Model benchmarks
qwen3.8-flash-next-abliterated-iq3_s local LLM performance
As of October 2026, qwen3.8-flash-next-abliterated-iq3_s runs at up to 58.7 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
Unknown
Peak speed
58.7 tok/s
Average speed
57.5 tok/s
Avg PP
205.4 tok/s
Min memory
35.2 GB
Max context
65,536 tokens
Avg output / run
25,648 tokens
Avg runtime / run
7m 23s
Avg quality
81.0
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 | 77.4 | 81.0 | 85.6 |
| Agent Workflow | 73.6 | 79.9 | 89.0 |
| Code Generation | 63.4 | 67.3 | 72.6 |
| Role Play & Narrative | 89.9 | 91.0 | 92.3 |
| Research & Analysis | 81.2 | 85.9 | 88.8 |
Performance by hardware and tool
Every hardware/tool/quantization combination qwen3.8-flash-next-abliterated-iq3_s 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 |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon AI PRO R9700 | Strata | — | 58.7 tok/s | 57.5 tok/s | 35.2 GB | 65,536 tokens | 81.0 | 3 |
Benchmark runs
All 3 qwen3.8-flash-next-abliterated-iq3_s runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is qwen3.8-flash-next-abliterated-iq3_s good for coding?
- In our benchmarks, qwen3.8-flash-next-abliterated-iq3_s scores 67.3/100 for coding. It runs at about 57.5 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-abliterated-iq3_s good for agentic (tool-using) tasks?
- In our benchmarks, qwen3.8-flash-next-abliterated-iq3_s scores 79.9/100 for agentic workflows. It runs at about 57.5 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-flash-next-abliterated-iq3_s for local inference?
- Across 3 community benchmark runs, qwen3.8-flash-next-abliterated-iq3_s reaches up to 58.7 tok/s and averages 57.5 tok/s, with the fastest results on AMD Radeon AI PRO R9700.
- How much memory does qwen3.8-flash-next-abliterated-iq3_s need?
- The leanest observed configuration used about 35.2 GB of memory.
- Which tools have been used to run qwen3.8-flash-next-abliterated-iq3_s?
- Benchmarks were submitted using Strata. Results are community-contributed and updated as new runs arrive.