Qwen / text-generation updated 1 year ago

Qwen2.5-7B-Instruct

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

Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:

Params

7.6 B

Context

32,768

Downloads 30d

9.7 M

Likes

2,214

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

Download history

daily snapshots · 55 days

▲ 2.4 M in the last 30 days (19.7%)

12.3 M9.7 M

Jul 28Aug 15Sep 2Sep 20

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/qwen2-5-7b-instruct
{
  "hf_id": "Qwen/Qwen2.5-7B-Instruct",
  "params_b": 7.62,
  "context_length": 32768,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 9726568,
  "vram_estimates": [
    { "quant": "bf16", "gb": 18.4 }
  ],
  "updated_at": "2026-07-28T17:06:23Z"
}

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: 2024-09-16
Base model: Qwen2.5-7B
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Family

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

Base Qwen2.5-7B Qwen 684 K Derivative Qwen2.5-7B-Instruct-AWQ Qwen 3.5 M Derivative Qwen2.5-7B-Instruct unsloth 294 K Derivative Qwen2.5-7B-Instruct-GGUF bartowski 197 K Derivative Qwen2.5-7B-Instruct-GPTQ-Int4 Qwen 186 K Derivative Qwen2.5-7B-Instruct-bnb-4bit unsloth 170 K

Compare with any text-generation model

Popular comparisons

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Appears in

Commercial-use text models