Best open coding models to run locally

Coding models are language models trained or fine-tuned on code. They can generate, complete, explain, and debug code across multiple programming languages. Run them locally with the same tools as other language models.

Last updated 3 November 2026 · refreshed after every Hugging Face sync · 9 models

#ModelSizeMemoryLicenseDownloads (30 days)Likes
1Qwen3-Coder-30B-A3B-Instruct
Qwen
30B · FP16~72 GBApache 2.01.1M1.3K
2Qwen2.5-Coder-7B-Instruct
Qwen
7B · FP16~17 GBApache 2.01.4M859
3Qwen3-Coder-30B-A3B-Instruct-GGUF
unsloth
30B · GGUF~18 GBApache 2.01.1M1.2K
4Qwen2.5-Coder-14B-Instruct
Qwen
14B · FP16~34 GBApache 2.02M211
5Qwen3-Coder-30B-A3B-Instruct-FP8
Qwen
30B · FP16~72 GBApache 2.01.1M240
6Qwen3-Coder-Next-FP8
Qwen
– · FP16–Apache 2.0812.8K212
7Qwen2.5-Coder-32B-Instruct-AWQ
Qwen
32B · AWQ~20 GBApache 2.01M50
8Qwen3-Coder-30B-A3B-Instruct-AWQ-4bit
cyankiwi
30B · AWQ~18 GBApache 2.0777.2K67
9gemma-4-12B-coder-fable5-composer2.5-v1-GGUF
yuxinlu1
12B · GGUF~8 GBApache 2.0110.7K3K

How we rank

Text-generation models whose name or metadata signals coding capability. We include models seen on Hugging Face in the last 14 days with at least 10,000 downloads in the last 30 days. Score = log10(30-day downloads) + ½ × log10(likes + 1), so popularity leads and likes break near-ties. We keep one entry per model name and leave out adult and uncensored builds. Memory is estimated from parameter count and the published file format (16-bit ≈ 2 bytes per parameter, 4-bit ≈ 0.5) plus 20% headroom; long contexts need more. A quantised copy of a bigger model may also fit — check the model page.

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