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Data

Data as of October 2, 2026 · How the score is built

CurrentWeight access pendingReasoning

Released Jul 16, 20261.05M context

Kimi K3

Decision readingKimi K3 scores 72.1 out of 100 and ranks #15 of 212. This profile shows 52 source-displayable benchmark rows; its strongest eligible category is Multimodal & Grounded at #1. API pricing is $3 input and $15 output per million tokens, with cached input at $0.3.

Released Jul 16, 2026 — see all recent releases

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

72.1/100

field median 52.2#15 of 212 ranked models

Public

#15of 212

Verified #8 of 74

Price

$3input / $15 output

input median $0.95cached $0.30 · blended $9

Speed

34tok/s

field median 89 tok/sFirst token 63.81 s

Context

1.05Mtokens

field median 256,000Reported for this model; direct source link not stored

Strongest published evidence

Multimodal & Grounded ranks #1. Particularly strong for screenshots, documents, charts, and grounded multimodal workflows.

Validate before choosing

52 published rows leave some tracked benchmark slots empty. Knowledge is its lowest eligible category at #18.

Source-linked · 52 displayable benchmark rows

Follow model changes

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #8 of 119Percentile 94thWeight 22%12 benchmarksVerified
68.1
CodingRank #18 of 144Percentile 88thWeight 20%14 benchmarksVerified
61.4
ReasoningRank #18 of 27Percentile 35thWeight 17%2 benchmarksVerified
65.8
MultimodalRank #1 of 49Percentile 100thWeight 12%13 benchmarksVerified
89.4
KnowledgeRank #18 of 171Percentile 90thWeight 12%6 benchmarksVerified
67.9
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingWeight 5%1 benchmarkVerified
Score pending
MathWeight 5%0 benchmarksNot measured
Not measured

52 of 645 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. Agentic12/12 verified
  2. Coding14/14 verified
  3. Reasoning2/2 verified
  4. Multimodal13/13 verified
  5. Knowledge6/6 verified
  6. MultilingualNot measured
  7. Inst. Following1/1 verified
  8. MathNot measured
Verified sourceProvisionalNot measured

Capability shape

Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.

Kimi K3 category percentile values

  • Agentic94th percentile
  • Coding88th percentile
  • Reasoning35th percentile
  • Multimodal100th percentile
  • Knowledge90th percentile
  • MultilingualNot eligible
  • Instruction followingNot eligible
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#8/119
  2. Coding#18/144
  3. Reasoning#18/27
  4. Multimodal#1/49
  5. Knowledge#18/171
  6. MultilingualNot ranked
  7. Inst. FollowingNot ranked
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding14 rows
Coding benchmark values, best verified comparison, weight, and source status
FrontierSWE v2Score25.9%Versus best verified row

Best verified: GPT-6 Astra · 65.5%

Gap39.6 behindWeight8% ref. weight
LiveCodeBench (Vals)LiveCodeBench, Vals AI runScore87.2%Versus best verified row

Best verified: Claude Fable 5.1 · 90.5%

Gap3.3 behindWeight8% ref. weight
VulcanBench v3Score73.7%Versus best verified row

Best verified: Grok 4.5 · 89.9%

Gap16.2 behindWeight3% ref. weight
DeepSWEScore67.5%Versus best verified row

Best verified: Gemini 4 Argon · 77.9%

Gap10.4 behindWeightDisplay only
CursorBench 3.2Score60.8%Versus best verified row

Best verified: Claude Fable 5.1 · 73.4%

Gap12.6 behindWeightDisplay only
FrontierSWEScore81.2%Versus best verified row

Best verified: Kimi K3 · 81.2%

GapBest verifiedWeightDisplay only
ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch?Score77.8%Versus best verified row

Best verified: Claude Opus 5 · 93.0%

Gap15.2 behindWeightDisplay only
Kimi Code Bench v2Score72.9%Versus best verified row

Best verified: Kimi K3 · 72.9%

GapBest verifiedWeightDisplay only
sweMarathonScore42%Versus best verified row

Best verified: Step 5 Preview · 72.7%

Gap30.7 behindWeightDisplay only
PostTrain BenchScore36.6%Versus best verified row

Best verified: GLM-5.3 · 39.8%

Gap3.2 behindWeightDisplay only
MLS-Bench LiteScore48.3%Versus best verified row

Best verified: Kimi K3 · 48.3%

GapBest verifiedWeightDisplay only
OpenHarmony BenchOpenHarmony Bench v1.0Score57.3%Versus best verified row

Best verified: Qwen3.8 Max · 60.8%

Gap3.5 behindWeightDisplay only
SWE-bench (Vals)SWE-bench, Vals AI runScore93.4%Versus best verified row

Best verified: Claude Opus 5 · 97.0%

Gap3.6 behindWeightDisplay only
PostTrainBench v1.1Score32.0%Versus best verified row

Best verified: Claude Opus 5.5 · 49.3%

Gap17.3 behindWeightDisplay only
Agentic12 rows
Agentic benchmark values, best verified comparison, weight, and source status
Terminal-Bench 2.1Score88.3%Versus best verified row

