Is qwen3.8-flash-next-iq3_s-fp8-ple good for coding?

In our benchmarks, qwen3.8-flash-next-iq3_s-fp8-ple scores 69.7/100 for coding. It runs at about 99.8 tok/s, so if you want more speed, Qwen3.6-35B-A3B-Q4_K_XL is faster (~156.9 tok/s) and still scores well for coding (82.2/100).

Is qwen3.8-flash-next-iq3_s-fp8-ple good for agentic (tool-using) tasks?

In our benchmarks, qwen3.8-flash-next-iq3_s-fp8-ple scores 89.9/100 for agentic workflows. It runs at about 99.8 tok/s, so if you want more speed, swift-1.5-qwen3.8-flash-next-iq3_s is faster (~259.0 tok/s) and still scores well for agentic workflows (88.9/100).

How fast is qwen3.8-flash-next-iq3_s-fp8-ple for local inference?

Across 7 community benchmark runs, qwen3.8-flash-next-iq3_s-fp8-ple reaches up to 124.0 tok/s and averages 99.8 tok/s, with the fastest results on NVIDIA GeForce RTX 4090.

How much memory does qwen3.8-flash-next-iq3_s-fp8-ple need?

The leanest observed configuration used about 71.5 GB of memory.

Which tools have been used to run qwen3.8-flash-next-iq3_s-fp8-ple?

Benchmarks were submitted using Strata. Results are community-contributed and updated as new runs arrive.

Model benchmarks

qwen3.8-flash-next-iq3_s-fp8-ple local LLM performance

As of November 2026, qwen3.8-flash-next-iq3_s-fp8-ple runs at up to 124.0 tok/s for local inference (best of 7 community benchmark runs across 1 GPU).

Strata

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Model size

Unknown

Peak speed

124.0 tok/s

Average speed

99.8 tok/s

Avg PP

411.7 tok/s

Min memory

71.5 GB

Max context

262,144 tokens

Avg output / run

61,614 tokens

Avg runtime / run

10m 29s

Avg quality

85.2

Benchmark runs

GPUs tested

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 7 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	80.5	85.2	87.5
Agent Workflow	83.1	89.9	93.5
Code Generation	51.1	69.7	78.6
Role Play & Narrative	88.4	92.0	95.8
Research & Analysis	87.7	89.0	90.2

Performance by hardware and tool

Every hardware/tool/quantization combination qwen3.8-flash-next-iq3_s-fp8-ple 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 GeForce RTX 4090	Strata	—	124.0 tok/s	99.8 tok/s	71.5 GB	262,144 tokens	85.2	7

Benchmark runs

All 7 qwen3.8-flash-next-iq3_s-fp8-ple runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

Is qwen3.8-flash-next-iq3_s-fp8-ple good for coding?: In our benchmarks, qwen3.8-flash-next-iq3_s-fp8-ple scores 69.7/100 for coding. It runs at about 99.8 tok/s, so if you want more speed, Qwen3.6-35B-A3B-Q4_K_XL is faster (~156.9 tok/s) and still scores well for coding (82.2/100).
Is qwen3.8-flash-next-iq3_s-fp8-ple good for agentic (tool-using) tasks?: In our benchmarks, qwen3.8-flash-next-iq3_s-fp8-ple scores 89.9/100 for agentic workflows. It runs at about 99.8 tok/s, so if you want more speed, swift-1.5-qwen3.8-flash-next-iq3_s is faster (~259.0 tok/s) and still scores well for agentic workflows (88.9/100).
How fast is qwen3.8-flash-next-iq3_s-fp8-ple for local inference?: Across 7 community benchmark runs, qwen3.8-flash-next-iq3_s-fp8-ple reaches up to 124.0 tok/s and averages 99.8 tok/s, with the fastest results on NVIDIA GeForce RTX 4090.
How much memory does qwen3.8-flash-next-iq3_s-fp8-ple need?: The leanest observed configuration used about 71.5 GB of memory.
Which tools have been used to run qwen3.8-flash-next-iq3_s-fp8-ple?: Benchmarks were submitted using Strata. Results are community-contributed and updated as new runs arrive.