Qwen3-8B-FP8
The NVIDIA Qwen3-8B FP8 model is the quantized version of Alibaba's Qwen3-8B model, which is an auto-regressive language model that uses an optimized transformer architecture. For more information, please check here. The NVIDIA Qwen3-8B FP8 model is quantized with TensorRT Model Optimizer.
Params
8.2 B
Context
40,960
Downloads 30d
240 K
Likes
6
Download history
daily snapshots · 42 days
▲ 229 K in the last 30 days (48.9%)
469 K240 K
Aug 23Sep 2Sep 12Sep 21
469 K173 K
Aug 11Aug 25Sep 8Sep 21
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 | f8_e4m3 | 9.4 GB | 12.1 GB | ✅ Runs comfortably |
| model.safetensors (bf16, full) | bf16 + 40K ctx | 9.4 GB | 17.0 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 -s https://aimodelscomparison.com/api/v1/models/qwen3-8b-fp8-nvidia
{
"hf_id": "nvidia/Qwen3-8B-FP8",
"params_b": 8.19,
"context_length": 40960,
"license": { "id": "apache-2.0", "commercial": "yes" },
"downloads_30d": 239712,
"vram_estimates": [
{ "quant": "f8_e4m3", "gb": 12.1 }
],
"updated_at": "2026-08-11T01:00:25Z"
}
Specifications
- Architecture
- Qwen3ForCausalLM
- Parameters
- 8.2 B
- Tensor type
- F8_E4M3
- Context length
- 40,960
- Vocabulary
- 151,936
- Layers / heads
- 36 / 32
- Licence
- apache-2.0
- First seen on the Hub
- 2025-09-09
- Base model
- Qwen3-8B
- Training datasets
- undisclosed
- Added to our catalog
- 2026-08-11
Compare with any text-generation model