Best verified: SWE-2 · 92.8%

Gap4.5 behindWeight8% ref. weight
BrowseCompScore91.2%Versus best verified row

Best verified: Atria Dawn Preview · 92.5%

Gap1.3 behindWeight8% ref. weight
Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI runScore80.9%Versus best verified row

Best verified: GPT-6 Astra · 87.3%

Gap6.4 behindWeight3% ref. weight
AutomationBenchScore30.8%Versus best verified row

Best verified: DeepSeek V4.1 Flash · 54.8%

Gap24 behindWeightDisplay only
JobBenchScore52.9%Versus best verified row

Best verified: Muse Spark 1.3 · 64.9%

Gap12 behindWeightDisplay only
MCP AtlasScore84.2%Versus best verified row

Best verified: Muse Spark 1.1 · 88.1%

Gap3.9 behindWeightDisplay only
Toolathlon-VerifiedScore73.2%Versus best verified row

Best verified: Claude Opus 5 · 80.6%

Gap7.4 behindWeightDisplay only
DeepSearchQAScore95.0%Versus best verified row

Best verified: Atria Dawn Preview · 96.0%

Gap1 behindWeightDisplay only
APEX-AgentsScore37.6%Versus best verified row

Best verified: Grok 4.6 · 57.5%

Gap19.9 behindWeightDisplay only
SpreadsheetBench 2Score34.8%Versus best verified row

Best verified: Kimi K3 · 34.8%

GapBest verifiedWeightDisplay only
DECK-BenchDECK-Bench (Internal)Score73.5%Versus best verified row

Best verified: Kimi K3 · 73.5%

GapBest verifiedWeightDisplay only
ApprenticeBenchApprenticeBench: end-to-end computer use, continual learning, and long-horizon agency on a real accounts-payable jobScore18%Versus best verified row

Best verified: Claude Fable 5.1 · 72%

Gap54 behindWeightDisplay only
Reasoning2 rows
Reasoning benchmark values, best verified comparison, weight, and source status
ARC-AGI-2Abstraction and Reasoning Corpus for AGI v2Score60.4%Versus best verified row

Best verified: GPT-6 Astra · 95%

Gap34.6 behindWeightWeighted 25%
ARC-AGI-1ARC-AGI-1 Semi-Private EvaluationScore94.50%Versus best verified row

Best verified: GPT-6 Astra · 98.50%

Gap4 behindWeightDisplay only
Multimodal13 rows
Multimodal benchmark values, best verified comparison, weight, and source status
MMMU-ProMassive Multi-discipline Multimodal Understanding ProScore81.6%Versus best verified row

Best verified: Gemini 3.5 Flash · 83.6%

Gap2 behindWeightWeighted 40%
OfficeQA ProScore63.3%Versus best verified row

Best verified: Claude Opus 5.5 · 67.7%

Gap4.4 behindWeightWeighted 25%
CharXivCharXiv ReasoningScore91.3%Versus best verified row

Best verified: Qwen3.8 Max · 93.5%

Gap2.2 behindWeightWeighted 20%
MMMU-Pro w/ PythonMMMU-Pro with PythonScore83.4%Versus best verified row

Best verified: GPT-5.6 Sol · 84.6%

Gap1.2 behindWeightDisplay only
CharXiv w/o toolsCharXiv Reasoning without toolsScore84.8%Versus best verified row

Best verified: Claude Mythos 5 · 88.9%

Gap4.1 behindWeightDisplay only
MathVisionScore94.3%Versus best verified row

Best verified: Qwen3.8 Max · 95.2%

Gap0.9 behindWeightDisplay only
MathVision w/ PythonMathVision with PythonScore97.8%Versus best verified row

Best verified: Kimi K3 · 97.8%

GapBest verifiedWeightDisplay only
BabyVision w/ PythonBabyVision with PythonScore85.7%Versus best verified row

Best verified: Qwen3.8 Max · 91.3%

Gap5.6 behindWeightDisplay only
ZeroBenchScore23.0%Versus best verified row

Best verified: Muse Spark · 33.0%

Gap10 behindWeightDisplay only
ZeroBench w/ PythonZeroBench_main with PythonScore41.0%Versus best verified row

Best verified: Qwen3.8 Max · 49.0%

Gap8 behindWeightDisplay only
WorldVQA ForceAnswerScore51.0%Versus best verified row

Best verified: Kimi K3 · 51.0%

GapBest verifiedWeightDisplay only
OmniDocBenchScore91.1%Versus best verified row

Best verified: Kimi K3 · 91.1%

GapBest verifiedWeightDisplay only
PerceptionBenchPerceptionBench (Internal)Score58.5%Versus best verified row

Best verified: Qwen3.8 Max · 63.5%

Gap5 behindWeightDisplay only
Knowledge6 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLEHumanity's Last ExamScore56%Versus best verified row

Best verified: Claude Fable 5.1 · 65%

Gap9 behindWeight44% ref. weight
MMLU-Pro (Vals)MMLU-Pro, Vals AI runScore88.0%Versus best verified row

