Inference360
Moonshot AI

Kimi K2 Thinking

Kimi K2 Thinking is a model from Moonshot AI. 11 benchmarks count toward its score, in 5 categories.

availableShows if the model has enough results for an index.
IndexOverall score out of 100.48.5 ±6.9
CoverageShare of the index weight with results.80%
SpeedOutput tokens per second.34/s
Input / 1MUS dollars per 1M input tokens.$0.6
Output / 1MUS dollars per 1M output tokens.$2.5
ContextMaximum tokens in one request.262K
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.
47.3
CodingCode writing and repair.
45.1
ReasoningLogic problems and puzzles.
49.4
MultimodalTasks with images and text.
N/A
KnowledgeFacts and expert knowledge.
50.8
MultilingualTasks in many languages.
N/A
InstructionTasks with strict rules in the prompt.
N/A
MathMath problems.
51.4

Results

11 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.
MGSMMultilingual90.1%——9 Jan 2026Vals AI
AIMEMath85.4%53.5—16 Apr 2026Vals AI
GPQA diamondKnowledge84.2%56.0——Epoch AI
OTIS Mock AIME 2024-2025Math83.1%58.0——Epoch AI
MMLU ProKnowledge81.1%48.2—1 Sept 2026Vals AI
GPQA DiamondKnowledge78.5%50.7—1 Sept 2026Vals AI
SWE-bench VerifiedCoding63.4%48.4mini-SWE-agent26 Feb 2026SWE-bench team
SWE-bench VerifiedCoding63.4%48.4mini-SWE-agent1 Sept 2026SWE-bench team
LiveCodeBenchCoding63.1%41.7—1 Sept 2026Vals AI
SWE-benchCoding60.2%45.8—1 Sept 2026Vals AI
Terminal-Bench 1.0Agentic40.0%45.4—12 Jan 2026Vals AI
Terminal-Bench 2.0Agentic37.1%49.1—4 Jun 2026Vals AI
FrontierMath-2025-02-28-PrivateMath21.4%50.6——Epoch AI
Chess PuzzlesReasoning20.0%49.4——Epoch AI
FrontierMath-Tier-4-2025-07-01-PrivateMath0.0%43.4——Epoch AI

11 benchmarks count, from 14 of 15 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 AIEpoch AI, collected directlyCC BY — free to use and redistribute with attributionSWE-bench team, collected directlyNo licence stated for the leaderboard. The harness repo is MIT

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