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This is just unbelievable.
Imagine having a model that's:
More than 5 times cheaper than Claude Opus -- yet just as intelligent?
Blazing fast -- up to 15x faster than Claude Opus for heavy prompts and massive context?
Open-source with open weights to top it all off?
Yeah it's definitely no surprise how so many people have been going absolutely wild over the few days over the new MiniMax M3.
Look how closely it matches Claude's and GPT's capabilities! It's even better in certain key areas:
I still can't wrap my head around the absolutely wild feats of endurance and intelligent it displayed during testing -- and has been performing ever since.
This just truly completely shattered the limits of what we thought was possible with open-source models -- or any type of model really.
1. Not the same "1 million token context"...
Don't let AI companies fool you with their loud claims of 1 million token context.
Not all 1 million token contexts are remotely the same -- not even close.
Yes they can all process massive codebases, research archives, books, or long-running projects.
But they vastly differ in the quality of processing all that massive data, how much they can actually make sense of, how much they comprehend the interconnectedness of all the data.
And speed. A big, big one.
Most AI models become painfully slow and expensive when dealing with that much information.
M3 uses an innovative new approach called MiniMax Sparse Attention (MSA) that allows it to focus on the important parts instead of wasting resources on everything at once.
This allows M3 to:
Read huge amounts of information more than 9x faster
Generate responses more than 15x faster
Use a fraction of the computing power normally required
The giant context window is no longer just for fancy -- it actually becomes a beast in the real world.
And those models that still use the slower methods of parsing large token contexts will get absolutely left in the dust.
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