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Reviews and evidence

MiniMax M3 · Media / benchmark · Independent measurement

MiniMax M3: Google supplement: Artificial Analysis's public metrics for MiniMax-M3

This Google supplement points to public Artificial Analysis metrics for MiniMax-M3; quality, speed, and cost must be read separately within the page version and time window, without inventing provider, tier, sample, or hidden fields.

Unverified: the original source could not be rechecked. Historical figures below are not current verified results.

Media / benchmarkIndependent measurementEdited 2026-09-20

Test conditions

Platform
Public Artificial Analysis metrics; provider and harness follow the page
Version/tier
Version, reasoning tier, and time window require a fresh check
Metrics
Quality, speed, and cost only as shown; unknown values stay unknown
Sample
Aggregation method and sample configuration incomplete

Key data and applicable tasks

Summary

Google results show that Artificial Analysis's MiniMax-M3 page compares model quality, price, output speed, and latency. A Google snippet gives an Intelligence Index of about 45 and a Coding Index of about 58.6; different result cards also showed 55 as an older or otherwise different snapshot, so the scores must be understood together with the page date.

Results visible in Google

  • MiniMax-M3 - Intelligence, Performance & Price Analysis: used to compare quality, price, performance, tokens per second, and time to first token.

  • Metrics cited in Google's AI Overview: Intelligence Index 45; output speed of approximately 93.5–110 tokens/s; time-to-first-token of approximately 1.3–1.4 seconds; a context window of 1,000,000 tokens; and standard pricing of approximately $0.30 per million input tokens / $1.20 per million output tokens.

  • The OpenRouter result card showed an Artificial Analysis Intelligence Index of 45.4, higher than 69% of its comparison models; the Coding Index was 58.6.

  • Another Artificial Analysis article snippet in the Google results said that MiniMax-M3 scored 55 on 2026-06-08 and called it the leading open-weights model; this conflicts with the 45 on another result card and indicates that the data snapshot or metric version changed.

Assessment

  • As a supplement, M3's public positioning is as a cost-effective model with a long context window and relatively strong coding/Agent capabilities.

  • Public metrics differ across time snapshots; actual selection should record the access date, page version, and provider.

  • This material should not supersede real-workflow evidence from X/Reddit: public leaderboards measure standardized metrics, while community posts measure harnesses, quotas, and task experience.

Original text (Google-visible snippets)

Analysis of MiniMax's MiniMax-M3 and comparison to other AI models across key metrics including quality, price, performa… This is a necessary excerpt; read the original source for full context.

Limitations

The target page could not be accessed directly in this collection, and Google snippets are not the complete article text; the score conflict could not be verified on the page itself. This file is for indexing and supplementary context only, not a final quantitative conclusion.

What this supports

  • Supports reading MiniMax-M3 metrics within the cited Artificial Analysis release.

What this does not support

  • Does not fill undisclosed providers, samples, or historical values into a current trend.

Method, limits, and reproduction

The figures, task set, reasoning tier, and client conditions apply only to the listed source and collection snapshot. Different versions, harnesses, or providers must not be compared directly; undisclosed parameters remain unknown.

For a reproduction, fix the model version, provider or client, reasoning tier, tools, task-set version, sample count, and collection date, and record failures, retries, and human corrections. Full steps are in the source notes below.

Original source

Artificial Analysis; reached through Google search results · Artificial Analysis · Original publication date Unknown · Site edit date 2026-09-20

Open original source

MiniMax M3

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Read the full analysis

Overview · English

MiniMax M3: 1M Context, Coding Power, and the Quota Catch

A source-led MiniMax M3 overview covering M2.7 changes, API and Token Plan access, provider costs, workload fit, Tabbit boundaries, and unknowns.

Related reviews

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