Model reference · open weights

FlexOlmo-7x-1T

Available as managed deployment LLMs allenai Text gen 1 variants 9k dl/mo

FlexOlmo-7x-1T is an open-weight language model from allenai. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.

What it is

Makerallenai
TypeLanguage models
TaskText gen
Parameters (lead)33.3B
Context4k tokens
Runs withtransformers
Released2025-06-11
Popularity9k downloads / month
LicenceOpen weights

About

What FlexOlmo-7x-1T is

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:

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

ModelMC9Gen5MMLUMMLU ProAGIEvalBBHMath2NewsGPoemGSciRIFF5Code4Avg.
Prev. Public model68.758.855.926.239.935.78.276.047.848.11.142.4
Individual
Math62.544.350.624.142.045.653.142.628.050.715.841.8
Code40.539.429.514.527.438.16.045.128.248.021.030.7
News46.548.636.415.225.730.92.577.726.947.00.032.5
Creative Writing42.743.931.511.623.327.61.756.967.542.40.031.7
Academic41.045.233.814.824.132.46.551.823.052.00.029.5
Reddit64.736.556.125.535.519.72.554.18.632.71.730.7
Combined
BTM (top-2)68.757.759.428.343.244.323.173.654.446.324.047.6
FlexOlmo-7x7B-1T65.644.750.922.137.235.625.455.839.045.910.639.3
FlexOlmo-7x7B-1T-RT70.659.760.030.544.645.947.779.767.654.511.352.0
  • 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},
}

From the published model card. Full card on the HuggingFace links in the sidebar.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys flexolmo-7x-1t for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (flexolmo-7x-1t below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"flexolmo-7x-1t","messages":[{"role":"user","content":"Hello"}]}'

Create an account — your API key is available in the console. 5M tokens/month currently included with every new account at launch.

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