RedHatAI / text-generation updated 10 months ago

Qwen3-32B-NVFP4

- Model Architecture: Qwen/Qwen3-32B - Input: Text - Output: Text - Model Optimizations: - Weight quantization: FP4 - Activation quantization: FP4 - Out-of-scope: Use in any manner that violates applicable laws or regulations (including trade compliance laws). Use in languages other than English. - Release Date: 6/25/2025 - Version: 1.0 - Model Developers: RedHatAI

Params
32.0 B
Context
40,960
Downloads 30d
219 K
Likes
9
Commercial use: allowed apache-2.0 Not gated SAFETENSORS 8 languages View on Hugging Face ↗

Download history

tracking started — chart appears after 7 days of snapshots (2 recorded)
219 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.

FileQuantSizeEst. VRAMVerdict on RTX 4090 · 24 GB
model.safetensors u8 20.7 GB 28.0 GB ❌ Won’t fit
model.safetensors (bf16, full) bf16 + 40K ctx 20.7 GB 47.2 GB ❌ Won’t fit
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/qwen3-32b-nvfp4
{
  "hf_id": "RedHatAI/Qwen3-32B-NVFP4",
  "params_b": 32.00,
  "context_length": 40960,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 218556,
  "vram_estimates": [
    { "quant": "u8", "gb": 28.0 }
  ],
  "updated_at": "2026-09-21T01:00:18Z"
}
est. VRAM —on RTX 4090 · 24 GBJSON API →

Specifications

Architecture
Qwen3ForCausalLM
Parameters
32.0 B
Tensor type
U8
Context length
40,960
Vocabulary
151,936
Layers / heads
64 / 64
Licence
apache-2.0
First seen on the Hub
2025-06-27
Base model
Qwen3-32B
Training datasets
undisclosed
Added to our catalog
2026-09-21

Family

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

Compare with any text-generation model