Is qwen/qwen3.6-35b-a3b good for coding?

In our benchmarks, qwen/qwen3.6-35b-a3b scores 63.4/100 for coding. It runs at about 62.7 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 qwen/qwen3.6-35b-a3b good for agentic (tool-using) tasks?

In our benchmarks, qwen/qwen3.6-35b-a3b scores 71.1/100 for agentic workflows. It runs at about 62.7 tok/s, so if you want more speed, Nex-N2.5-mini-APEX-Mini is faster (~88.2 tok/s) and still scores well for agentic workflows (91.3/100).

How fast is qwen/qwen3.6-35b-a3b for local inference?

Across 15 community benchmark runs, qwen/qwen3.6-35b-a3b reaches up to 437.3 tok/s and averages 62.7 tok/s, with the fastest results on NVIDIA GeForce RTX 5090.

Which tools have been used to run qwen/qwen3.6-35b-a3b?

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

Model benchmarks

qwen/qwen3.6-35b-a3b local LLM performance

As of September 2026, qwen/qwen3.6-35b-a3b runs at up to 437.3 tok/s for local inference (best of 15 community benchmark runs across 6 GPUs).

LM Studiollama.cppvLLM

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Model size

35B

Peak speed

437.3 tok/s

Average speed

62.7 tok/s

Avg PP

222.2 tok/s

Min memory

n/a

Max context

131,072 tokens

Avg output / run

20,133 tokens

Avg runtime / run

7m 26s

Avg quality

73.4

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 15 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	58.7	73.4	83.2
Agent Workflow	43.3	71.1	85.7
Code Generation	30.2	63.4	80.6
Role Play & Narrative	72.3	83.7	92.1
Research & Analysis	55.1	75.5	88.5

Performance by hardware and tool

Every hardware/tool/quantization combination qwen/qwen3.6-35b-a3b 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	—	437.3 tok/s	437.3 tok/s	n/a	65,536 tokens	84.7	1
NVIDIA GeForce RTX 5070 Ti	LM Studio	—	75.9 tok/s	75.9 tok/s	n/a	121,072 tokens	70.8	1
Apple M4 Max	LM Studio	—	69.8 tok/s	69.8 tok/s	n/a	120,000 tokens	72.9	1
AMD Radeon RX 7900 XTX	LM Studio	—	46.1 tok/s	31.1 tok/s	n/a	65,536 tokens	68.1	6
NVIDIA GeForce RTX 4070 SUPER	llama.cpp	—	43.9 tok/s	37.2 tok/s	n/a	8,192 tokens	72.0	2
CPU only	vLLM	—	26.0 tok/s	26.0 tok/s	n/a	98,304 tokens	80.6	1
CPU only	LM Studio	—	25.0 tok/s	24.9 tok/s	n/a	131,072 tokens	78.7	2
AMD Radeon RX 7600 XT	LM Studio	—	20.8 tok/s	20.8 tok/s	n/a	32,768 tokens	82.2	1

Benchmark runs

All 15 qwen/qwen3.6-35b-a3b runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

Is qwen/qwen3.6-35b-a3b good for coding?: In our benchmarks, qwen/qwen3.6-35b-a3b scores 63.4/100 for coding. It runs at about 62.7 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 qwen/qwen3.6-35b-a3b good for agentic (tool-using) tasks?: In our benchmarks, qwen/qwen3.6-35b-a3b scores 71.1/100 for agentic workflows. It runs at about 62.7 tok/s, so if you want more speed, Nex-N2.5-mini-APEX-Mini is faster (~88.2 tok/s) and still scores well for agentic workflows (91.3/100).
How fast is qwen/qwen3.6-35b-a3b for local inference?: Across 15 community benchmark runs, qwen/qwen3.6-35b-a3b reaches up to 437.3 tok/s and averages 62.7 tok/s, with the fastest results on NVIDIA GeForce RTX 5090.
Which tools have been used to run qwen/qwen3.6-35b-a3b?: Benchmarks were submitted using LM Studio, llama.cpp, vLLM. Results are community-contributed and updated as new runs arrive.