unsloth / text-generation Open weights updated 1 year ago

Qwen3-4B-unsloth-bnb-4bit

Name: Qwen3-4B-unsloth-bnb-4bit
Author: unsloth

See our collection for all versions of Qwen3 including GGUF, 4-bit & 16-bit formats. Learn to run Qwen3 correctly - Read our Guide. Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants. ✨ Run & Fine-tune Qwen3 with Unsloth!

Params

4.1 B

Context

40,960

Downloads 30d

188 K

Likes

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

Download history

daily snapshots · 102 days

▲ 0 in the last 30 days (0.0%)

191 K176 K

Aug 1Sep 4Oct 8Nov 10

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	u8	3.6 GB	5.0 GB	✅ Runs comfortably
model.safetensors (bf16, full)	bf16 + 40K ctx	3.6 GB	7.5 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/qwen3-4b-unsloth-bnb-4bit
{
  "hf_id": "unsloth/Qwen3-4B-unsloth-bnb-4bit",
  "params_b": 4.12,
  "context_length": 40960,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 187861,
  "vram_estimates": [
    { "quant": "u8", "gb": 5.0 }
  ],
  "updated_at": "2026-08-01T01:00:28Z"
}

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

Specifications

Architecture: Qwen3ForCausalLM
Parameters: 4.1 B
Tensor type: U8
Context length: 40,960
Vocabulary: 151,936
Layers / heads: 36 / 32
Licence: apache-2.0
First seen on the Hub: 2025-04-28
Base model: Qwen3-4B
Training datasets: undisclosed
Added to our catalog: 2026-08-01

Family

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

Base Qwen3-4B Qwen 4.0 M

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