HuggingFaceTB / text-generation updated 1 year ago

SmolLM2-135M

Name: SmolLM2-135M
Author: HuggingFaceTB

SmolLM2 is a family of compact language models available in three size: 135M, 360M, and 1.7B parameters. They are capable of solving a wide range of tasks while being lightweight enough to run on-device. More details in our paper: https://arxiv.org/abs/2502.02737

Params

130 M

Context

8,192

Downloads 30d

1.8 M

Likes

219

Commercial use: allowed apache-2.0 Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

1.9 M1.7 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	bf16	0.3 GB	0.8 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/smollm2-135m
{
  "hf_id": "HuggingFaceTB/SmolLM2-135M",
  "params_b": 0.13,
  "context_length": 8192,
  "license": { "id": "apache-2.0", "commercial": "yes" },
  "downloads_30d": 1824932,
  "vram_estimates": [
    { "quant": "bf16", "gb": 0.8 }
  ],
  "updated_at": "2026-07-28T18:02:54Z"
}

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

Specifications

Architecture: LlamaForCausalLM
Parameters: 130 M
Tensor type: BF16
Context length: 8,192
Vocabulary: 49,152
Layers / heads: 30 / 9
Licence: apache-2.0
First seen on the Hub: 2024-10-31
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Family

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

Derivative SmolLM2-135M-Instruct HuggingFaceTB 2.0 M

Compare with

gpt2 13.7 M Qwen2.5-0.5B-Instruct 6.6 M distilgpt2 2.6 M pythia-160m 2.5 M gemma-3-270m 2.1 M SmolLM2-135M-Instruct 2.0 M

Appears in

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