Model benchmarks
bartowski/Qwen_Qwen3-Coder-Next-GGUF:Q6_K_L local LLM performance
As of August 2026, bartowski/Qwen_Qwen3-Coder-Next-GGUF:Q6_K_L runs at up to 40.2 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
7B
Peak speed
40.2 tok/s
Average speed
38.3 tok/s
Min memory
n/a
Max context
65,536 tokens
Avg runtime / run
3m 31s
Avg quality
79.8
Benchmark runs
2
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 2 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 | 78.9 | 79.8 | 80.7 |
| Agent Workflow | 85.3 | 86.1 | 86.9 |
| Code Generation | 71.8 | 74.0 | 76.2 |
| Role Play & Narrative | 88.9 | 89.2 | 89.5 |
| Research & Analysis | 67.5 | 70.0 | 72.5 |
Performance by hardware and tool
Every hardware/tool/quantization combination bartowski/Qwen_Qwen3-Coder-Next-GGUF:Q6_K_L has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 5080 | llama.cpp | Q6_K | 40.2 tok/s | 38.3 tok/s | n/a | 65,536 tokens | 79.8 | 2 |
Benchmark runs
All 2 bartowski/Qwen_Qwen3-Coder-Next-GGUF:Q6_K_L runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is bartowski/Qwen_Qwen3-Coder-Next-GGUF:Q6_K_L good for coding?
- In our benchmarks, bartowski/Qwen_Qwen3-Coder-Next-GGUF:Q6_K_L scores 74.0/100 for coding. It runs at about 38.3 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 bartowski/Qwen_Qwen3-Coder-Next-GGUF:Q6_K_L good for agentic (tool-using) tasks?
- In our benchmarks, bartowski/Qwen_Qwen3-Coder-Next-GGUF:Q6_K_L scores 86.1/100 for agentic workflows. It runs at about 38.3 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 bartowski/Qwen_Qwen3-Coder-Next-GGUF:Q6_K_L for local inference?
- Across 2 community benchmark runs, bartowski/Qwen_Qwen3-Coder-Next-GGUF:Q6_K_L reaches up to 40.2 tok/s and averages 38.3 tok/s, with the fastest results on NVIDIA GeForce RTX 5080.
- Which tools have been used to run bartowski/Qwen_Qwen3-Coder-Next-GGUF:Q6_K_L?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.