Model benchmarks
ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF local LLM performance
As of September 2026, ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF runs at up to 36.4 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
Unknown
Peak speed
36.4 tok/s
Average speed
31.9 tok/s
Avg PP
324.6 tok/s
Min memory
28.3 GB
Max context
262.114 tokens
Avg output / run
28.085 tokens
Avg runtime / run
28m
Avg quality
56.2
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 | 40.9 | 56.2 | 71.5 |
| Agent Workflow | 62.0 | 75.0 | 88.0 |
| Code Generation | 4.9 | 11.6 | 18.3 |
| Role Play & Narrative | 92.0 | 93.1 | 94.2 |
| Research & Analysis | 4.5 | 45.1 | 85.7 |
Performance by hardware and tool
Every hardware/tool/quantization combination ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 5090 | vLLM | — | 36.4 tok/s | 31.9 tok/s | 28.3 GB | 262.114 tokens | 56.2 | 2 |
Benchmark runs
All 2 ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF good for coding?
- In our benchmarks, ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF scores 11.6/100 for coding. It runs at about 31.9 tok/s, so if you want more speed, unsloth/Qwen3.8-27B-GGUF:IQ3_S is faster (~104.3 tok/s) and still scores well for coding (83.0/100).
- Is ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF good for agentic (tool-using) tasks?
- In our benchmarks, ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF scores 75.0/100 for agentic workflows. It runs at about 31.9 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 ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF for local inference?
- Across 2 community benchmark runs, ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF reaches up to 36.4 tok/s and averages 31.9 tok/s, with the fastest results on NVIDIA GeForce RTX 5090.
- How much memory does ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF need?
- The leanest observed configuration used about 28.3 GB of memory.
- Which tools have been used to run ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF?
- Benchmarks were submitted using vLLM. Results are community-contributed and updated as new runs arrive.