Agent Workflow | 77.8 | 84.1 | 90.7 |
| Code Generation | 75.9 | 79.7 | 85.5 |
| Role Play & Narrative | 84.8 | 88.5 | 91.3 |
| Research & Analysis | 82.6 | 85.7 | 88.3 |
Performance by hardware and tool
Every hardware/tool/quantization combination Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF-RVN-Q6_K-multilingual-mtp 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 RTX A6000 | llama.cpp | Q6_K | 27.4 tok/s | 27.3 tok/s | 33.2 GB | 262,144 tokens | 84.5 | 3 |
Benchmark runs
All 3 Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF-RVN-Q6_K-multilingual-mtp runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF-RVN-Q6_K-multilingual-mtp good for coding?
- In our benchmarks, Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF-RVN-Q6_K-multilingual-mtp scores 79.7/100 for coding. It runs at about 27.3 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 Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF-RVN-Q6_K-multilingual-mtp good for agentic (tool-using) tasks?
- In our benchmarks, Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF-RVN-Q6_K-multilingual-mtp scores 84.1/100 for agentic workflows. It runs at about 27.3 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 Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF-RVN-Q6_K-multilingual-mtp for local inference?
- Across 3 community benchmark runs, Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF-RVN-Q6_K-multilingual-mtp reaches up to 27.4 tok/s and averages 27.3 tok/s, with the fastest results on NVIDIA RTX A6000.
- How much memory does Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF-RVN-Q6_K-multilingual-mtp need?
- The leanest observed configuration used about 33.2 GB of memory (quantizations tested: Q6_K).
- Which tools have been used to run Qwen3.8-27B-Heretic-Abliterated-Uncensored-GGUF-RVN-Q6_K-multilingual-mtp?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.