Capability
74.8/100
field median 56.2
#7 of 232 ranked models
Keep up with the models you depend on. Follow price changes, retirements, and API updates.Follow the models you depend on.
Follow model changesReleased Jul 16, 2026 — see all recent releases
Data as of September 10, 2026 · How the score is built
Share or export
Multimodal & Grounded ranks #1. Particularly strong for screenshots, documents, charts, and grounded multimodal workflows.
48 published rows leave some tracked benchmark slots empty. Knowledge is its lowest eligible category at #8.
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
74.8/100
field median 56.2
#7 of 232 ranked models
Price
$3input / $15 output
input median $0.97
cached $0.30 · blended $9
Speed
38tok/s
field median 86.5 tok/s
First token 56.57 s
Context
1.05Mtokens
field median 256,000
Reported for this model; direct source link not stored
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
The dashed outline is median of 6 nearest peers.
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.
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Horizontal: blended price per million tokens, log scale · Vertical: public score
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.
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Continue the Kimi K3 decision
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #4 of 152Percentile 98thWeight 22%12 benchmarksVerified | 71.9 | #4 of 152 | 98th | 22% | 12 benchmarks | Verified |
| CodingRank #6 of 151Percentile 97thWeight 20%13 benchmarksVerified | 68.0 | #6 of 151 | 97th | 20% | 13 benchmarks | Verified |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeRank #8 of 183Percentile 96thWeight 12%6 benchmarksVerified | 72.0 | #8 of 183 | 96th | 12% | 6 benchmarks | Verified |
| MathWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalRank #1 of 48Percentile 100thWeight 12%13 benchmarksVerified | 89.5 | #1 of 48 | 100th | 12% | 13 benchmarks | Verified |
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
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.
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| LiveCodeBench (Vals)LiveCodeBench, Vals AI run | Score87.2% | Versus best verified row Best verified: Claude Fable 5.1 · 90.5% | Gap3.3 behind | WeightWeighted 15% | |
| cursorBench32 | Score60.8% | Versus best verified row Best verified: Claude Fable 5.1 · 73.4% | Gap12.6 behind | WeightWeighted 10% | Benchmark exact |
| DeepSWE | Score67.5% | Versus best verified row Best verified: Muse Spark 1.3 · 75.4% | Gap7.9 behind | WeightDisplay only | Provider exact |
| FrontierSWE | Score81.2% | Versus best verified row Best verified: Kimi K3 · 81.2% | GapBest verified | WeightDisplay only | Provider exact |
| ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch? | Score77.8% | Versus best verified row Best verified: Claude Opus 5 · 93.0% | Gap15.2 behind | WeightDisplay only | Provider exact |
| Kimi Code Bench v2 | Score72.9% | Versus best verified row Best verified: Kimi K3 · 72.9% | GapBest verified | WeightDisplay only | Provider exact |
| sweMarathon | Score42% | Versus best verified row Best verified: GLM-5.3 · 42.5% | Gap0.5 behind | WeightDisplay only | Provider exact |
| PostTrain Bench | Score36.6% | Versus best verified row Best verified: GLM-5.3 · 39.8% | Gap3.2 behind | WeightDisplay only | Provider exact |
| MLS-Bench Lite | Score48.3% | Versus best verified row Best verified: Kimi K3 · 48.3% | GapBest verified | WeightDisplay only | Provider exact |
| VulcanBench v3 | Score73.7% | Versus best verified row Best verified: Grok 4.5 · 89.9% | Gap16.2 behind | WeightDisplay only | Benchmark exact |
| OpenHarmony BenchOpenHarmony Bench v1.0 | Score57.3% | Versus best verified row Best verified: Qwen3.8 Max · 60.8% | Gap3.5 behind | WeightDisplay only | Benchmark exact |
| FrontierSWE v2 | Score25.9% | Versus best verified row Best verified: Claude Fable 5.1 · 56.3% | Gap30.4 behind | WeightDisplay only | Benchmark exact |
