How much does Kimi K3 cost?

Kimi K3 costs $3.00 per million input tokens and $15.00 per million output tokens, using the list price from Moonshot AI as of 26 Oct 2026. That is about $1.05 for 100 chats of about 1,000 tokens in and 500 tokens back. Confirm on the maker's site before you buy, because prices change.

What is the context window of Kimi K3?

Kimi K3 has a context window of 1M tokens, roughly 786,000 words of text read at once. A single answer can be up to 1M tokens long.

Is Kimi K3 open source?

Kimi K3 has open weights: its trained parameters can be downloaded. That is not always the same as open source, because licence terms differ, so read the licence before you use it commercially.

How good is Kimi K3 compared with other AI models?

On the Epoch Capabilities Index, Kimi K3 scores 157.9 (likely range 155.1 to 160.6), which ranks 19 of 270 models we track. On Arena's human-vote text board it is ranked 15 of 166. Scores close together are a tie in practice.

How does Kimi K3 compare with Claude Opus 4.6?

Kimi K3 scores higher on 5 of 10 shared quality measures, Claude Opus 4.6 on 3. 2 measures are too close to call. Kimi K3 costs about 40% less than Claude Opus 4.6 on a blended price of $6.00 against $10.00 per million tokens. See the full comparison for every measure.

How current are these numbers for Kimi K3?

The newest data on this page is dated 26 Oct 2026. Scores come from Epoch AI and Arena, prices from the open LiteLLM price list.

AI Rankings

Kimi K3: Score, Price and Context Window

Where Kimi K3 from Moonshot AI ranks, what it costs and how much text it can read, in plain numbers with the sources.

Data updated 26 Oct 2026

Moonshot AI
Open weights
Released Jul 2026

Its score range overlaps with Gemini 3.7 Flash, the model just above it, so a small gap in rank is not a meaningful difference.

Best for

Demanding tasks: its overall Epoch score is in the top 10% of models we track.
Coding help: people rate its coding answers in the top 10% on Arena.
Very long documents: its context window is 1M tokens, roughly 786,000 words.

Skip if

Tight budgets: it is among the priciest quarter of models in the top half by score.

These lines are worked out from the numbers on this page, not from hands-on testing.

Key facts

Overall score: 157.9; Rank 19 of 270. Likely range 155.1 to 160.6.
Human preference: chat: 1487; Rank 15 of 166. 35,379 votes, at the "Max" setting.
Human preference: coding: 1539; Rank 9 of 166. 8,871 votes, at the "Max" setting.
Human preference: web pages: 1655; Rank 12 of 85. 20,312 votes, at the "Max" setting.
Price per million tokens: $3.00 in / $15.00 out; Blended $6.00. Cached input $0.30. List price from Moonshot AI, checked 26 Oct 2026.
Context window: 1M tokens; About 786,000 words at once. One answer up to 1M tokens.
Weights: Open; The weights can be downloaded. Check the licence before commercial use.

Features listed by the price list: Image input, Tool use, Reasoning, Structured output.

Try itKimi in our AI tools directoryAI assistant for research, documents, presentations, coding, and agent-driven knowledge work.

How Kimi K3 stacks up

Each strip shows every model we track as faint bars. The dot is this model. Better is always to the right, even for price.

Kimi K3 compared with all models we trackOverall capability: 157.9. Better than 93% of the other 269 models. Human preference: chat: 1487. Better than 91% of the other 165 models. Human preference: coding: 1539. Better than 95% of the other 165 models. Human preference: web pages: 1655. Better than 86% of the other 84 models. Price: $6.00 per 1M. Cheaper than 12% of the other 200 priced models. Context window: 1M tokens. Larger context window than 84% of the other 198 models.

Overall capability157.9
Better than 93% of the other 269 modelsTop 10%
Epoch Capabilities Index: one score that combines many tests.
Human preference: chat1487
Better than 91% of the other 165 modelsTop 10%
How often people pick its answers over another model's on Arena.
Human preference: coding1539
Better than 95% of the other 165 modelsTop 10%
How often people pick its answers to coding questions on Arena.
Human preference: web pages1655
Better than 86% of the other 84 modelsTop 25%
How often people pick the web pages and small apps it builds on Arena.
Price$6.00 per 1M
Cheaper than 12% of the other 200 priced models
Blended price per million tokens. Lower is better, so the cheapest models sit on the right.
Context window1M tokens
Larger context window than 84% of the other 198 modelsTop 25%
How much text it can read at once. Bigger suits long documents.

