All models

Moonshot AIChina· released Jul 2026· open weights

Kimi K3

Ranked #8, 20.4% behind the frontier on average.

Moonshot AI, China. One of 5 models from this lab on the Index.

Third-party publishedMedium confidence (7+ comparable tests, 3+ Index categories)
Theo

Available in Theo as Theo Open Max

Theo orchestrates it for the steps it does best and always shows which engine answered.

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Snapshot September 8, 2026

OpenCharts Index

79.6

Ranked #8 (6 to 10) of 36 · 20.4% behind the frontier on average · 18 comparable tests · 3 counting categories

Drop any single test and the Index lands between 77.2 and 83.5, anywhere from #6 to #10. Neighbours inside that range are ties.

HARD SET

Needs more results (3 of 8 so far)

Averaging 60.2 on the 3 it has; the score opens at 4 of 8.

Distance to today's frontier on the hardest tests. Not a measure of intelligence.

What it's known for

Kimi K3, in 18 results.

Strongest in coding (83.0) and reasoning (80.5). It trails the frontier most in math, 24.7% behind on average. No comparable results yet in multimodal and long context. Between 20% and 25% behind the best published results, on average. Drop any single test and it would sit anywhere from #6 to #10.

Strongest category

Coding

Writing, fixing and shipping real code, judged by tests or users.

83.0

Mean of 5 of the category's 7 comparable tests. Counts toward the Index.

Best single result

Mock AIME 2024–2025

Solve competition mathematics problems that have a single exact integer answer.

97.2%

97.2% of the best (100.0%) · #15 of 78.

Olympiad-style problems need long, careful chains of reasoning, and there is no partial credit.

Where it trails

FrontierMath Tier 4

Solve the hardest FrontierMath tier: problems that take expert mathematicians days.

39.0%

60.0% behind the best published result (97.6%) · #16 of 51.

The deepest end of the set. Progress here signals genuinely new capability.

Not measured yet

No comparable result yet in these 2 categories. A blank is a blank, never a zero, and it does not lower the Index.

  • Multimodal
  • Long context

Covered, but not averaged into the Index:

  • Knowledgesingle-test category, shown beside the Index · 66.9
  • Agentic2 of 8 tests · needs 4 · mean 79.0
  • Human preferencesingle-test category, shown beside the Index · 94.7
Every score, with its source

See it at work

What Kimi K3 was asked to do, and how it did.

Every test it has taken, by category, with the kind of task it faced, who produced the number and where the result landed against the best published one. The examples are original and illustrative, never items from the datasets themselves.

Human preference · mean 94.7 across 1 comparable test · a single-test category, shown beside the Index and never averaged into it

Text ArenaLeaderboard

Answer the same prompt as a rival model; real users vote blind on which answer they prefer.

1,489

47% expected win rate against the board leader (1,507)
#10 of 92

max · board 2026-09-02

Source: Arena

Every result is read against the best published one on its test: percent scores as a share of the best above chance, Arena ratings as the expected win rate against the board leader, open-ended values on a log scale. Sitting a harder exam never lowers a model. Every number links to the publisher that produced it.

Head to head

Kimi K3 against whoever you pick.

Choose a rival. Every counted test both have taken appears side by side as a share of the best published result on that test, with the category means above. A win is a higher share; a gap under 2 points is a tie, because one item on a 45-problem exam is 2.2 points and publishers' own standard errors are of that order.

Kimi K3

#8·Index 79.6B

1 : 13

wins · 0 ties · 14 shared

GPT-6 Astra

#1·Index 99.0A+

GPT-6 Astra comes out ahead on 13 of the 14 tests both have taken.

Category means

  • Reasoning

    80.5
    99.6
  • Knowledge

    66.9
    100.0
  • Coding

    83.0
    97.7
  • Math

    75.3
    99.8
  • Agentic

    79.0
    98.5
  • Human preference

    94.7

Shared tests · biggest gaps first

Bars are distances to the best published result on each test (percent scores above chance, Arena ratings as win rate against the leader, open-ended values on a log scale). Raw values as the publishers report them.

