Qwen / text-generation updated 1 year ago

Qwen2.5-Math-1.5B-Instruct

Name: Qwen2.5-Math-1.5B-Instruct
Author: Qwen

> [!Warning] > > > 🚨 Qwen2.5-Math mainly supports solving English and Chinese math problems through CoT and TIR. We do not recommend using this series of models for other tasks. > >

Params

1.5 B

Context

4,096

Downloads 30d

167 K

Likes

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

Download history

daily snapshots · 10 days

171 K160 K

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	3.1 GB	4.1 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-math-1-5b-instruct
{
  "hf_id": "Qwen/Qwen2.5-Math-1.5B-Instruct",
  "params_b": 1.54,
  "context_length": 4096,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 166691,
  "vram_estimates": [
    { "quant": "bf16", "gb": 4.1 }
  ],
  "updated_at": "2026-07-28T18:09:01Z"
}

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

Specifications

Architecture: Qwen2ForCausalLM
Parameters: 1.5 B
Tensor type: BF16
Context length: 4,096
Vocabulary: 151,936
Layers / heads: 28 / 12
Licence: apache-2.0
First seen on the Hub: 2024-09-16
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Compare with

Qwen3-0.6B 29.7 M Qwen2.5-1.5B-Instruct 14.0 M Llama-3.2-1B-Instruct 10.4 M Qwen3-1.7B 7.8 M gemma-3-1b-it 4.7 M Qwen2-1.5B-Instruct 3.2 M

Appears in

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