| SWE-bench (Vals)SWE-bench, Vals AI run | Score93.4% | Versus best verified row Best verified: Claude Opus 5 · 97.0% | Gap3.6 behind | WeightDisplay only | Verified |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.0 | Score88.3% | Versus best verified row Best verified: GPT-5.6 Sol · 91.9% | Gap3.6 behind | WeightWeighted 30% | Provider exact |
| BrowseComp | Score91.2% | Versus best verified row Best verified: GPT-5.6 Sol · 92.2% | Gap1 behind | WeightWeighted 25% | Provider exact |
| AutomationBench | Score30.8% | Versus best verified row Best verified: DeepSeek V4.1 Flash · 54.8% | Gap24 behind | WeightWeighted 10% | Provider exact |
| DeepSearchQA | Score95.0% | Versus best verified row Best verified: Claude Opus 5 · 95.0% | GapBest verified | WeightDisplay only | Provider exact |
| Toolathlon-Verified | Score73.2% | Versus best verified row Best verified: Claude Opus 5 · 80.6% | Gap7.4 behind | WeightDisplay only | Provider exact |
| MCP Atlas | Score84.2% | Versus best verified row Best verified: Muse Spark 1.1 · 88.1% | Gap3.9 behind | WeightDisplay only | Provider exact |
| JobBench | Score52.9% | Versus best verified row Best verified: Muse Spark 1.3 · 64.9% | Gap12 behind | WeightDisplay only | Provider exact |
| APEX-Agents | Score37.6% | Versus best verified row Best verified: Grok 4.6 · 57.5% | Gap19.9 behind | WeightDisplay only | Provider exact |
| SpreadsheetBench 2 | Score34.8% | Versus best verified row Best verified: Kimi K3 · 34.8% | GapBest verified | WeightDisplay only | Provider exact |
| DECK-BenchDECK-Bench (Internal) | Score73.5% | Versus best verified row Best verified: Kimi K3 · 73.5% | GapBest verified | WeightDisplay only | Provider exact |
| Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI run | Score80.9% | Versus best verified row Best verified: GPT-6 Astra · 87.3% | Gap6.4 behind | WeightDisplay only | |
| ApprenticeBenchApprenticeBench: end-to-end computer use, continual learning, and long-horizon agency on a real accounts-payable job | Score18% | Versus best verified row Best verified: Claude Fable 5.1 · 72% | Gap54 behind | WeightDisplay only | Benchmark exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| HLEHumanity's Last Exam | Score56% | Versus best verified row Best verified: Claude Fable 5.1 · 65% | Gap9 behind | WeightWeighted 35% | Provider exact |
| HLE w/o toolsHumanity's Last Exam without tools | Score43.5% | Versus best verified row Best verified: Claude Fable 5.1 · 60.9% | Gap17.4 behind | WeightWeighted 10% | Provider exact |
| MMLU-Pro (Vals)MMLU-Pro, Vals AI run | Score88.0% | Versus best verified row Best verified: Claude Fable 5.1 · 92.4% | Gap4.4 behind | WeightWeighted 10% | Verified |
| GPQAGraduate-Level Google-Proof Q&A | Score93.5% | Versus best verified row Best verified: GPT-6 Astra · 96% | Gap2.5 behind | WeightWeighted 7% | Provider exact |
| GPQA-DGPQA Diamond | Score93.5% | Versus best verified row Best verified: GPT-6 Astra · 96.0% | Gap2.5 behind | WeightDisplay only | Provider exact |
| GPQA Diamond (Vals)GPQA Diamond, Vals AI run | Score92.9% | Versus best verified row Best verified: Gemini 3.1 Pro · 95.5% | Gap2.6 behind | WeightDisplay only |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMMU-ProMassive Multi-discipline Multimodal Understanding Pro | Score81.6% | Versus best verified row Best verified: Gemini 3.5 Flash · 83.6% | Gap2 behind | WeightWeighted 40% | Provider exact |
| OfficeQA Pro | Score63.3% | Versus best verified row Best verified: Claude Opus 5 · 66.9% | Gap3.6 behind | WeightWeighted 25% | Provider exact |
| CharXivCharXiv Reasoning | Score91.3% | Versus best verified row Best verified: Qwen3.8 Max · 93.5% | Gap2.2 behind | WeightWeighted 20% | Provider exact |
| MMMU-Pro w/ PythonMMMU-Pro with Python | Score83.4% | Versus best verified row Best verified: GPT-5.6 Sol · 84.6% | Gap1.2 behind | WeightDisplay only | Provider exact |
| CharXiv w/o toolsCharXiv Reasoning without tools | Score84.8% | Versus best verified row Best verified: Claude Mythos 5 · 88.9% | Gap4.1 behind | WeightDisplay only | Provider exact |
| MathVision | Score94.3% | Versus best verified row Best verified: Qwen3.8 Max · 95.2% | Gap0.9 behind | WeightDisplay only | Provider exact |
