HuggingFaceTB / text-generation updated 11 months ago

SmolLM3-3B-Base

Name: SmolLM3-3B-Base
Author: HuggingFaceTB

1. Model Summary 2. How to use 3. Evaluation 4. Training 5. Limitations 6. License

Params

3.1 B

Context

65,536

Downloads 30d

161 K

Likes

167

Commercial use: allowed apache-2.0 Not gated SAFETENSORS 8 languages View on Hugging Face ↗

Download history

tracking started — chart appears after 7 days of snapshots (5 recorded)

161 K downloads in the last 30 days

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	6.2 GB	7.7 GB	✅ Runs comfortably
model.safetensors (bf16, full)	bf16 + 64K ctx	6.2 GB	11.0 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 · api/v1

$ curl -s https://aimodelscomparison.com/api/v1/models/smollm3-3b-base
{
  "hf_id": "HuggingFaceTB/SmolLM3-3B-Base",
  "params_b": 3.08,
  "context_length": 65536,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 160743,
  "vram_estimates": [
    { "quant": "bf16", "gb": 7.7 }
  ],
  "updated_at": "2026-08-02T01:00:38Z"
}

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

Specifications

Architecture: SmolLM3ForCausalLM
Parameters: 3.1 B
Tensor type: BF16
Context length: 65,536
Vocabulary: 128,256
Layers / heads: 36 / 16
Licence: apache-2.0
First seen on the Hub: 2025-06-19
Training datasets: undisclosed
Added to our catalog: 2026-08-02

Compare with

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Appears in

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