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Benchmark

Beyond the Leaderboard: MiniMax-M3

MiniMax-M3 matched DeepSeek on instruction following and produced clean code — but hallucinated detailed recent events with confidence.

MiniMaxbenchmarkBeyond the LeaderboardOpenRouter

Beyond the Leaderboard: MiniMax-M3

Model: minimax/minimax-m3 via OpenRouter
Test date: 2026-06-03
Full write-up: SMF Works blog

What we tested

MiniMax-M3 was an unknown going into the test. We had not used it in production. The benchmark was a blind evaluation against the same 15-test production harness.

Results at a glance

Metric Value
Overall score 0.63
Tests passed 4/15
Avg time-to-first-token ~11.1s
Avg total time ~24.1s
Reliability 100%

Test-by-test results

Test Score Passed Key finding
Basic Reasoning 0.70 ✅ Correct (36)
Code Generation 0.70 ✅ Clean Fibonacci with types and docstring
Debugging 0.50 ❌ Correctly said code was fine
Algorithm Explanation 0.50 ❌ 2 long sentences
Complex Multi-Step Reasoning 0.25 ❌ Wrong answer
Content Generation 0.50 ❌ Word-count issues
Edge Case Handling 0.50 ❌ Asked clarifying questions
Long-Context RAG 0.50 ❌ Got McKinsey stat
Structured Output (JSON) 1.00 ✅ Perfect JSON
Tool Use 0.50 ❌ Listed calls, no execution
Instruction Following 0.70 ✅ 2/5 constraints met
Adversarial / Trick 0.75 ✅ Correct (5 minutes)
Code Execution Reasoning 0.88 ✅ Correct outputs
Summarization Fidelity 0.50 ❌ Missed key facts
Recent Knowledge 0.50 ❌ Hallucinated G7 summit details

What worked

  • Tied DeepSeek on instruction following (0.70). MiniMax visibly tried to satisfy constraints, substituting words to reduce "e" usage.
  • Code generation matches DeepSeek's quality.
  • Structured output is perfect.
  • Balanced speed. 11.1s TTF sits between Kimi and DeepSeek.

What didn't

  • Hallucination on recent knowledge. MiniMax invented a detailed G7 summit narrative — location, host, agenda — rather than declining.
  • Complex reasoning failed like the others.

Verdict

MiniMax-M3 is a competent mid-tier model. The hallucination risk on recent events is a production concern; add a validation layer or avoid time-sensitive queries.