Is qwen3.5:latest good for coding?

In our benchmarks, qwen3.5:latest scores 29.6/100 for coding. It runs at about 28.1 tok/s, so if you want more speed, Qwen3.8-27B-Turbo-Brilliance-50X-RI-GSQ-RCO-IQ3_XXS-mtp is faster (~37.5 tok/s) and still scores well for coding (83.8/100).

Is qwen3.5:latest good for agentic (tool-using) tasks?

In our benchmarks, qwen3.5:latest scores 58.2/100 for agentic workflows. It runs at about 28.1 tok/s, so if you want more speed, muse-glimmer:latest is faster (~33.3 tok/s) and still scores well for agentic workflows (91.6/100).

How fast is qwen3.5:latest for local inference?

Across 8 community benchmark runs, qwen3.5:latest reaches up to 69.5 tok/s and averages 28.1 tok/s.

How much memory does qwen3.5:latest need?

The leanest observed configuration used about 5.1 GB of memory (quantizations tested: Q4_K_M).

Which tools have been used to run qwen3.5:latest?

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

Model benchmarks

qwen3.5:latest local LLM performance

As of October 2026, qwen3.5:latest runs at up to 69.5 tok/s for local inference (best of 8 community benchmark runs across 2 GPUs).

OllamaQ4_K_M

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Model size

9.7B

Peak speed

69.5 tok/s

Average speed

28.1 tok/s

Avg PP

451.8 tok/s

Min memory

5.1 GB

Max context

65,536 tokens

Avg output / run

18,886 tokens

Avg runtime / run

20m 52s

Avg quality

52.8

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 8 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	30.6	52.8	63.1
Agent Workflow	13.8	58.2	86.8
Code Generation	1.9	29.6	52.1
Role Play & Narrative	58.4	70.6	78.6
Research & Analysis	16.4	52.6	68.8

Performance by hardware and tool

Every hardware/tool/quantization combination qwen3.5:latest 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
CPU only	Ollama	Q4_K_M	69.5 tok/s	69.5 tok/s	5.5 GB	8,192 tokens	39.6	1
Apple M4 Pro	Ollama	Q4_K_M	35.9 tok/s	35.9 tok/s	5.5 GB	8,192 tokens	25.8	1
NVIDIA GPU	Ollama	Q4_K_M	29.5 tok/s	29.5 tok/s	5.1 GB	8,192 tokens	58.0	2
Intel Arc B390	Ollama	Q4_K_M	15.1 tok/s	15.0 tok/s	5.4 GB	65,536 tokens	60.2	4

Benchmark runs

All 8 qwen3.5:latest runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

Is qwen3.5:latest good for coding?: In our benchmarks, qwen3.5:latest scores 29.6/100 for coding. It runs at about 28.1 tok/s, so if you want more speed, Qwen3.8-27B-Turbo-Brilliance-50X-RI-GSQ-RCO-IQ3_XXS-mtp is faster (~37.5 tok/s) and still scores well for coding (83.8/100).
Is qwen3.5:latest good for agentic (tool-using) tasks?: In our benchmarks, qwen3.5:latest scores 58.2/100 for agentic workflows. It runs at about 28.1 tok/s, so if you want more speed, muse-glimmer:latest is faster (~33.3 tok/s) and still scores well for agentic workflows (91.6/100).
How fast is qwen3.5:latest for local inference?: Across 8 community benchmark runs, qwen3.5:latest reaches up to 69.5 tok/s and averages 28.1 tok/s.
How much memory does qwen3.5:latest need?: The leanest observed configuration used about 5.1 GB of memory (quantizations tested: Q4_K_M).
Which tools have been used to run qwen3.5:latest?: Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.