Compared with the other published models that have each measure. Data updated 26 Oct 2026.

Where Kimi K3 ranks

Leaderboards it appears on, best placing first.

See all leaderboards

Test results

Each test checks one kind of skill. Place shows where it stands among the models that took that test.

GPQA Diamond
Very hard multiple-choice science questions in biology, physics and chemistry, written by experts and designed so a quick web search does not give the answer.
93.1%
Place 19 of 183
OTIS Mock AIME
Maths competition problems in the style of the US AIME exam, from the 2024 and 2025 sets. Every answer is a whole number.
97.2%
Place 32 of 174
tied with 1 other
FrontierMath (Tiers 1-3)
Original, very hard maths problems written by mathematicians. Each has an exact answer and the problems are kept private so models cannot have memorised them. This is the Tiers 1 to 3 set, version 2.
72.2%
Place 24 of 87
SimpleBench
Everyday common-sense and trick questions that most people answer correctly but AI models often get wrong.
60.7%
Place 23 of 80
DeepSWE
Software engineering tasks scored as the share solved on the first try (pass@1), run with the open mini-SWE-agent setup.
68.5%
Place 8 of 26
SimpleQA Verified
Short factual questions that each have one correct answer. It measures how often a model gets facts right.
50.6%
Place 26 of 82
ARC-AGI-2
Visual puzzles where the AI must work out a new rule from a few examples and apply it. They test picking up a new idea quickly, not recalling facts.
60.4%
Place 30 of 86
tied with 2 others

What it costs in everyday terms

List prices turned into amounts you can picture. Real bills depend on how you use it.

100 chats: $1.05; Cost of 100 chats assumes each chat sends 1,000 tokens (about 750 words) and gets 500 tokens (about 375 words) back.
A 300-page book: $0.30; Cost to read a 300-page book assumes about 100,000 input tokens and no reply. A real book varies with page size and language.
Blended price: $6.00 per 1M; Three parts input to one part output. Our own calculation for comparing models.

Compare Kimi K3

Side-by-side pages for the closest rivals.

Similar models

Learn more

Questions about Kimi K3

How much does Kimi K3 cost?: Kimi K3 costs $3.00 per million input tokens and $15.00 per million output tokens, using the list price from Moonshot AI as of 26 Oct 2026. That is about $1.05 for 100 chats of about 1,000 tokens in and 500 tokens back. Confirm on the maker's site before you buy, because prices change.
What is the context window of Kimi K3?: Kimi K3 has a context window of 1M tokens, roughly 786,000 words of text read at once. A single answer can be up to 1M tokens long.
Is Kimi K3 open source?: Kimi K3 has open weights: its trained parameters can be downloaded. That is not always the same as open source, because licence terms differ, so read the licence before you use it commercially.
How good is Kimi K3 compared with other AI models?: On the Epoch Capabilities Index, Kimi K3 scores 157.9 (likely range 155.1 to 160.6), which ranks 19 of 270 models we track. On Arena's human-vote text board it is ranked 15 of 166. Scores close together are a tie in practice.
How does Kimi K3 compare with Claude Opus 4.6?: Kimi K3 scores higher on 5 of 10 shared quality measures, Claude Opus 4.6 on 3. 2 measures are too close to call. Kimi K3 costs about 40% less than Claude Opus 4.6 on a blended price of $6.00 against $10.00 per million tokens. See the full comparison for every measure.
How current are these numbers for Kimi K3?: The newest data on this page is dated 26 Oct 2026. Scores come from Epoch AI and Arena, prices from the open LiteLLM price list.

Where this data comes from

Epoch AI: Benchmark data: Epoch AI, 'Capabilities & benchmarking', epoch.ai/benchmarks (CC BY 4.0). We match models across sources, rank them and show them in charts. Scores are not changed. Epoch AI does not endorse this site.
Arena (formerly LMArena): Human-preference ratings: Arena (arena.ai) leaderboard dataset, CC BY 4.0. We keep the latest published ratings, match them to models from other sources and rank them. Ratings are not changed. Arena does not endorse this site.
LiteLLM model price list: Prices and context windows: LiteLLM model price list (github.com/BerriAI/litellm, MIT licence). We use the model maker's own price entry when there is one. Prices change often, so always confirm on the maker's site before you buy.

Newest data on this page: 26 Oct 2026. Prices are list prices and change often, so confirm on the maker's site before you buy. Sponsors never change a score or an order. How we calculate this · Report a mistake