Is Qwen3.6-35B-A3B-Q4_K_XL good for agentic (tool-using) tasks?

In our benchmarks, Qwen3.6-35B-A3B-Q4_K_XL scores 84.4/100 for agentic workflows. It runs at about 156.9 tok/s, so if you want more speed, mudler/Ornith-1.5-35B-A3B-APEX-MTP-GGUF is faster (~190.9 tok/s) and still scores well for agentic workflows (85.7/100).

How fast is Qwen3.6-35B-A3B-Q4_K_XL for local inference?

Across 2 community benchmark runs, Qwen3.6-35B-A3B-Q4_K_XL reaches up to 159.0 tok/s and averages 156.9 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.

Which tools have been used to run Qwen3.6-35B-A3B-Q4_K_XL?

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

Model benchmarks

Qwen3.6-35B-A3B-Q4_K_XL local LLM performance

As of August 2026, Qwen3.6-35B-A3B-Q4_K_XL runs at up to 159.0 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).

llama.cppQ4_K

ShareReddit X

Model size

35B

Peak speed

159.0 tok/s

Average speed

156.9 tok/s

Min memory

n/a

Max context

65,536 tokens

Avg output / run

17,702 tokens

Avg runtime / run

1m 55s

Avg quality

84.0

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 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	83.9	84.0	84.1
Agent Workflow	76.9	84.4	91.9
Code Generation	80.2	82.2	84.2
Role Play & Narrative	84.8	86.6	88.4
Research & Analysis	79.6	82.8	86.0

Performance by hardware and tool

Every hardware/tool/quantization combination Qwen3.6-35B-A3B-Q4_K_XL has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.

Hardware	Tool	Quant	Best tok/s	Avg tok/s	Memory	Context	Quality	Runs
AMD Radeon RX 7900 XTX	llama.cpp	Q4_K	159.0 tok/s	156.9 tok/s	n/a	65,536 tokens	84.0	2

Benchmark runs

All 2 Qwen3.6-35B-A3B-Q4_K_XL runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

Is Qwen3.6-35B-A3B-Q4_K_XL good for agentic (tool-using) tasks?: In our benchmarks, Qwen3.6-35B-A3B-Q4_K_XL scores 84.4/100 for agentic workflows. It runs at about 156.9 tok/s, so if you want more speed, mudler/Ornith-1.5-35B-A3B-APEX-MTP-GGUF is faster (~190.9 tok/s) and still scores well for agentic workflows (85.7/100).
How fast is Qwen3.6-35B-A3B-Q4_K_XL for local inference?: Across 2 community benchmark runs, Qwen3.6-35B-A3B-Q4_K_XL reaches up to 159.0 tok/s and averages 156.9 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.
Which tools have been used to run Qwen3.6-35B-A3B-Q4_K_XL?: Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.