Providers
Provider-specific identifiers, limits, and listed prices per million tokens. Every row links back to the provider's own documentation.
The model record exists, but no source-linked provider offer is available yet.
Submit a sourceMiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...
Provider-specific identifiers, limits, and listed prices per million tokens. Every row links back to the provider's own documentation.
The model record exists, but no source-linked provider offer is available yet.
Submit a sourceRecorded from the source catalog and provider listings.
minimax/minimax-m1Every result stays attached to its source, version, metric and harness. Scores from different versions are never merged, and the profile below plots each benchmark against its own population rather than on a shared scale.
Each strip shows every published score for that benchmark, with this model marked. The lighter shape behind the ticks is the density of results, and the dashed line is the median.
Listed input price plotted against Intelligence Index, the benchmark with the widest published coverage that this model appears in.
The stepped line is the efficient frontier: at each price, the best score available for that money or less. A model sitting on it is not being beaten by anything cheaper. Price is log-scaled because listed rates span four orders of magnitude. Only models with both a listed price and a score on this benchmark can appear.
Field-level changes detected between successful source imports.
Every figure on this page traces back to one of these records.
Fetch the complete source-linked model record. No key, no account, no rate-limited tier.
GET https://modelbench.lol/api/v1/models/minimax/minimax-m1curl "https://modelbench.lol/api/v1/models/minimax/minimax-m1"Answered directly from the stored record — nothing here is generated beyond the catalog's own fields.
MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it. It is published by MiniMax and catalogued here from OpenRouter.
MiniMax: MiniMax M1 accepts up to 1M tokens of context and returns up to 40K output tokens.
MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding,...
MiniMax: MiniMax M2.7MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent...
MiniMax: MiniMax M2.5MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1...
MiniMax: MiniMax M2-herMiniMax M2-her is a dialogue-first large language model built for immersive roleplay, character-driven chat, and expressive multi-turn conversations. Designed to stay consistent in tone and personality, it supports rich message...