Tag: minimax
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MiniMax Ships M3.1 Flash: API Now, Weights Due October 23
On October 19, 2026, MiniMax released M3.1 Flash, a faster and cheaper successor to June’s M3, and put it on its API the same day — but the weights are not out yet. MiniMax’s launch post says only that the weights “will be released later”. The Decoder and SiliconANGLE both report October 23. Until a […]
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H3-World Turns MiniMax-H3 Into a Playable World Model
On September 1, 2026, researchers from Tencent, the National University of Singapore, and The Hong Kong Polytechnic University posted H3-World — a framework that converts MiniMax-H3, the 33B omni-modal video generator whose weights shipped in August, into an interactive world model you drive with keyboard input. It adds no action encoder and no dedicated control […]
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MiniMax Opens Music 3.0 Weights — No Territorial Carve-Out This Time
MiniMax published the weights for Music 3.0 on August 13, 2026, releasing an ~11.1B-parameter text-to-music model that generates complete five-minute songs — vocals, arrangement, and production — in a single pass. The weights are on Hugging Face, GitHub, and ModelScope, and ComfyUI shipped support the same day. Notably, the accompanying MiniMax-Music3 Community License contains no […]
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MiniMax Ships H3 Weights — With the US and EU Excluded
MiniMax published the MiniMax-H3 weights to Hugging Face on August 3, 2026 — three days after announcing the omni-modal video model and promising an open release “in the coming days.” The checkpoints are real, the quantized build is small enough to matter, and ComfyUI shipped day-0 support. But the accompanying MiniMax H3 Community License carves […]
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MiniMax Releases H3: 2K Video With Native Audio, Open Weights Promised
MiniMax released H3 on July 30, 2026 — a general-purpose multimodal video model that generates clips of up to 15 seconds at native 2K resolution with synchronized stereo audio, and takes text, images, video, and audio as reference inputs in a single request. The Shanghai company says it will publish H3’s weights “within days,” which […]
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MiniMax M3: Frontier Coding, 1M Context, and Sparse Attention
MiniMax released M3 on June 1, 2026, claiming the first open-weight model to combine frontier coding, a 1-million-token context window, and native multimodality in a single architecture. The headline is not just the benchmark sheet — it is the engine underneath: a new sparse-attention mechanism (MSA) that the company says cuts per-token compute at 1M […]
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MiniMax M2.7 Ships as Open Weights: Frontier Agentic Model on Hugging Face
MiniMax M2.7 is now downloadable. The 230B-parameter self-evolving model that MiniMax unveiled in March has shipped as open weights on Hugging Face and ModelScope under a Modified-MIT license, and community quantizations already cover everything from a 60 GB 1-bit build to the full 457 GB BF16 release — putting a frontier-class agentic model in reach […]
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MiniMax M2.7: The First AI Model That Helps Train Itself
MiniMax has released M2.7, the first frontier AI model designed to participate in its own training loop. Announced on March 18, 2026, M2.7 introduces what MiniMax calls “self-evolution” — the model autonomously analyzes its own failure trajectories, modifies its scaffold code, and runs evaluations across 100+ iterative rounds, achieving a 30% performance improvement on internal […]
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MiniMax M2.5: Frontier AI Performance at a Fraction of the Cost
Key points Announced on February 12, 2026, MiniMax’s M2.5 ships as open weights under a modified MIT license and, according to the company, matches leading proprietary systems at one-tenth to one-twentieth of their cost. M2.5 is a mixture-of-experts model with 229 billion total parameters, 10 billion active parameters and a 200,000-token context window, designed for […]
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MiniMax M1: The World’s First Open-Weight, Million-Token Context AI Model
MiniMax, a Shanghai-based AI company founded in 2021, has released MiniMax M1, an open-weight reasoning model designed to handle extremely long inputs—up to one million tokens—while maintaining high inference efficiency. This marks a significant milestone in large-scale model design, positioning M1 as a leader in applications requiring deep, multi-step reasoning over vast contexts (arxiv.org, en.wikipedia.org). […]