Qwen / text-generation updated 1 year ago

Qwen2.5-0.5B

Name: Qwen2.5-0.5B
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

490 M

Context

32,768

Downloads 30d

2.6 M

Likes

434

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

Download history

daily snapshots · 10 days

2.7 M2.6 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	1.0 GB	1.7 GB	✅ Runs comfortably
model.safetensors (bf16, full)	bf16 + 32K ctx	1.0 GB	1.9 GB	✅ Runs comfortably

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/qwen2-5-0-5b
{
  "hf_id": "Qwen/Qwen2.5-0.5B",
  "params_b": 0.49,
  "context_length": 32768,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 2599813,
  "vram_estimates": [
    { "quant": "bf16", "gb": 1.7 }
  ],
  "updated_at": "2026-07-28T17:07:38Z"
}

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

Specifications

Architecture: Qwen2ForCausalLM
Parameters: 490 M
Tensor type: BF16
Context length: 32,768
Vocabulary: 151,936
Layers / heads: 24 / 14
Licence: apache-2.0
First seen on the Hub: 2024-09-15
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Family

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

Derivative Qwen2.5-0.5B-Instruct Qwen 6.6 M Derivative VibeVoice-Realtime-0.5B microsoft 657 K

Compare with

Qwen3-0.6B 29.7 M Qwen2.5-1.5B-Instruct 14.0 M gpt2 13.7 M Llama-3.2-1B-Instruct 10.4 M Qwen2.5-0.5B-Instruct 6.6 M gemma-3-1b-it 4.7 M

Appears in

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