LLM Reference

MiniMax M3

minimax-m3

Teased - not yet releasedResearched 1d ago

Last refreshed 2026-05-26. Next refresh: weekly.

upcoming

MiniMax M3 is a watchlist entry, not a production pick; wait for published weights, API access, pricing, context, and benchmarks before planning a migration.

Decision context: pre-release watchlist status, 0 tracked provider routes, and research from 2026-05-26.

Use it for

  • Teams monitoring MiniMax M3's release
  • MiniMax M2 users deciding whether to wait
  • Architecture watchlists for long-context efficiency

Do not use it for

  • Production launches that need model access today
  • Cost estimates that need sourced token pricing
  • Benchmark-led selections that need independent scores

Cheapest output

-

No tracked output price

Provider routes

0

No provider route in seed

Quality / dollar

Unknown

No task benchmark coverage yet

Freshness

2026-05-26

Researched 1d ago

fresh

Top use-case fit

No primary decision-task fit is mapped for this model yet.

Provider price ladder

No tracked provider token pricing is available for this model yet.

Benchmark peer barsfor Coding

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.

About

MiniMax M3 is an upcoming model from MiniMax, teased in May 2026 but not yet released. MiniMax highlighted MiniMax Sparse Attention, a GQA-based sparse attention mechanism using a two-stage block-selection approach, and claimed 9.7x faster prefill plus 15.6x faster decoding versus MiniMax M2 at 1M-token context while preserving output quality. No weights, API route, benchmarks, pricing, parameter count, license, or confirmed context-window spec has been officially published.

Capabilities

No model capability flags are currently sourced.

Rankings

Specifications

AvailabilityTeased - not yet released
ArchitectureMiniMax Sparse Attention
Specializationgeneral

Created by

Developing AI for gaming and entertainment.

Minhang, Shanghai, China
Founded 2021
Website