unsloth / text-generation updated 1 year ago

Llama-3.2-3B-Instruct

Name: Llama-3.2-3B-Instruct
Author: unsloth

We have a free Google Colab Tesla T4 notebook for Llama 3.2 (3B) here: https://colab.research.google.com/drive/1T5-zKWM5OD21QHwXHiV9ixTRR7k3iB9?usp=sharing

Params

3.2 B

Context

131,072

Downloads 30d

189 K

Likes

Commercial use: conditional · llama3.2 Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

189 K157 K

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	bf16	6.4 GB	8.0 GB	✅ Runs comfortably
model.safetensors (bf16, full)	bf16 + 128K ctx	6.4 GB	15.3 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-3-2-3b-instruct-unsloth
{
  "hf_id": "unsloth/Llama-3.2-3B-Instruct",
  "params_b": 3.21,
  "context_length": 131072,
  "license": { "id": "llama3.2", "commercial": "conditional" },
  "downloads_30d": 189016,
  "vram_estimates": [
    { "quant": "bf16", "gb": 8.0 }
  ],
  "updated_at": "2026-07-28T18:09:12Z"
}

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

Specifications

Architecture: LlamaForCausalLM
Parameters: 3.2 B
Tensor type: BF16
Context length: 131,072
Vocabulary: 128,256
Layers / heads: 28 / 24
Licence: llama3.2
First seen on the Hub: 2024-09-25
Base model: Llama-3.2-3B-Instruct
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Family

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

Base Llama-3.2-3B-Instruct meta-llama 1.5 M

Compare with

Qwen3-8B 16.3 M Qwen2.5-1.5B-Instruct 14.0 M Qwen2.5-7B-Instruct 12.1 M Llama-3.2-1B-Instruct 10.4 M Qwen3-1.7B 7.8 M Qwen2.5-3B-Instruct 6.0 M

Appears in

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