Qwen / text-generation updated 1 year ago

Qwen2.5-Coder-7B-Instruct

Name: Qwen2.5-Coder-7B-Instruct
Author: Qwen

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). As of now, Qwen2.5-Coder has covered six mainstream model sizes, 0.5, 1.5, 3, 7, 14, 32 billion parameters, to meet the needs of different developers. Qwen2.5-Coder brings the following improvements upon CodeQwen1.5:

Params

7.6 B

Context

32,768

Downloads 30d

2.0 M

Likes

765

Commercial use: allowed apache-2.0 Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

2.0 M1.9 M

Jul 28Jul 31Aug 3Aug 6

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	bf16	15.2 GB	18.4 GB	✅ Runs comfortably
model.safetensors (bf16, full)	bf16 + 32K ctx	15.2 GB	21.8 GB	⚠️ Tight — reduce context

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub

~ · curl · api/v1

$ curl -s https://aimodelscomparison.com/api/v1/models/qwen2-5-coder-7b-instruct
{
  "hf_id": "Qwen/Qwen2.5-Coder-7B-Instruct",
  "params_b": 7.62,
  "context_length": 32768,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 2019400,
  "vram_estimates": [
    { "quant": "bf16", "gb": 18.4 }
  ],
  "updated_at": "2026-07-28T18:02:43Z"
}

est. VRAM —on RTX 4090 · 24 GBJSON API →

Specifications

Architecture: Qwen2ForCausalLM
Parameters: 7.6 B
Tensor type: BF16
Context length: 32,768
Vocabulary: 152,064
Layers / heads: 28 / 28
Licence: apache-2.0
First seen on the Hub: 2024-09-17
Base model: Qwen2.5-Coder-7B
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Family

Base model and the most-downloaded derivatives in the catalog.

Base Qwen2.5-Coder-7B Qwen 1.0 M Derivative Qwen2.5-Coder-7B-Instruct-AWQ Orion-zhen 604 K Derivative Qwen2.5-Coder-7B-Instruct-GPTQ-Int4 Qwen 536 K Derivative Qwen2.5-Coder-7B-Instruct-AWQ Qwen 522 K Derivative Qwen2.5-Coder-7B-Instruct-GGUF Qwen 204 K

Compare with

Qwen3-8B 16.3 M Qwen2.5-7B-Instruct 12.1 M Qwen3.6-35B-A3B-NVFP4 11.3 M Llama-3.1-8B-Instruct 8.0 M Qwen2.5-7B-Instruct-AWQ 4.6 M granite-4.1-8b 4.2 M

Appears in

Best open coding models Commercial-use text models Models that fit in 12 GB