Llama-3.2-3B-Instruct-FP8
- Model Architecture: Llama-3 - Input: Text - Output: Text - Model Optimizations: - Activation quantization: FP8 - Weight quantization: FP8 - Intended Use Cases: Intended for commercial and research use multiple languages. Similarly to Llama-3.2-3B-Instruct, this models is intended for assistant-like chat. - Out-of-scope: Use in any manner that violates applicable laws or regulations (including trade compliance laws)...
Params
3.6 B
Context
131,072
Downloads 30d
173 K
Likes
6
Download history
daily snapshots · 40 days
▲ 12 K in the last 30 days (6.3%)
186 K173 K
Oct 12Oct 22Nov 1Nov 10
186 K173 K
Oct 2Oct 15Oct 28Nov 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 | f8_e4m3 | 4.4 GB | 5.9 GB | ✅ Runs comfortably |
| model.safetensors (bf16, full) | bf16 + 128K ctx | 4.4 GB | 14.0 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/llama-3-2-3b-instruct-fp8
{
"hf_id": "RedHatAI/Llama-3.2-3B-Instruct-FP8",
"params_b": 3.61,
"context_length": 131072,
"license": { "id": "llama3.2", "commercial": "conditional" },
"downloads_30d": 173310,
"vram_estimates": [
{ "quant": "f8_e4m3", "gb": 5.9 }
],
"updated_at": "2026-10-02T01:00:31Z"
}
Specifications
- Architecture
- LlamaForCausalLM
- Parameters
- 3.6 B
- Tensor type
- F8_E4M3
- Context length
- 131,072
- Vocabulary
- 128,256
- Layers / heads
- 28 / 24
- Licence
- llama3.2
- First seen on the Hub
- 2024-09-26
- Base model
- Llama-3.2-3B-Instruct
- Training datasets
- undisclosed
- Added to our catalog
- 2026-10-02
Family
Base model and the most-downloaded derivatives in the catalog.
Compare with any text-generation model