Back to Gap Map Model components / Training & synthetic datasets

Tulu 3 SFT Mixture

Allen Institute for AI
open / Overall score: 3.5

Supervised fine-tuning dataset of roughly 939,000 samples combining 18 data sources, created by the Allen Institute for AI for its Tulu 3 post-training recipe. It covers conversation, instruction-following, math, code, safety and multilingual data across more than 70 languages, and underpins the Tulu 3 model family.

Some constituent subsets carry terms narrower than the mixture's own, which the card documents.

Openness

5 high confidence
5.0
license
odc-by(mixed subset licenses incl CC-BY-NC)
access
ungated
dataset_card
present

ODC-BY licensed and ungated with a full dataset card, though some subsets carry non-commercial licenses.

Adoption

3 high confidence
3.0

Adoption is measured by Hugging Face downloads of the dataset over the trailing month, the only usage channel on record for the Tulu 3 SFT Mixture.

Capability

4 high confidence
4.0

The Tulu 3 paper reports that models post-trained with this mixture and the wider Tulu 3 recipe surpass the instruct versions of Llama 3.1, Qwen 2.5 and Mistral as well as GPT-4o-mini, and Marin 8B Instruct also uses it for supervised fine-tuning. Ai2's newer Dolci suite, not this mixture, post-trains Olmo 3-Think 32B, which Ai2 reports as the strongest fully open thinking model.

  • https://arxiv.org/abs/2411.15124 recorded 2026-09-29

    The Tulu 3 paper abstract reports models "surpassing the instruct versions of Llama 3.1, Qwen 2.5, Mistral, and even closed models such as GPT-4o-mini and Claude 3.5-Haiku."

  • https://huggingface.co/marin-community/marin-8b-instruct recorded 2026-09-29

    The Marin 8B Instruct card says it is an "SFT-only model. It was trained on the following datasets:" and links allenai/tulu-3-sft-mixture.

Verified 2026-09-27