Model reference · open weights
OLMoE-0125 is an open-weight language model from allenai. OLMoE-1B-7B-0125-Instruct (BF16) weighs 13.8 GB; the smallest configuration that runs it is RTX 4060 Ti 16 GB.
Summary of the allenai/OLMoE-1B-7B-0125-Instruct model card, 2026-10-01
What it is
| Released by | allenai |
|---|---|
| Released | 2025-01-27 |
| Parameters | 6.9B |
| VRAM | 13.8 GB for the weights |
What it runs on
| Card | Requests at once | Context max | Memory |
|---|---|---|---|
| 4K each | |||
| RTX 3060 12 GB | — | — | 11.6 GB |
| RTX 4060 Ti 16 GB | 1 | all 4K | 15.4 GB |
| RTX 3090 24 GB | 16 | all 4K | 23.4 GB |
| RTX 4090 24 GB | 16 | all 4K | 23.4 GB |
| RTX 5090 32 GB | 31 | all 4K | 31.0 GB |
| L40S 48 GB | 55 | all 4K | 44.0 GB |
| A100 80 GB | 118 | all 4K | 78.2 GB |
| H100 80 GB | 113 | all 4K | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | 142 | all 4K | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | 167 | all 4K | 107 GB |
| H200 141 GB | 225 | all 4K | 138 GB |
| B200 180 GB | 295 | all 4K | 176 GB |
| 2× RTX 3060 12 GB tensor parallel | 15 | all 4K | 11.6 GB a card |
| 2× RTX 4060 Ti 16 GB tensor parallel | 29 | all 4K | 15.4 GB a card |
| Requests at once | 4K tokens each |
|---|---|
| 1 | 14.9 GB |
| 5 | 17.0 GB |
| 8 | 18.7 GB |
| 16 | 23.0 GB |
| 32 | 31.5 GB |
| 64 | 48.7 GB |
One card, with vLLM's small-card settings.
From the model card
OLMoE-1B-7B-0125-Instruct January 2025 is post-trained variant of the OLMoE-1B-7B January 2025 model, which has undergone supervised finetuning on an OLMo-specific variant of the Tülu 3 dataset and further DPO training on this dataset, and finally RLVR training using this data. Tülu 3 is designed for state-of-the-art performance on a diversity of tasks in addition to chat, such as MATH, GSM8K, and IFEval. Check out the OLMoE paper or Tülu 3 paper for more details!
OLMo is a series of Open Language Models designed to enable the science of language models. These models are trained on the Dolma dataset. We are releasing all code, checkpoints, logs (coming soon), and associated training details. The core models released in this batch include the following:
| Stage | OLMoE 1B-7B |
|---|---|
| Base Model | allenai/OLMoE-1B-7B-0125 |
| SFT | allenai/OLMoE-1B-7B-0125-SFT |
| DPO | allenai/OLMoE-1B-7B-0125-DPO |
| Final Models (RLVR) | allenai/OLMoE-1B-7B-0125-Instruct |
| Reward Model (RM) | allenai/OLMoE-1B-7B-0125-RM |
OLMo 2 will be supported in the next version of Transformers, and you need to install it from the main branch using:
pip install --upgrade git+https://github.com/huggingface/transformers.git
To load the model with HuggingFace, use the following snippet:
from transformers import AutoModelForCausalLM
olmo_model = AutoModelForCausalLM.from_pretrained("OLMoE-1B-7B-0125-Instruct")
The chat template for our models is formatted as:
Or with new lines expanded:
How are you doing?
I'm just a computer program, so I don't have feelings, but I'm functioning as expected. How can I assist you today?
It is embedded within the tokenizer as well, for tokenizer.apply_chat_template.
In Ai2 demos, we use this system prompt by default:
You are OLMo 2, a helpful and harmless AI Assistant built by the Allen Institute for AI.
The model has not been trained with a specific system prompt in mind.
The OLMo-2 models have limited safety training, but are not deployed automatically with in-the-loop filtering of responses like ChatGPT, so the model can produce problematic outputs (especially when prompted to do so). See the Falcon 180B model card for an example of this.
| Benchmark (eval) | OLMoE-1B-7B-0125-Instruct | OLMoE-1B-7B-0924-Instruct | OLMoE-1B-7B-0125-DPO | OLMoE-1B-7B-0125-SFT | OLMoE-1B-7B-0924-SFT |
|---|---|---|---|---|---|
| Avg. | 45.62 | 38.44 | 45.05 | 41.76 | 37.05 |
| MMLU (CoT) | 55.08 | 54.57 | 54.93 | 55.26 | 54.32 |
| PopQA | 19.75 | 20.56 | 19.65 | 20.12 | 21.01 |
| TruthfulQA | 50.56 | 49.14 | 49.99 | 45.48 | 44.66 |
| BigBenchHard (CoT) | 38.61 | 36.78 | 37.37 | 37.31 | 36.55 |
| DROP | 47.87 | 34.48 | 48.38 | 48.57 | 34.71 |
| MATH (Flex) | 21.41 | 8.16 | 20.36 | 21.38 | 8.15 |
| GSM8K | 72.40 | 47.38 | 64.59 | 55.72 | 42.46 |
| HumanEval | 62.30 | 63.04 | 61.92 | 62.58 | 63.72 |
| HumanEval+ | 54.37 | 58.93 | 57.61 | 55.67 | 57.40 |
| IFEval | 66.36 | 45 |
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.