Reasoning
MiniMax M3
MiniMax's current flagship: a 427B-parameter sparse mixture-of-experts model (MiniMaxM3SparseForConditionalGeneration) accepting both image and text input, with a 1,048,576-token (~1M) context window.
MiniMax · MiniMax
Editorial review
Model checkpoints, context windows, provider support, local runtime compatibility, and license terms can change quickly. Verify the exact model card before production or commercial use.
Best for
Teams evaluating frontier-scale open-weight reasoning/coding models with genuine multimodal (image) input and a ~1M-token context window, willing to work within a named commercial license rather than a standard OSI one.
Who should use it
- Teams evaluating frontier-scale open-weight reasoning/coding models with genuine multimodal (image) input and a ~1M-token context window, willing to work within a named commercial license rather than a standard OSI one.
- Teams with access to hosted inference or server-class deployment paths.
- Developers evaluating coding assistant, repo-editing, and code review workflows.
- Teams testing tool-use, agentic planning, and multi-step workflow behavior.
Common workflows
- Coding, reasoning, tool use, agents, multimodal (image-and-text input)
- reasoning workflows
- coding workflows
- tool-use workflows
- agents workflows
Deployment and hardware notes
427B total parameters, sparse MoE. No GGUF exists in the official repository and the custom MiniMaxM3Sparse architecture class has no known llama.cpp support, so local consumer-hardware deployment is not currently possible regardless of quantization. Multi-GPU server inference (vLLM, SGLang) or a hosted provider only.
License and usage notes
MiniMax Community License. Open weights. Verify the exact model card and license terms for the checkpoint or hosted provider you use.
Strengths
- Open weights model option for MiniMax workflows.
- Teams evaluating frontier-scale open-weight reasoning/coding models with genuine multimodal (image) input and a ~1M-token context window, willing to work within a named commercial license rather than a standard OSI one.
- Tracked as Frontier 2026 in the OpenSourcesAI model directory.
Limitations
- Commercial use is free under the license's own terms below $20M in annual revenue (with attribution: display "Built with MiniMax M3" and notify MiniMax), but requires prior written authorization above that threshold -- read the LICENSE file, not just the model card, before commercial deployment. 427B total parameters with no official or community GGUF/llama.cpp support: this is a server-class or hosted-inference model only, not a local single-GPU deployment.
- 427B total parameters, sparse MoE. No GGUF exists in the official repository and the custom MiniMaxM3Sparse architecture class has no known llama.cpp support, so local consumer-hardware deployment is not currently possible regardless of quantization. Multi-GPU server inference (vLLM, SGLang) or a hosted provider only.
- Context window and limits: 1,048,576 tokens (~1M), confirmed from the model's published config.
- Verify the exact model card, provider docs, license, and serving support before production use.
Frontier-model verification note
This page is written to stay accurate as of the latest available 2026 public model information. Availability, licenses, context windows, API support, pricing, benchmark standing, and local-serving support can change quickly. Verify the official model card, provider docs, and license before using this model in production or commercial workflows.
Sources to verify
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Setup and deployment
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