Open GPT-6 Astra

Scores

Every test, every source

The best published run per benchmark, the raw value as the publisher reports it, who produced the number, how close it comes to the best published result on that test, and where the model sits among every model scored on it. Percent scores are read above chance, Arena ratings as a win rate against the board leader, open-ended values on a log scale. A test with too few models to compare against is shown but not counted.

Category means

  • Reasoning80.5 · 5/6
  • Knowledgebeside66.9 · 1/1
  • Coding83.0 · 5/7
  • Math75.3 · 4/5
  • Agentic79.0 · 2/8
  • Multimodal
  • Human preferencebeside94.7 · 1/1
  • Long context

Mean · tests taken of the category's comparable tests. A faded category either rests on fewer than half of them or is a single-test category (marked “beside”), which is shown next to the Index and never averaged into it.

GPQA DiamondEpoch-runReasoning

93.1%

96.3% of the best (95.8%), above chance
86th percentile of 78 · n = 198

max

Source: Epoch AI — AI Benchmarking Hub
ARC-AGI-2LeaderboardReasoning

60.4%

63.6% of the best (95.0%)
54th percentile of 51 · n = 120

max

Source: Epoch AI — AI Benchmarking Hub
ARC-AGI-1LeaderboardReasoning

94.5%

95.9% of the best (98.5%)
76th percentile of 51 · n = 100

max

Source: Epoch AI — AI Benchmarking Hub
SimpleBenchLeaderboardReasoning

60.7%

74.1% of the best (81.9%)
51th percentile of 46

max

Source: Epoch AI — AI Benchmarking Hub
CritPtLeaderboardReasoning

23.4%

72.4% of the best (32.3%)
86th percentile of 78

max

Source: Epoch AI — AI Benchmarking Hub
SimpleQA VerifiedEpoch-runKnowledge

50.6%

66.9% of the best (75.6%)
68th percentile of 57 · n = 1,000

max

Source: Epoch AI — AI Benchmarking Hub
SciCodeLeaderboardCoding

58.7%

94.6% of the best (62.0%)
96th percentile of 73 · n = 338

Source: Epoch AI — AI Benchmarking Hub
WeirdMLLeaderboardCoding

82.6%

88.9% of the best (92.9%)
88th percentile of 69

max

Source: Epoch AI — AI Benchmarking Hub
FrontierCodeLeaderboardCoding

44.2%

82.6% of the best (53.5%)
73th percentile of 27

harness: mini-swe-agent · reasoning effort: none

Source: Epoch AI — AI Benchmarking Hub
CursorBenchLeaderboardCoding

60.8%

82.8% of the best (73.4%)
40th percentile of 21

max · reasoning level: Max

Source: Epoch AI — AI Benchmarking Hub
Code Arena (WebDev)LeaderboardCoding

1,674

33% expected win rate against the board leader (1,797)
95th percentile of 86

max · board 2026-09-05

Source: Arena (LMArena) — Leaderboard Dataset

97.2%

97.2% of the best (100.0%)
81th percentile of 78 · n = 45

max

Source: Epoch AI — AI Benchmarking Hub

72.2%

77.0% of the best (93.7%)
77th percentile of 61 · n = 290

max

Source: Epoch AI — AI Benchmarking Hub
FrontierMath Tier 4Epoch-runMath

39.0%

40.0% of the best (97.6%)
70th percentile of 51 · n = 48

max

Source: Epoch AI — AI Benchmarking Hub
ProofBenchLeaderboardMath

87.0%

87.0% of the best (100.0%)
93th percentile of 61

Source: Epoch AI — AI Benchmarking Hub
APEX-AgentsLeaderboardAgentic

39.3%

82.9% of the best (47.4%)
81th percentile of 49

Source: Epoch AI — AI Benchmarking Hub
Vending-Bench 2LeaderboardAgentic

$5,165

75.1% of the best ($11,182) on a log scale
60th percentile of 53

Source: Epoch AI — AI Benchmarking Hub
Text ArenaLeaderboardHuman preference

1,489

47% expected win rate against the board leader (1,507)
90th percentile of 92

max · board 2026-09-02

Source: Arena (LMArena) — Leaderboard Dataset

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