Llama-3.2-3B-Instruct-GGUF
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
—
Context
131,072
Downloads 30d
224 K
Likes
80
Download history
daily snapshots · 17 days242 K192 K
Sep 5Sep 10Sep 16Sep 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 |
|---|---|---|---|---|
| Llama-3.2-3B-Instruct-Q2_K.gguf | Q2_K | 1.4 GB | 2.0 GB | ✅ Runs comfortably |
| Llama-3.2-3B-Instruct-Q2_K_L.gguf | Q2_K_L | 1.4 GB | 2.0 GB | ✅ Runs comfortably |
| Llama-3.2-3B-Instruct-Q3_K_S.gguf | Q3_K_S | 1.5 GB | 2.2 GB | ✅ Runs comfortably |
| Llama-3.2-3B-Instruct-Q3_K_M.gguf | Q3_K_M | 1.7 GB | 2.4 GB | ✅ Runs comfortably |
| Llama-3.2-3B-Instruct-IQ4_XS.gguf | IQ4_XS | 1.8 GB | 2.5 GB | ✅ Runs comfortably |
| Llama-3.2-3B-Instruct-IQ4_NL.gguf | IQ4_NL | 1.9 GB | 2.6 GB | ✅ Runs comfortably |
| Llama-3.2-3B-Instruct-Q4_0.gguf | Q4_0 | 1.9 GB | 2.6 GB | ✅ Runs comfortably |
| Llama-3.2-3B-Instruct-BF16.gguf | GGUF | 6.4 GB | 7.6 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$ ollama run llama-3-2-3b-instruct-gguf-unsloth # pin the quantization explicitly $ ollama run llama-3-2-3b-instruct-gguf-unsloth-q4_0
$ huggingface-cli download unsloth/Llama-3.2-3B-Instruct-GGUF-GGUF \
Llama-3.2-3B-Instruct-Q4_0.gguf --local-dir .
$ llama-cli -m Llama-3.2-3B-Instruct-Q4_0.gguf \
-c 8192 -ngl 99 -t 8 --color
$ curl -s https://aimodelscomparison.com/api/v1/models/llama-3-2-3b-instruct-gguf-unsloth
{
"hf_id": "unsloth/Llama-3.2-3B-Instruct-GGUF",
"params_b": null,
"context_length": 131072,
"license": { "id": "llama3.2", "commercial": "conditional" },
"downloads_30d": 224233,
"vram_estimates": [
{ "quant": "GGUF", "gb": 7.6 },
{ "quant": "IQ4_NL", "gb": 2.6 }
],
"updated_at": "2026-09-05T01:00:29Z"
}
Specifications
- Architecture
- LlamaForCausalLM
- 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
- 2026-09-05
Family
Base model and the most-downloaded derivatives in the catalog.
Compare with any text-generation model