OLMo Models by Allen Institute for Artificial Intelligence (AI2)
Last refreshed 2026-04-27. Next refresh: weekly.
Details
Capabilities
About
The OLMo family of large language models (LLMs) is a series of open-source models developed by the Allen Institute for Artificial Intelligence (AI2) to advance the science of language modeling. These models stand out for their openness, offering researchers access to the training data, code, models, and evaluation resources. This transparency helps examine various aspects of LLM development, including biases and risks. Trained on the Dolma dataset, OLMo models utilize the Tulu SFT mixture and a refined UltraFeedback dataset for enhanced question answering. The family includes different models with varying parameters, such as 1B and 7B, reflecting distinct training phases and optimizations, and encourages collaborative research within the open-source AI community 123.
Decision facts
- Best fit
- reasoningJSON / Tool usestructured outputs
- Capability starting point
- OLMo 3.1 32B Instruct with 64k context and JSON / Tool use and structured outputs
- Lowest tracked input
- OLMo 7B · $0.2/1M · Together AI
- Closest related family
- Tulu
Current Variants
Use-when guidance is based on each model's tracked capabilities, context window, release date, and replacement status.
Use when the workload needs 64k context, 32B parameters, and reasoning.
Use when the workload needs 64k context, 32B parameters, and JSON / Tool use.
Use when the workload needs 7B parameters and structured outputs.
Use when the workload needs 1B parameters and structured outputs.
Use when the workload needs 7B parameters and structured outputs.
| Model | Use when | Released | Signals | Status |
|---|---|---|---|---|
| OLMo 3 32B Think | Use when the workload needs 64k context, 32B parameters, and reasoning. | 2026-03 | 64k context32B parametersreasoning | Current |
| OLMo 3.1 32B Instruct | Use when the workload needs 64k context, 32B parameters, and JSON / Tool use. | 2026-02 | 64k context32B parametersJSON / Tool use | Current |
| OLMo 7B | Use when the workload needs 7B parameters and structured outputs. | 2024-02 | 7B parametersstructured outputs | Current |
| OLMo 1B | Use when the workload needs 1B parameters and structured outputs. | 2024-02 | 1B parametersstructured outputs | Current |
| OLMo 7B Twin-2T | Use when the workload needs 7B parameters and structured outputs. | 2024-02 | 7B parametersstructured outputs | Current |
| OLMo 1.7 7B | Use when the workload needs 7B parameters. | 2024-02 | 7B parameters | Current |
Release Timeline
3 release groupsSpecifications(6 models)
| Model | Released | Context | Parameters | Reasoning | JSON / Tool use | Structured Outputs |
|---|---|---|---|---|---|---|
| OLMo 3 32B Think | 2026-03 | 64k | 32B | Yes | No | No |
| OLMo 3.1 32B Instruct | 2026-02 | 64k | 32B | No | Yes | Yes |
| OLMo 7B | 2024-02 | — | 7B | No | No | Yes |
| OLMo 1B | 2024-02 | — | 1B | No | No | Yes |
| OLMo 7B Twin-2T | 2024-02 | — | 7B | No | No | Yes |
| OLMo 1.7 7B | 2024-02 | — | 7B | No | No | No |
Available From(3 providers)
Pricing
| Model | Provider | Input / 1M | Output / 1M | Type |
|---|---|---|---|---|
| OLMo 7B | Together AI | $0.2 | $0.2 | Serverless |
| OLMo 7B Twin-2T | Together AI | $0.2 | $0.2 | Serverless |
| OLMo 1B | OpenRouter | $15 | $60 | Serverless |
