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All content about MiniMax, organized for fast scanning.
MiniMax has introduced its M3 model, featuring open weights and the ability to handle up to 1 million context tokens through Sparse Attention, along with benchmark results and pricing tiers. Additionally, a recent comparison of code audit costs between MiniMax M3 and another model revealed significant differences in budget allocation and coverage, indicating a potential shift in how teams approach AI code reviews.
Kilo Blog ran the same TypeScript code audit across Claude Opus 4.8 settings and MiniMax M3, tracking spend, speed, and issues found. The results highlight a sharp cost-vs-coverage tradeoff that may reshape how teams budget AI reviews.
MiniMax has just rolled out M3, touting open weights, agentic coding chops, and up to 1M context via Sparse Attention. The company shared benchmark results and pricing tiers, and says weights plus a tech report should land in about 10 days.