Best verified: Claude Fable 5.1 · 92.4%

Gap4.4 behindWeight6% ref. weight
GPQAGraduate-Level Google-Proof Q&AScore93.5%Versus best verified row

Best verified: GPT-6 Astra · 96%

Gap2.5 behindWeight3% ref. weight
GPQA Diamond (Vals)GPQA Diamond, Vals AI runScore92.9%Versus best verified row

Best verified: Gemini 3.1 Pro · 95.5%

Gap2.6 behindWeight2% ref. weight
HLE w/o toolsHumanity's Last Exam without toolsScore43.5%Versus best verified row

Best verified: Claude Opus 5.5 · 64.4%

Gap20.9 behindWeightDisplay only
GPQA-DGPQA DiamondScore93.5%Versus best verified row

Best verified: GPT-6 Astra · 96.0%

Gap2.5 behindWeightDisplay only
Inst. Following1 row
Inst. Following benchmark values, best verified comparison, weight, and source status
Gray Swan IPI (15 attempts)Gray Swan Indirect Prompt Injection, attack success at 15 attemptsScore52.7%Versus best verified row

Best verified: Gemini 4 Argon · 0.7%

Gap52 behindWeightDisplay only
External signals4 rows
External signals benchmark values, best verified comparison, weight, and source status
ExploitBenchExploitBench v8-benchScore32%Versus best verified row

Best verified: GPT-6 Astra · 100%

Gap68 behindWeightDisplay only
ACE solvedACE Cyber Range Challenges SolvedScore0%Versus best verified row

Best verified: Kimi K3 · 0%

GapBest verifiedWeightDisplay only
The Last Ones stepsThe Last Ones Average ProgressScore17%Versus best verified row

Best verified: Kimi K3 · 17%

GapBest verifiedWeightDisplay only
The Last Ones completionThe Last Ones Cyber Range Completion RateScore10%Versus best verified row

Best verified: GPT-5.6 Sol · 70%

Gap60 behindWeightDisplay only

What it costs to get this score

Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.

Current modelExplore all models

Kimi K3 · 72.1 score · $9 blended per million tokens

The chart opens on the current model. Scroll horizontally to inspect the full price axis.

30405060708090100$0.10$0.50$1$5$10$25$50$100↘ frontierKimi K3

Horizontal: blended price per million tokens, log scale · Vertical: public score

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Feb 1, 2026

    Kimi K2.5

    Score 53.7 · $0.6 / $3

  2. Apr 20, 2026

    Kimi K2.6

    Score 60.2 · $0.95 / $4

  3. Jul 16, 2026 · you are here

    Kimi K3

    Score 72.1 · $3 / $15

Base entry

Radar

Kimi K3 release history

Full release history

Radar confirmed these at the source. Use Kimi K3 in your work? Explore Radar to follow supported changes and choose your alerts.

Radar

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
Not published
Context window
1.05M
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
Not sourced yet
Output modalities
Not sourced yet
Parameters
Not sourced yet
Availability
Not sourced yet
Cloud regions
Not tracked yet
Lifecycle
Current
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Published at $0.30 per million cached input tokens
Self-host
Weight availability is pending
Rate limits
Not tracked yet

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

Kimi K3 ranks #15 of 212 on the public leaderboard with a score of 72.14/100. Its source-verified position is #8 of 74.

Kimi K3 has no verified publication yet for weight access. Its 1.05M context window is documented separately from that pending weight status. The profile records its reasoning mode as reasoning.

Its explicit predecessor is Kimi K2.6. 52 of 645 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Multimodal & Grounded at #1, while its lowest eligible position is Knowledge at #18. particularly strong for screenshots, documents, charts, and grounded multimodal workflows.

Last updated October 2, 2026. Runtime fields remain blank until a sourced snapshot exists.

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Questions

How does Kimi K3 perform overall in AI benchmarks?

Kimi K3 ranks #15 out of 212 models on the public BenchAlign leaderboard, with a score of 72.14/100. Its evidence status is Supported, and this profile shows 52 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Kimi K3 good for knowledge and understanding?

Kimi K3 ranks #18 out of 171 eligible models for knowledge and understanding, with a public category score of 67.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Kimi K3 good for coding and programming?

Kimi K3 ranks #18 out of 144 eligible models for coding and programming, with a public category score of 61.4/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Kimi K3 good for reasoning and logic?

Kimi K3 ranks #18 out of 27 eligible models for reasoning and logic, with a public category score of 65.8/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Kimi K3 good for agentic tool use and computer tasks?

Kimi K3 ranks #8 out of 119 eligible models for agentic tool use and computer tasks, with a public category score of 68.1/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Kimi K3 good for multimodal and grounded tasks?

Kimi K3 ranks #1 out of 49 eligible models for multimodal and grounded tasks, with a public category score of 89.4/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Kimi K3 good for instruction following?

Kimi K3 has source-displayable benchmark coverage for instruction following, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Does Kimi K3 have full benchmark coverage on BenchLM?

No. Kimi K3 currently has 79 source-displayable rows across 645 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of Kimi K3?

Kimi K3 has a reported context window of 1.05M in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.

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Compare Kimi K3 with every tracked model782 comparisons