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aiqbench

Moonshot · model passport

Kimi K2 5 Thinking

kimi-k2-5-thinking
  • Open weights
  • Modified MIT licence
  • Released 2026-09-13(first seen on LMArena)
9/27axes covered
Overall · LMArena
1,450#70 of 396
Best percentile
83.6Coding
Cohort standing
63.2median 60.4

What the data says

Benchmarked on 9 of 27 tracked axes. Every figure below is the model's own published result on that board.

Uneven: 65.2 percentile points between its best and worst axis — 83.6 pct on Coding versus 18.4 pct on Document Arena.

  • Coding83.6 pct1,502Verify →
  • Overall82.6 pct1,450Verify →
  • Instruction following82.1 pct1,439Verify →
  • Hard prompts81.8 pct1,471Verify →
  • LiveBench80.1 pct69.1%Verify →
  • Vision Arena72 pct1,252Verify →
  • Factuality Arena58.7 pct1,445Verify →
  • WebDev Arena48.9 pct1,436Verify →
  • Document Arena18.4 pct1,436Verify →
  • Search ArenaNot benchmarked
  • Agent ArenaNot benchmarked
  • GPQA DiamondNot benchmarked
  • AIME (math)Not benchmarked
  • FrontierMathNot benchmarked
  • SimpleQA VerifiedNot benchmarked
  • ARC-AGI-2Not benchmarked
  • Humanity's Last ExamNot benchmarked
  • SimpleBenchNot benchmarked
  • BFCL v4 (function calling)Not benchmarked
  • SWE-bench Verified (live board)Not benchmarked
  • Terminal-Bench 4.0Not benchmarked
  • MMLU-Pro (Artificial Analysis)Not benchmarked
  • LiveCodeBench (Artificial Analysis)Not benchmarked
  • IFBench (Artificial Analysis)Not benchmarked
  • HHEM Hallucination (Vectara)Not benchmarked
  • SWE-bench VerifiedNot benchmarked
  • Terminal-BenchNot benchmarked

Percentiles are the model's standing within each board's own population. Axes marked "not benchmarked" have no published result for this model — that is an absence of data, not a low score.

  • kimi-k2.5-thinking stands at 63.2 (raw mean 67.6) — measured on 9 of 27 axes.

    standingtemplateVerify →

  • kimi-k2.5-thinking stands at 63.2 versus a cohort median of 60.4 across 175 models released within 180 days — above the peer median.

    cohorttemplateVerify →

Every claim is a computed fact from the current board data, phrased by a low-temperature model call and rejected by a validation gate if any number is not in the source row. How the leaderboards work →