MiniMax M2.1

MiniMax M2.1 is a model from MiniMax. 9 benchmarks count toward its score, in 4 categories.

availableShows if the model has enough results for an index.
IndexOverall score out of 100.50.0 ±8.9
CoverageShare of the index weight with results.65%
SpeedOutput tokens per second.49/s
Input / 1MUS dollars per 1M input tokens.$0.3
Output / 1MUS dollars per 1M output tokens.$1.2
ContextMaximum tokens in one request.205K
EloLMArena rating and rank.N/A

The index is a score out of 100. The ± range shows how much it can change.

CapabilitiesScore per category, out of 100.

Out of 100
AgenticMulti-step tasks with tools.
47.8
CodingCode writing and repair.
52.5
ReasoningLogic problems and puzzles.
N/A
MultimodalTasks with images and text.
N/A
KnowledgeFacts and expert knowledge.
54.2
MultilingualTasks in many languages.
N/A
InstructionTasks with strict rules in the prompt.
N/A
MathMath problems.
45.7

Results

9 counted
BenchmarkThe test name.CategoryThe capability that the test measures.ResultThe score from the publisher.IndexThis result as a score out of 100.RunThe settings of the run.DateDate of the result.Published byThe source of the result.
MATH 500Math89.0%41.39 Jan 2026Vals AI
MGSMMultilingual87.9%9 Jan 2026Vals AI
MMLU ProKnowledge87.0%57.71 Sept 2026Vals AI
LiveCodeBenchCoding81.8%58.61 Sept 2026Vals AI
GPQA DiamondKnowledge78.5%50.71 Sept 2026Vals AI
AIMEMath77.9%50.016 Apr 2026Vals AI
SWE-benchCoding74.8%57.51 Sept 2026Vals AI
Terminal-Bench 1.0Agentic41.3%46.512 Jan 2026Vals AI
Terminal-Bench 2.0Agentic37.1%49.14 Jun 2026Vals AI
IOI v1Coding2.3%41.39 Aug 2026Vals AI

9 benchmarks count, from 9 of 10 results. A grey row does not count. Too few models took that benchmark.

Sources

BenchLM benchmark aggregationUsed with attribution; per-benchmark results credited to their original authorsOpenRouter, collected directlyNo licence statedVals AI, collected directlyNo licence stated. Read from the public leaderboard and credited to Vals AI

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