Model benchmarks

Qwen3.6-35B-A3B-IQ4_NL local LLM performance

As of August 2026, Qwen3.6-35B-A3B-IQ4_NL runs at up to 169.5 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).

llama.cpp
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Model size

35B

Peak speed

169.5 tok/s

Average speed

167.2 tok/s

Min memory

17.1 GB

Max context

65,536 tokens

Avg output / run

15,223 tokens

Avg runtime / run

1m 32s

Avg quality

73.5

Benchmark runs

2

GPUs tested

1

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.

TaskP5 (low)AvgP95 (high)
Overall73.473.573.6
Agent Workflow70.575.480.4
Code Generation54.158.362.5
Role Play & Narrative79.980.981.8
Research & Analysis79.179.479.6

Performance by hardware and tool

Every hardware/tool/quantization combination Qwen3.6-35B-A3B-IQ4_NL has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
AMD Radeon RX 7900 XT/7900 XTX/7900 GRE/7900Mllama.cpp169.5 tok/s167.2 tok/s17.1 GB65,536 tokens73.52

Frequently asked questions

Is Qwen3.6-35B-A3B-IQ4_NL good for coding?
In our benchmarks, Qwen3.6-35B-A3B-IQ4_NL scores 58.3/100 for coding. It runs at about 167.2 tok/s, so if you want more speed, Gemma4:E2B/QAT-MTP@131K is faster (~303.9 tok/s) and still scores well for coding (66.9/100).
Is Qwen3.6-35B-A3B-IQ4_NL good for agentic (tool-using) tasks?
In our benchmarks, Qwen3.6-35B-A3B-IQ4_NL scores 75.4/100 for agentic workflows. It runs at about 167.2 tok/s, so if you want more speed, Gemma4:E2B/QAT-MTP@131K is faster (~303.9 tok/s) and still scores well for agentic workflows (71.7/100).
How fast is Qwen3.6-35B-A3B-IQ4_NL for local inference?
Across 2 community benchmark runs, Qwen3.6-35B-A3B-IQ4_NL reaches up to 169.5 tok/s and averages 167.2 tok/s, with the fastest results on AMD Radeon RX 7900 XT/7900 XTX/7900 GRE/7900M.
How much memory does Qwen3.6-35B-A3B-IQ4_NL need?
The leanest observed configuration used about 17.1 GB of memory.
Which tools have been used to run Qwen3.6-35B-A3B-IQ4_NL?
Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.