Qwen3-4B-Instruct-2507-unsloth-bnb-4bit
Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants.
Params
4.0 B
Context
262,144
Downloads 30d
153 K
Likes
17
Download history
tracking started — chart appears after 7 days of snapshots (4 recorded)153 K downloads in the last 30 days
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 | 3.5 GB | 5.0 GB | ✅ Runs comfortably |
| model.safetensors (bf16, full) | bf16 + 256K ctx | 3.5 GB | 23.7 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 -s https://aimodelscomparison.com/api/v1/models/qwen3-4b-instruct-2507-unsloth-bnb-4bit
{
"hf_id": "unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit",
"params_b": 4.02,
"context_length": 262144,
"license": { "id": "apache-2.0", "commercial": "yes" },
"downloads_30d": 152773,
"vram_estimates": [
{ "quant": "u8", "gb": 5.0 }
],
"updated_at": "2026-10-22T01:00:14Z"
}
Specifications
- Architecture
- Qwen3ForCausalLM
- Parameters
- 4.0 B
- Tensor type
- U8
- Context length
- 262,144
- Vocabulary
- 151,936
- Layers / heads
- 36 / 32
- Licence
- apache-2.0
- First seen on the Hub
- 2025-08-06
- Base model
- Qwen3-4B-Instruct-2507
- Training datasets
- undisclosed
- Added to our catalog
- 2026-10-22
Family
Base model and the most-downloaded derivatives in the catalog.
Compare with any text-generation model