What are the hardware requirements for OLMo 7B Hf?

OLMo 7B Hf requires approximately 27.6 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed OLMo 7B Hf and how large is it?

OLMo 7B Hf is developed by allenai, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does OLMo 7B Hf perform on standard benchmarks?

OLMo 7B Hf has the following published scores: MMLU 28.13. Compare against reference models on this page or on the LLM Explorer leaderboards.

OLMo 7B Hf by allenai — VRAM 27.6GB, 2K context

Name: OLMo 7B Hf
Author: allenai

OLMo 7B Hf is an open-source language model by allenai. Features: 7b LLM, VRAM: 27.6GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.21, Arc: 45.7, HellaSwag: 77.3, MMLU: 28.1, GSM8K: 3.8.

Arxiv:2302.13971 Arxiv:2402.00838 Dataset:allenai/dolma En Endpoints compatible Olmo Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/allenai/OLMo-7B-hf

OLMo 7B Hf Benchmarks

ARC: 45.65 vs 96.7 (so35)^-52.8%

HellaSwag: 77.31 vs 95.3 (gpt4)^-18.9%

MMLU: 28.13 vs 88.3 (so35)^-68.1%

GSM8K: 3.79 vs 96.4 (so35)^-96.1%

LLME Score: 0.20649

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

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OLMo 7B Hf Parameters and Internals

Model Type

Transformer style autoregressive language model

Use Cases

Areas:

Research, Commercial applications

Applications:

Natural language processing tasks

Primary Use Cases:

Language modeling, Text generation

Limitations:

May produce harmful or biased content

Considerations:

User awareness of potential risks and limitations.

Additional Notes

Model checkpoints and code are open-source.

Supported Languages

English (High)

Training Details

Data Sources:

Dolma dataset

Data Volume:

2.5 Trillion Training Tokens

Methodology:

Sequential Block Transformer with SwiGLU activation and RoPE positional embeddings

Context Length:

2048

Hardware Used:

MI250X GPUs at LUMI supercomputer, A100-40GB GPUs provided by MosaicML

Model Architecture:

Transformer model with 32 layers, 4096 hidden size, 32 attention heads, sequential block type

Safety Evaluation

Risk Categories:

Harmful content, Sensitive content, Bias

Ethical Considerations:

Model can generate harmful and biased content.

Responsible Ai Considerations

Fairness:

Potential bias in language outputs.

Transparency:

Open-source model with accessible training data details.

Accountability:

Developed by Allen Institute for AI.

Mitigation Strategies:

Awareness of risks and user guidelines.

Input Output

Input Format:

Text prompts

Accepted Modalities:

Text

Output Format:

Generated text

Performance Tips:

Use optimized settings for text generation speed and accuracy.

Release Notes

Version:

Notes:

Initial release for open language modeling.

LLM Name	OLMo 7B Hf
Repository 🤗	https://huggingface.co/allenai/OLMo-7B-hf
Model Size	7b
Required VRAM	27.6 GB
Updated	2026-05-19
Maintainer	allenai
Model Type	olmo
Model Files	4.9 GB: 1-of-6 5.0 GB: 2-of-6 4.9 GB: 3-of-6 4.9 GB: 4-of-6 4.9 GB: 5-of-6 3.0 GB: 6-of-6
Supported Languages	en
Model Architecture	OlmoForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.40.0.dev0
Tokenizer Class	GPTNeoXTokenizer
Padding Token	<\|padding\|>
Vocabulary Size	50304
Torch Data Type	float32

Best Alternatives to OLMo 7B Hf

Best Alternatives	Context / RAM	Downloads	Likes
OLMo 1.7 7B Hf	4K / 27.6 GB	26379	8
OLMo 7B 0724 Hf	4K / 27.6 GB	1836	17
OLMo 7B 0724 Instruct Hf	4K / 13.8 GB	1067	7
OLMo 7B 0424 Hf	4K / 27.6 GB	792	14
OLMo 7B Instruct Hf	2K / 27.6 GB	1229	6
OLMo 7B 0724 SFT Hf	2K / 13.8 GB	101	4
OLMo 7B SFT Hf	2K / 27.6 GB	158	1
Olmo 7B Hf Step0	2K / 27.6 GB	6	0
OLMo 7B Twin 2T Hf	2K / 27.6 GB	397	1
OLMo 7B Instruct Hf	2K / 27.6 GB	11	3

Note: green Score (e.g. "73.2") means that the model is better than allenai/OLMo-7B-hf.

Rank the OLMo 7B Hf Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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Release v20260328a

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OLMo 7B Hf by allenai

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OLMo 7B Hf Benchmarks

OLMo 7B Hf Parameters and Internals

Best Alternatives to OLMo 7B Hf

Rank the OLMo 7B Hf Capabilities

What open-source LLMs or SLMs are you in search of? 53999 in total.