Model benchmarks
Qwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2 local LLM performance
As of November 2026, Qwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2 runs at up to 26.9 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
26.9 tok/s
Average speed
26.5 tok/s
Avg PP
460.5 tok/s
Min memory
38.2 GB
Max context
262,144 tokens
Avg output / run
64,049 tokens
Avg runtime / run
40m 43s
Avg quality
86.5
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 | 84.1 | 86.5 | 88.6 |
| Agent Workflow | 84.7 | 85.8 | 87.3 |
| Code Generation | 76.0 | 82.7 | 87.9 |
| Role Play & Narrative | 87.3 | 92.2 | 95.4 |
| Research & Analysis | 83.4 | 85.4 | 87.9 |
Performance by hardware and tool
Every hardware/tool/quantization combination Qwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2 has been benchmarked on, ranked by peak token generation speed. Last updated November 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA RTX A6000 | llama.cpp | — | 26.9 tok/s | 26.5 tok/s | 38.2 GB | 262,144 tokens | 86.5 | 3 |
Benchmark runs
All 3 Qwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2 runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Qwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2 good for coding?
- In our benchmarks, Qwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2 scores 82.7/100 for coding. It runs at about 26.5 tok/s, so if you want more speed, Qwen3.8-27B-Cold-Fusion-GAIN-V1.1-NM-DAU-NEO-MAX-MTP-GGUF-Q6_K is faster (~34.2 tok/s) and still scores well for coding (85.9/100).
- Is Qwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2 good for agentic (tool-using) tasks?
- In our benchmarks, Qwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2 scores 85.8/100 for agentic workflows. It runs at about 26.5 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-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2 for local inference?
- Across 3 community benchmark runs, Qwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2 reaches up to 26.9 tok/s and averages 26.5 tok/s, with the fastest results on NVIDIA RTX A6000.
- How much memory does Qwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2 need?
- The leanest observed configuration used about 38.2 GB of memory.
- Which tools have been used to run Qwen3.8-27B-EfficientThink-Uncensored-K3-Opus5-Grok4.6-GPT5.6Sol-SFT-SimPO-DFlash2?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.