Model benchmarks
Qwen3.8-Flash-Next-Sushi-2.6bpw local LLM performance
As of October 2026, Qwen3.8-Flash-Next-Sushi-2.6bpw runs at up to 78.0 tok/s for local inference (best of 5 community benchmark runs across 1 GPU).
Model size
6B
Peak speed
78.0 tok/s
Average speed
74.3 tok/s
Avg PP
575.3 tok/s
Min memory
46.2 GB
Max context
65,536 tokens
Avg output / run
12,654 tokens
Avg runtime / run
2m 55s
Avg quality
83.6
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 | 80.4 | 83.6 | 86.4 |
| Agent Workflow | 76.7 | 84.5 | 90.6 |
| Code Generation | 75.8 | 78.7 | 83.6 |
| Role Play & Narrative | 83.8 | 88.5 | 92.6 |
| Research & Analysis | 78.5 | 82.6 | 87.4 |
Performance by hardware and tool
Every hardware/tool/quantization combination Qwen3.8-Flash-Next-Sushi-2.6bpw 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 |
|---|---|---|---|---|---|---|---|---|
| Apple M5 Max | sushi | — | 78.0 tok/s | 76.1 tok/s | 46.2 GB | 65,536 tokens | 82.8 | 2 |
| Apple M5 Max | mlx-serve | — | 74.4 tok/s | 73.2 tok/s | 46.9 GB | 65,536 tokens | 84.1 | 3 |
Benchmark runs
All 5 Qwen3.8-Flash-Next-Sushi-2.6bpw runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Qwen3.8-Flash-Next-Sushi-2.6bpw good for coding?
- In our benchmarks, Qwen3.8-Flash-Next-Sushi-2.6bpw scores 78.7/100 for coding. It runs at about 74.3 tok/s, so if you want more speed, ornith-ai/Ornith-1.5-35B-A3B-GGUF is faster (~90.8 tok/s) and still scores well for coding (83.8/100).
- Is Qwen3.8-Flash-Next-Sushi-2.6bpw good for agentic (tool-using) tasks?
- In our benchmarks, Qwen3.8-Flash-Next-Sushi-2.6bpw scores 84.5/100 for agentic workflows. It runs at about 74.3 tok/s, so if you want more speed, Nex-N2.5-mini-APEX-Mini is faster (~88.2 tok/s) and still scores well for agentic workflows (91.3/100).
- How fast is Qwen3.8-Flash-Next-Sushi-2.6bpw for local inference?
- Across 5 community benchmark runs, Qwen3.8-Flash-Next-Sushi-2.6bpw reaches up to 78.0 tok/s and averages 74.3 tok/s, with the fastest results on Apple M5 Max.
- How much memory does Qwen3.8-Flash-Next-Sushi-2.6bpw need?
- The leanest observed configuration used about 46.2 GB of memory.
- Which tools have been used to run Qwen3.8-Flash-Next-Sushi-2.6bpw?
- Benchmarks were submitted using mlx-serve, sushi. Results are community-contributed and updated as new runs arrive.