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MiniMax · budget

Is MiniMax M3 good?

MiniMax M3 places top-3 in 3 of 22 task areas we tested. It's strongest at data & analytics and weakest at summarization & meeting notes. It's a budget-friendly option ($1.5/1M tokens).

Top-3 finishes
22/22
Task areas tested
$1.5
Per 1M tokens
Slow
Typical speed

Strengths

Clarity Concision Specificity Usefulness Structure Tone

Weak spots

Practical sequencing Visual design Timing accuracy Food quality No wrapper text Policy grounding

How MiniMax M3 ranks, task by task

Rank is the position in each field; Rating is the absolute quality bar. A model can be rated "Excellent" yet sit mid-table when the whole field is strong — and vice-versa.

Task area Rank
Data & Analytics #1 of 107
Sales #2 of 107
Product & Project Management #3 of 107
Investor & Pitch #9 of 63
Frontend & Landing Pages #17 of 106
AI Strategy #21 of 123
Landing Pages #17 of 69
Presentations & Decks #27 of 107
Content & Brand #34 of 121
Research & Competitive Analysis #31 of 107
Legal & HR #33 of 107
Executive Assistant #36 of 109
Coding #41 of 112
Training & Education #41 of 107
Creative & Comedy #53 of 107
Translation & Localization #53 of 107
Structured Output #60 of 110
Chef / Home Cooking #68 of 123
RAG, Safety & Grounding #64 of 110
Knowledge & Docs #64 of 107
Customer Support #74 of 110
Summarization & Meeting Notes #74 of 107

Industry benchmarks

Standardized third-party scores, shown for context — these are independent of our real-task tests.

Headline vs. real-world

Source: Artificial Analysis (artificialanalysis.ai) via OpenRouter (openrouter.ai/rankings). (2026-07-02) · Source: Design Arena (www.designarena.ai) via OpenRouter (openrouter.ai/rankings). (2026-07-02)

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Frequently asked

Is MiniMax M3 any good?

MiniMax M3 places top-3 in 3 of 22 task areas we benchmarked. It performs best at Data & Analytics.

What is MiniMax M3 best at?

Its strongest task areas are Data & Analytics, Sales, Product & Project Management.

Is there a cheaper alternative to MiniMax M3?

DeepSeek V4 Pro is 13% cheaper and stays competitive on quality across our benchmarks.

How we test & rank

Each model is scored on real tasks across 22 task areas by an LLM judge with deterministic checks. "Percentile" is this model's standing within each area's field; the cross-area figures are rank-based so quality and Elo scores are never mixed.

This page is Spring Prompt, running

We just did this for every model. Do it for your prompt.

The rankings above come from running real tasks through real models and scoring every output. Spring Prompt is that same engine — pointed at your prompt, your test cases, and your definition of good.

  • Generate test cases from your prompt — no eval set required to start.
  • Compare models side by side with quality, cost and latency in one matrix.
  • Optimise the winner until the scores say it's ready to ship.
Experiment · Cold outreach email

Prompt × model results

12 test cases · 3 evals
Claude Opus
GPT-5
Gemini
v1
7.1
6.8
7.4
v2
8.3
7.9
8.0
v3
9.2
8.6
8.4
Best combo: v3 × Claude Opus
9.2 quality · $0.004/run · 1.8s