| MathVision w/ PythonMathVision with Python | Score97.8% | Versus best verified row Best verified: Kimi K3 · 97.8% | GapBest verified | WeightDisplay only | Provider exact |
| BabyVision w/ PythonBabyVision with Python | Score85.7% | Versus best verified row Best verified: Qwen3.8 Max · 91.3% | Gap5.6 behind | WeightDisplay only | Provider exact |
| ZeroBench | Score23.0% | Versus best verified row Best verified: Muse Spark · 33.0% | Gap10 behind | WeightDisplay only | Provider exact |
| ZeroBench w/ PythonZeroBench_main with Python | Score41.0% | Versus best verified row Best verified: Qwen3.8 Max · 49.0% | Gap8 behind | WeightDisplay only | Provider exact |
| WorldVQA ForceAnswer | Score51.0% | Versus best verified row Best verified: Kimi K3 · 51.0% | GapBest verified | WeightDisplay only | Provider exact |
| OmniDocBench | Score91.1% | Versus best verified row Best verified: Kimi K3 · 91.1% | GapBest verified | WeightDisplay only | Provider exact |
| PerceptionBenchPerceptionBench (Internal) | Score58.5% | Versus best verified row Best verified: Qwen3.8 Max · 63.5% | Gap5 behind | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| ExploitBenchExploitBench v8-bench | Score32% | Versus best verified row Best verified: GPT-6 Astra · 100% | Gap68 behind | WeightDisplay only | Benchmark exact |
| ACE solvedACE Cyber Range Challenges Solved | Score0% | Versus best verified row Best verified: Kimi K3 · 0% | GapBest verified | WeightDisplay only | Benchmark exact |
| The Last Ones stepsThe Last Ones Average Progress | Score17% | Versus best verified row Best verified: Kimi K3 · 17% | GapBest verified | WeightDisplay only | Benchmark exact |
| The Last Ones completionThe Last Ones Cyber Range Completion Rate | Score10% | Versus best verified row Best verified: GPT-5.6 Sol · 70% | Gap60 behind | WeightDisplay only | Benchmark exact |
The sequence follows explicit supersedes links. A successor's displayed score stays at least 0.1 points above its predecessor; raw benchmark rows do not move. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Feb 1, 2026
Kimi K2.5Score 54.0 · $0.6 / $3
Apr 20, 2026
Kimi K2.6Score 65.4 · $0.95 / $4
Jul 16, 2026 · you are here
Kimi K3Score 74.8 · $3 / $15
Base entry
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
Kimi K3 ranks #7 of 232 on the public leaderboard with a score of 74.82/100. Its source-verified position is #6 of 130.
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. 48 of 435 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 #8. particularly strong for screenshots, documents, charts, and grounded multimodal workflows.
Moonshot AI · Model release
Radar confirmed these at the source. Use Kimi K3 in your work? Explore Radar to follow supported changes and choose your alerts.
Kimi K3 ranks #7 out of 232 models on the public BenchAlign leaderboard, with a score of 74.82/100. Its evidence status is Supported, and this profile shows 48 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Kimi K3 ranks #8 out of 183 eligible models for knowledge and understanding, with a public category score of 72/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Kimi K3 ranks #6 out of 151 eligible models for coding and programming, with a public category score of 68/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Kimi K3 ranks #4 out of 152 eligible models for agentic tool use and computer tasks, with a public category score of 71.9/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Kimi K3 ranks #1 out of 48 eligible models for multimodal and grounded tasks, with a public category score of 89.5/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
No. Kimi K3 currently has 75 source-displayable rows across 435 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.
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.
Related resources
Last updated September 10, 2026. Runtime fields remain blank until a sourced snapshot exists.
Get one weekly email when material rank, price, availability, or benchmark evidence changes are worth revisiting.
Read a sample issueJoin 2,000+ readers.