RedHatAI / text-generation updated 1 year ago

Llama-3.2-1B-Instruct-FP8-dynamic

Name: Llama-3.2-1B-Instruct-FP8-dynamic
Author: RedHatAI

- Model Architecture: Meta-Llama-3.2 - Input: Text - Output: Text - Model Optimizations: - Weight quantization: FP8 - Activation quantization: FP8 - Intended Use Cases: Intended for commercial and research use in multiple languages. Similarly to Llama-3.2-1B-Instruct, this models is intended for assistant-like chat. - Out-of-scope: Use in any manner that violates applicable laws or regulations (including trade compli...

Params

1.5 B

Context

131,072

Downloads 30d

1.5 M

Likes

Commercial use: conditional · llama3.2 Not gated SAFETENSORS 8 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

1.6 M1.5 M

Jul 28Jul 31Aug 3Aug 6

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	2.0 GB	3.0 GB	✅ Runs comfortably
model.safetensors (bf16, full)	bf16 + 128K ctx	2.0 GB	6.3 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/llama-3-2-1b-instruct-fp8-dynamic
{
  "hf_id": "RedHatAI/Llama-3.2-1B-Instruct-FP8-dynamic",
  "params_b": 1.50,
  "context_length": 131072,
  "license": { "id": "llama3.2", "commercial": "conditional" },
  "downloads_30d": 1491528,
  "vram_estimates": [
    { "quant": "f8_e4m3", "gb": 3.0 }
  ],
  "updated_at": "2026-07-28T18:03:05Z"
}

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

Specifications

Architecture: LlamaForCausalLM
Parameters: 1.5 B
Tensor type: F8_E4M3
Context length: 131,072
Vocabulary: 128,256
Layers / heads: 16 / 32
Licence: llama3.2
First seen on the Hub: 2024-09-25
Base model: Llama-3.2-1B-Instruct
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Family

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

Base Llama-3.2-1B-Instruct meta-llama 10.4 M

Compare with

Qwen3-0.6B 29.7 M Qwen2.5-1.5B-Instruct 14.0 M Llama-3.2-1B-Instruct 10.4 M Qwen3-1.7B 7.8 M gemma-3-1b-it 4.7 M Qwen2-1.5B-Instruct 3.2 M

Appears in

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