MPT-7B
by Community
Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available fo
OSS
MPT-7B
Added 1 June 2026
Overview
MPT-7B is an open-source transformer model trained from scratch on 1 trillion tokens of text and code. It matches the quality of LLaMA-7B and is available for commercial use. The model was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k.
Best for
Best for
Developers and organizations needing a high-quality open-source LLM with commercial rights for text and code tasks.
Use cases
- Fine-tuning for domain-specific language tasks
- Generating text or code in production applications
- Building custom LLM solutions with a commercially friendly license
Notes
MPT-7B is an open-source transformer model trained from scratch on 1 trillion tokens of text and code. It matches the quality of LLaMA-7B and is available for commercial use. The model was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k.
Use cases
- Fine-tuning for domain-specific language tasks
- Generating text or code in production applications
- Building custom LLM solutions with a commercially friendly license
Pros
- Open source and freely available for commercial use
- Matches LLaMA-7B quality despite lower training cost
- Trained with zero human intervention, demonstrating scalability
Cons
- Requires significant GPU resources for inference and fine-tuning
- Smaller context window and capacity compared to larger models like MPT-30B
- Community is smaller than LLaMA’s, potentially less third-party tooling
Indexed from awesome-llm and enriched against its public facts.
Pros
- Open source and freely available for commercial use
- Matches LLaMA-7B quality despite lower training cost
- Trained with zero human intervention, demonstrating scalability
Cons
- Requires significant GPU resources for inference and fine-tuning
- Smaller context window and capacity compared to larger models like MPT-30B
- Community is smaller than LLaMA’s, potentially less third-party tooling
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