MiniMax

MiniMax H3 now has Hugging Face weights, fal endpoints, AI Toolkit LoRA support, and reported single-RTX-5090 local runs. MiniMax also said deployment in the US, EU, UK, and South Korea is available through formal authorization.

MiniMax released H3 weights on Hugging Face for text-to-video, image-to-video, reference-to-video, and editing workflows. vLLM-Omni, ComfyUI, SGLang Diffusion, and fal added support at launch.

MiniMax announced H3 for app and API access, with OpenRouter, Vercel, Pika, fal, Runway, and Venice integrations. Artificial Analysis ranked it No. 1 for video editing, and MiniMax said open weights are planned.

MiniMax published M3 weights on Hugging Face with 428B total parameters, 23B active parameters, 1M context, and multimodal support. Unsloth quickly added local GGUF builds, so teams can try 2-bit runs at 138GB RAM or VRAM and 3-bit at 165GB.

A day after MiniMax M3 launched, OpenCode, Hermes Agent, Flowith, Atomic Chat, Kilo Code, Cloudflare AI Gateway, and Vercel AI Gateway shipped support. That breadth shows M3 plugged into agent harnesses and routing layers immediately, not just its own API.

A day after MiniMax M3 launched, independent testers posted mixed results: cheap demos and design tasks worked, but several coding runs stalled, broke features, or used more tokens than expected. New external numbers added nuance, with Context Arena falling sharply after 64k context and one DeepSWE run passing 15 of 113 tasks.

MiniMax shipped M3 with a 1M-token context window, native multimodal input, and frontier coding claims across SWE-Bench Pro, Terminal Bench, and MCP Atlas. It also appeared on OpenRouter, Ollama Cloud, Venice, Hermes, Cline, Together, and Arena on day one.

MiniMax started winding down its M2 series while previewing M3 and a new sparse-attention design with large long-context speedup claims. The teaser points to a fresh open-model race around block selection, GQA, and million-token serving efficiency.

MiniMax M2.7 moved from announcement to deployment, with GGUF guidance for 128 GB local systems and same-day availability on Together, Fireworks, Hugging Face, and ModelScope. Use the local and managed serving options now, but check the non-commercial license before adopting the 230B model.

MiniMax open-sourced M2.7 and published coding and agent benchmark claims including 56.22% SWE-Pro and 57.0% Terminal Bench 2. Day-zero support from SGLang, vLLM, Ollama Cloud, Together AI, and NVIDIA NIM makes it easy to try on common serving stacks.

MiniMax introduced a flat-rate Token Plan that covers text, speech, music, video, and image APIs under one subscription. It gives teams one predictable bill across modalities and can be used in third-party harnesses, not just MiniMax apps.

Skyler Miao said MiniMax M2.7 open weights are due in roughly two weeks, with updates tuned for agent tasks. Separate replies also confirm multimodal M3, so local-stack builders should watch both the drop and the benchmark setup.

MiniMax released M2.7 on its API and agent platform with coding and office-task claims plus a self-improving training harness. Engineers should validate the benchmark gains on real workloads, especially given mixed third-party results and aggressive pricing.