SmolLM3 Checkpoints

We are releasing intermediate checkpoints of SmolLM3 to enable further research.

For more details, check the SmolLM GitHub repo with the end-to-end training and evaluation code:

✓ Pretraining scripts (nanotron)
✓ Post-training code SFT + APO (TRL/alignment-handbook)
✓ Evaluation scripts to reproduce all reported metrics

Pre-training

We release checkpoints every 40,000 steps, which equals 94.4B tokens. The GBS (Global Batch Size) in tokens for SmolLM3-3B is 2,359,296. To calculate the number of tokens from a given step:

nb_tokens = nb_step * GBS

Training Stages

Stage 1: Steps 0 to 3,450,000 (86 checkpoints) config

Stage 2: Steps 3,450,000 to 4,200,000 (19 checkpoints) config

Stage 3: Steps 4,200,000 to 4,720,000 (13 checkpoints) config

Long Context Extension

For the additional 2 stages that extend the context length to 64k, we sample checkpoints every 4,000 steps (9.4B tokens) for a total of 10 checkpoints:

Long Context 4k to 32k config

Long Context 32k to 64k config

Post-training

We release checkpoints at every step of our post-training recipe: Mid training, SFT, APO soup, and LC expert.

How to Load a Checkpoint

# pip install transformers
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
checkpoint = "HuggingFaceTB/SmolLM3-3B-checkpoints"
revision = "stage1-step-40000" # replace by the revision you want
device = torch.device("cuda" if torch.cuda.is_available() else "mps" if hasattr(torch, 'mps') and torch.mps.is_available() else "cpu")
tokenizer = AutoTokenizer.from_pretrained(checkpoint, revision=revision)
model = AutoModelForCausalLM.from_pretrained(checkpoint, revision=revision).to(device)
inputs = tokenizer.encode("Gravity is", return_tensors="pt").to(device)
outputs = model.generate(inputs)
print(tokenizer.decode(outputs[0]))

License

Apache 2.0

Citation

@misc{bakouch2025smollm3,
  title={{SmolLM3: smol, multilingual, long-context reasoner}},
  author={Bakouch, Elie and Ben Allal, Loubna and Lozhkov, Anton and Tazi, Nouamane and Tunstall, Lewis and Patiño, Carlos Miguel and Beeching, Edward and Roucher, Aymeric and Reedi, Aksel Joonas and Gallouédec, Quentin and Rasul, Kashif and Habib, Nathan and Fourrier, Clémentine and Kydlicek, Hynek and Penedo, Guilherme and Larcher, Hugo and Morlon, Mathieu and Srivastav, Vaibhav and Lochner, Joshua and Nguyen, Xuan-Son and Raffel, Colin and von Werra, Leandro and Wolf, Thomas},
  year={2025},
  howpublished={\url{https://huggingface.co/blog/smollm3}}
}

HuggingFaceTB
/

SmolLM3-3B-checkpoints