FlexOlmo-7x7B-1T

FlexOlmo-7x7B-1T (without router training) is a Mixture-of-Experts with 33B total parameters, combining independently trained experts on public-mix, news, math, code, academic texts, creative writing, and Reddit data. The public-mix expert is trained on 1T tokens of public data while the other experts are branched from the public-mix expert and trained on 50B tokens of their respective data.

This information and more can also be found:

• Paper: https://allenai.org/papers/flexolmo
• Code: https://github.com/allenai/FlexOlmo
• Blog: https://allenai.org/blog/flexolmo
• Data and corresponding models: | Corpus | Public | Math | News | Academic | Code | Creative Writing | Reddit | |------------------|----------------|----------------|----------------|----------------|----------------|------------------|----------------| | Model | Flex-public-7B-1T | Flex-math-2x7B-1T | Flex-news-2x7B-1T | Flex-pes2o-2x7B-1T | Flex-code-2x7B-1T | Flex-creative-2x7B-1T | Flex-reddit-2x7B-1T |

Use

Install transformers with version 4.57.0 or newer and run:

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

DEVICE = "cuda" if torch.cuda.is_available() else "cpu"

MODEL_NAME = "allenai/FlexOlmo-7x7B-1T"
TOKENIZER_NAME = "allenai/dolma2-tokenizer"
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME).to(DEVICE)
tokenizer = AutoTokenizer.from_pretrained(TOKENIZER_NAME)
inputs = tokenizer("Bitcoin is", return_tensors="pt")
inputs = {k: v.to(DEVICE) for k, v in inputs.items()}
out = model.generate(**inputs, max_length=64)
print(tokenizer.decode(out[0]))

Evaluation Snapshot

• The evaluation of the individual model refers to the dense model, not the 2x7B MoE model.

Citation

@misc{flexolmo,
      title={FlexOlmo: Open Language Models for Flexible Data Use},
      author={Weijia Shi and Akshita Bhagia and Kevin Farhat and Niklas Muennighoff and Pete Walsh and Jacob Morrison and Dustin Schwenk and Shayne Longpre and Jake Poznanski and Allyson Ettinger and Daogao Liu and Margaret Li and Mike Lewis and Wen-tau Yih and Dirk Groeneveld and Luca Soldaini and Kyle Lo and Noah A. Smith and Luke Zettlemoyer and Pang Wei Koh and Hannaneh Hajishirzi and Ali Farhadi and Sewon Min},
      year={2025},
      eprint={2507.07024},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://allenai.org/papers/flexolmo},
}