That's NeuralModel catalog

moonshotai

MoonshotAI: Kimi K3

moonshotai/kimi-k3

About this model

Description below is the original text supplied by OpenRouter, shown in the source language.

Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at...

Specifications

Model ID
moonshotai/kimi-k3
Canonical ID
moonshotai/kimi-k3-20260715
Creator
moonshotai
Added to OpenRouter
16.07.2026
Context length
1,048,576
Modality
text+image+video->text
Input modalities
text, image, video
Output modalities
text
Token pricing
USD per 1M tokens: in $0.192 / out $16
Knowledge cutoff
—
Expiration date
—

Tasks and capabilities

A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.

TaskGradeSource-declared capability
General qualityCC — below the B bandreasoning: optional · default max · efforts: max, high, low, none · parameters: include_reasoning, reasoning, reasoning_effort
CodingAA — next 20% of the cohort—
AgentsAA — next 20% of the cohortparameters: structured_outputs, tool_choice, tools
WritingNo measurementoutput: text
ReasoningNo measurementreasoning: optional · default max · efforts: max, high, low, none · parameters: include_reasoning, reasoning, reasoning_effort
Document analysisNo measurement—
VisionNo measurementinput: image
Image generationNo measurement—
AudioNo measurement—
VideoNo measurementinput: video
EmbeddingsNo measurement—

Evaluations

SourceBenchmarkValueGradeData retrieved
Artificial AnalysisIntelligence index17.4CC — below the B band13.11.2026
Artificial AnalysisCoding index72AA — next 20% of the cohort13.11.2026
Artificial AnalysisAgentic index29.3AA — next 20% of the cohort13.11.2026
Design Arenaagents · agenticgamedevwin rate 54% · rank 41,202EloAA — next 20% of the cohort13.11.2026
Design Arenaagents · androidnativewin rate 57.7% · rank 71,255EloAA — next 20% of the cohort13.11.2026
Design Arenaagents · blender3dwin rate 40.1% · rank 91,156EloBB — next 30% of the cohort13.11.2026
Design Arenaagents · codetovideowin rate 63.3% · rank 31,269EloSS — top 10% of the cohort13.11.2026
Design Arenaagents · fullstackwin rate 61.5% · rank 41,295EloSS — top 10% of the cohort13.11.2026
Design Arenaagents · godotgamedevwin rate 48.5% · rank 141,204EloBB — next 30% of the cohort13.11.2026
Design Arenaagents · htmlslideswin rate 55.6% · rank 51,152EloAA — next 20% of the cohort13.11.2026
Design Arenaagents · mobileappswin rate 56.7% · rank 81,256EloAA — next 20% of the cohort13.11.2026
Design Arenaagents · pdfwin rate 66% · rank 61,278EloAA — next 20% of the cohort13.11.2026
Design Arenaagents · python-pptxslideswin rate 54.7% · rank 91,220EloAA — next 20% of the cohort13.11.2026
Design Arenaagents · spreadsheetwin rate 33.5% · rank 191,128EloCC — below the B band13.11.2026
Design Arenaagents · webappswin rate 59.3% · rank 71,280EloAA — next 20% of the cohort13.11.2026
Design Arenamodels · 3dwin rate 63.8% · rank 101,367EloSS — top 10% of the cohort13.11.2026
Design Arenamodels · codecategorieswin rate 60.3% · rank 61,352EloSS — top 10% of the cohort13.11.2026
Design Arenamodels · datavizwin rate 63.6% · rank 41,351EloSS — top 10% of the cohort13.11.2026
Design Arenamodels · gamedevwin rate 54.7% · rank 91,353EloSS — top 10% of the cohort13.11.2026
Design Arenamodels · svgwin rate 59.7% · rank 71,298EloSS — top 10% of the cohort13.11.2026
Design Arenamodels · uicomponentwin rate 60.5% · rank 101,339EloSS — top 10% of the cohort13.11.2026
Design Arenamodels · websitewin rate 59.3% · rank 41,337EloSS — top 10% of the cohort13.11.2026
How grades work

Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.

  • S — S — top 10% of the cohort
  • A — A — next 20% of the cohort
  • B — B — next 30% of the cohort
  • C — C — below the B band

Providers

Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.

ProviderContext lengthPrice in /1MPrice out /1MLatency p50 (30m, s)Throughput p50 (30m, tok/s)Uptime (30m)
Wafermxfp41,048,576$0.153$16——100%
Relacefp41,048,576$0.182$11.01——100%
Wafermxfp41,048,576$0.192$16——100%
InferenceNetfp41,048,576$0.234$15——100%
InferenceNetfp41,048,576$0.234$15——100%
Wafermxfp41,048,576$0.276$9.6——100%
Sail Researchfp41,048,576$0.345$16.58———
Sail Researchfp41,048,576$0.345$16.58———
InferenceNetfp41,048,576$0.450$18——100%
InferenceNetfp41,048,576$0.450$18——100%
ParetoAlpha1,048,576$1$11.25———
Makorafp41,048,576$1.2$16——100%
Chutesmxfp41,048,576$1.85$9.5——100%
Io Netfp41,048,320$2.3$14——96.67%
DigitalOcean1,048,576$2.55$12.95——100%
DeepInframxfp41,048,576$2.85$14.25——100%
KT1,048,576$3$15——100%
Amazon Bedrock1,048,576$3$15——100%
Parasailfp41,048,576$3$15——100%
Modalmxfp41,048,576$3$15——100%
Together1,048,576$3$15——100%
Fireworks1,048,576$3$15——100%
BaseTenfp81,048,576$3$15———
Moonshot AI1,048,576$3$15——100%
Alibaba1,048,576$3.45$17.25——100%
Parasailfp41,000,000$4.5$22.5——100%
Fireworks1,048,576$4.5$22.5——100%
Fireworks1,048,576$4.5$22.5——16.67%

Provider data retrieved: 13.11.2026