Model benchmarks

qwen2.5-coder:7b-instruct local LLM performance

As of July 2026, qwen2.5-coder:7b-instruct runs at up to 17.2 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).

OllamaQ4_K_M
ShareRedditX

Model size

7.6B

Peak speed

17.2 tok/s

Average speed

15.2 tok/s

Min memory

4.6 GB

Max context

8,192 tokens

Avg quality

44.6

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)
Overall38.644.650.6
Agent Workflow44.757.470.2
Code Generation25.438.150.7
Role Play & Narrative49.954.959.8
Research & Analysis24.428.131.7

Performance by hardware and tool

Every hardware/tool/quantization combination qwen2.5-coder:7b-instruct has been benchmarked on, ranked by peak token generation speed. Last updated July 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
Apple M4OllamaQ4_K_M17.2 tok/s15.2 tok/s4.6 GB8,192 tokens44.62

Frequently asked questions

Is qwen2.5-coder:7b-instruct good for coding?
In our benchmarks, qwen2.5-coder:7b-instruct scores 38.1/100 for coding. It runs at about 15.2 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 qwen2.5-coder:7b-instruct good for agentic (tool-using) tasks?
In our benchmarks, qwen2.5-coder:7b-instruct scores 57.4/100 for agentic workflows. It runs at about 15.2 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 qwen2.5-coder:7b-instruct for local inference?
Across 2 community benchmark runs, qwen2.5-coder:7b-instruct reaches up to 17.2 tok/s and averages 15.2 tok/s, with the fastest results on Apple M4.
How much memory does qwen2.5-coder:7b-instruct need?
The leanest observed configuration used about 4.6 GB of memory (quantizations tested: Q4_K_M).
Which tools have been used to run qwen2.5-coder:7b-instruct?
Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.