Is qwen3:14b good for coding?

In our benchmarks, qwen3:14b scores 20.3/100 for coding. It runs at about 91.7 tok/s, so if you want more speed, Tiel-Coder-35B-A3B-MLX-oQ4e is faster (~107.9 tok/s) and still scores well for coding (81.5/100).

Is qwen3:14b good for agentic (tool-using) tasks?

In our benchmarks, qwen3:14b scores 70.4/100 for agentic workflows. It runs at about 91.7 tok/s, so if you want more speed, qwen3.8-flash-next-iq3_s is faster (~116.8 tok/s) and still scores well for agentic workflows (88.4/100).

How fast is qwen3:14b for local inference?

Across 7 community benchmark runs, qwen3:14b reaches up to 224.6 tok/s and averages 91.7 tok/s, with the fastest results on NVIDIA GeForce RTX 5060 Ti.

How much memory does qwen3:14b need?

The leanest observed configuration used about 10.0 GB of memory (quantizations tested: Q4_K_M).

Which tools have been used to run qwen3:14b?

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

Model benchmarks

qwen3:14b local LLM performance

As of October 2026, qwen3:14b runs at up to 224.6 tok/s for local inference (best of 7 community benchmark runs across 3 GPUs).

OllamaQ4_K_M

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Model size

14.8B

Peak speed

224.6 tok/s

Average speed

91.7 tok/s

Avg PP

15.6 tok/s

Min memory

10.0 GB

Max context

196,608 tokens

Avg output / run

15,954 tokens

Avg runtime / run

8m 55s

Avg quality

56.8

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 7 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	50.8	56.8	63.4
Agent Workflow	53.4	70.4	80.4
Code Generation	0.0	20.3	51.6
Role Play & Narrative	67.4	75.6	80.0
Research & Analysis	50.5	60.8	73.0

Performance by hardware and tool

Every hardware/tool/quantization combination qwen3:14b 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
NVIDIA GeForce RTX 5060 Ti	Ollama	Q4_K_M	224.6 tok/s	189.2 tok/s	n/a	16,384 tokens	53.4	3
AMD Radeon RX 7800 XT	Ollama	Q4_K_M	33.4 tok/s	33.4 tok/s	15.2 GB	196,608 tokens	64.2	1
AMD Radeon RX 7900 XTX	Ollama	Q4_K_M	16.5 tok/s	13.7 tok/s	10.0 GB	65,536 tokens	57.7	3

Benchmark runs

All 7 qwen3:14b runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

Is qwen3:14b good for coding?: In our benchmarks, qwen3:14b scores 20.3/100 for coding. It runs at about 91.7 tok/s, so if you want more speed, Tiel-Coder-35B-A3B-MLX-oQ4e is faster (~107.9 tok/s) and still scores well for coding (81.5/100).
Is qwen3:14b good for agentic (tool-using) tasks?: In our benchmarks, qwen3:14b scores 70.4/100 for agentic workflows. It runs at about 91.7 tok/s, so if you want more speed, qwen3.8-flash-next-iq3_s is faster (~116.8 tok/s) and still scores well for agentic workflows (88.4/100).
How fast is qwen3:14b for local inference?: Across 7 community benchmark runs, qwen3:14b reaches up to 224.6 tok/s and averages 91.7 tok/s, with the fastest results on NVIDIA GeForce RTX 5060 Ti.
How much memory does qwen3:14b need?: The leanest observed configuration used about 10.0 GB of memory (quantizations tested: Q4_K_M).
Which tools have been used to run qwen3:14b?: Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.