MiniMax (official)
1.6K posts
@MiniMax_AI
Agent: @MiniMaxAgent Token Plan: https://t.co/BDCycxepZw API: https://t.co/fHRdSV7BwZ Community: https://t.co/uhxxfLgkLU
Qatar vs Switzerland. Five models and one human predicted. Everyone took a side. @MiniMax_AI's M3 took the draw, and it was the only correct call. So we ran it back through Kilo CLI to see why. The breakdown: the bench excludes betting odds on purpose, so the 64% Switzerland market line never entered the picture. MiniMax weighed form instead. Identical WWDLW records, Qatar's higher raw ratings, Switzerland's stronger league level, called even. One model, one good read. Built on Kilo. #FWC26
forked clicky into a tiny Mac top-bar app that reviews my website designs, talks back, and patches the code itself. the loop: “what’s wrong with this?” → @MiniMax_AI M3 reads the screen + points at the weak parts “fix it” → it edits the actual files on disk @togethercompute served the full model stack for the demo: Parakeet for STT, MiniMax Speech 2.8 for voice, and MiniMax M3 for reasoning. Even saw a reduction in latency from 546ms to 277ms when switching STT to Together AI demo below
The frontier labs are coming to World's Fair. @OpenAI, @AnthropicAI, @Google DeepMind, @amazon AGI Labs, @Zai_org, and @MiniMax_AI are all on the program this year. The people building the models, in the same place as the people building on them. June 29 to July 2 in San Francisco. ai.engineer/worldsfair
MiniMax M3, Open-Weight, Now On Hugging Face , with only ~428B parameters and ~23B activated parameters Weights: huggingface.co/MiniMaxAI/Mini… MiniMax Sparse Attention: huggingface.co/papers/2606.13…
my afternoon tea activity is reading the best papers from last week in my garden. <3 Sparse Attention from @MiniMax_AI and From AGI to ASI from @GoogleDeepMind get some sun, folks - the tax here is so high.
Open-weight MiniMax M3 filled out a US customs form from a driver's license photo For this test we deployed MiniMax M3 Q4 using MLX-VLM on a Mac Studio M3 Ultra 512GB RAM. The model was tasked with reading a scanned document and an ID card photo, then completing a declaration form Output: 736 tokens · Input: 1,847 tokens · Time: ~31s The model analyzed both inputs, streamed its reasoning, and then called three tools: write_field for text fields, mark for Yes/No checkboxes, and sign for the signature and date. It extracted the required information, mapped it to the correct fields and completed the form without any manual input
MiniMax M3 is now FREE in Command Code! We're partnering up with MiniMax. One of the best open models. LIVE NOW • all subscribers $1 Go, Pro, Max, Ultra • June 15-17 till capacity lasts HOW $ npm i -g command-code $ cmd /model MiniMax M3 (FREE) What are you building?
To celebrate, we’re launching a 3-day global campaign: 🌟 100% FREE access to MiniMax M3 on 0G Compute 📅 June 15-18 (12:00 UTC) 💰 $0 cost (just 1 $0G in your account to verify you’re a real user) 🚀 Register in advance, M3 goes free on June 15: pc.0g.ai/models
It's live. MiniMax M3 is now 100% free on 0G Private Computer. The #1 open-weight model, zero cost for the next 3 days. Try it now: pc.0g.ai/models/minimax…
