Is Qwen3.8-27B-IQ3_XXS good for coding?

In our benchmarks, Qwen3.8-27B-IQ3_XXS scores 60.0/100 for coding. It runs at about 45.7 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 Qwen3.8-27B-IQ3_XXS good for agentic (tool-using) tasks?

In our benchmarks, Qwen3.8-27B-IQ3_XXS scores 86.5/100 for agentic workflows. It runs at about 45.7 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 Qwen3.8-27B-IQ3_XXS for local inference?

Across 4 community benchmark runs, Qwen3.8-27B-IQ3_XXS reaches up to 61.1 tok/s and averages 45.7 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.

Which tools have been used to run Qwen3.8-27B-IQ3_XXS?

Benchmarks were submitted using LM Studio, llama.cpp. Results are community-contributed and updated as new runs arrive.

Model benchmarks

Qwen3.8-27B-IQ3_XXS local LLM performance

As of September 2026, Qwen3.8-27B-IQ3_XXS runs at up to 61.1 tok/s for local inference (best of 4 community benchmark runs across 3 GPUs).

LM Studiollama.cpp

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Model size

27B

Peak speed

61.1 tok/s

Average speed

45.7 tok/s

Avg PP

343.6 tok/s

Min memory

n/a

Max context

98,304 tokens

Avg output / run

27,537 tokens

Avg runtime / run

16m 31s

Avg quality

80.2

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 4 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	73.4	80.2	85.2
Agent Workflow	81.6	86.5	91.7
Code Generation	28.3	60.0	80.3
Role Play & Narrative	84.4	89.3	94.6
Research & Analysis	82.8	84.9	88.2

Performance by hardware and tool

Every hardware/tool/quantization combination Qwen3.8-27B-IQ3_XXS 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
AMD Radeon RX 7900 XTX	llama.cpp	—	61.1 tok/s	59.6 tok/s	n/a	65,536 tokens	84.4	2
NVIDIA GeForce RTX 5060	llama.cpp	—	43.5 tok/s	43.5 tok/s	n/a	98,304 tokens	79.7	1
AMD Radeon RX 7600 XT	LM Studio	—	20.0 tok/s	20.0 tok/s	n/a	32,768 tokens	72.2	1

Benchmark runs

All 4 Qwen3.8-27B-IQ3_XXS runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

Is Qwen3.8-27B-IQ3_XXS good for coding?: In our benchmarks, Qwen3.8-27B-IQ3_XXS scores 60.0/100 for coding. It runs at about 45.7 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 Qwen3.8-27B-IQ3_XXS good for agentic (tool-using) tasks?: In our benchmarks, Qwen3.8-27B-IQ3_XXS scores 86.5/100 for agentic workflows. It runs at about 45.7 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 Qwen3.8-27B-IQ3_XXS for local inference?: Across 4 community benchmark runs, Qwen3.8-27B-IQ3_XXS reaches up to 61.1 tok/s and averages 45.7 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.
Which tools have been used to run Qwen3.8-27B-IQ3_XXS?: Benchmarks were submitted using LM Studio, llama.cpp. Results are community-contributed and updated as new runs arrive.