Moonshot AI Models

34 modelsGeneral models free to startUp to 1.05M context

Usage

Last 30 days · 2026-07-13 to 2026-08-11

Tokens

112B

Requests

614K

Models in use

25 of 34

Tokens per day

015B29.9B07-1307-2007-2708-0308-102026-07-13 — 339,573,030 tokens2026-07-14 — 438,880,160 tokens2026-07-15 — 437,520,925 tokens2026-07-16 — 831,019,480 tokens2026-07-17 — 2,732,525,330 tokens2026-07-18 — 2,747,119,070 tokens2026-07-19 — 2,052,104,325 tokens2026-07-20 — 2,974,767,570 tokens2026-07-21 — 3,420,518,700 tokens2026-07-22 — 5,975,452,665 tokens2026-07-23 — 7,593,443,240 tokens2026-07-24 — 3,128,932,730 tokens2026-07-25 — 3,045,199,865 tokens2026-07-26 — 2,191,580,200 tokens2026-07-27 — 3,494,906,340 tokens2026-07-28 — 5,780,633,620 tokens2026-07-29 — 7,815,843,385 tokens2026-07-30 — 2,742,629,200 tokens2026-07-31 — 2,595,514,910 tokens2026-08-01 — 1,485,450,655 tokens2026-08-02 — 1,133,753,835 tokens2026-08-03 — 2,365,479,990 tokens2026-08-04 — 2,947,383,635 tokens2026-08-05 — 1,830,718,070 tokens2026-08-06 — 3,631,375,680 tokens2026-08-07 — 29,936,666,305 tokens2026-08-08 — 1,149,813,535 tokens2026-08-09 — 4,583,387,485 tokens2026-08-10 — 1,325,250,320 tokens2026-08-11 — 1,621,707,200 tokens

Which models that traffic went to

  1. kimi-k372.9%81.9B
  2. kimi-k2.69.4%10.6B
  3. kimi-k2.7-code8.1%9B
  4. coding-kimi-k36.5%7.3B
  5. kimi-k2.51.7%1.9B
  6. coding-kimi-k3-free1.0%1.1B
  7. kimi-k2.7-code-highspeed0.3%338M
  8. azure-kimi-k2.5<0.1%21.6M
  9. 8 more models0.1%61.8M

Share of 112B tokens. 9 models with traffic report no token counts and cannot be ranked here, including cc-kimi-k2-instruct and kimi-k2-instruct — they are in the request view.

The two views disagree on purpose: a model can take a large share of the calls and a small share of the tokens — many short requests — or the reverse. Which one matters depends on whether your cost is driven by call volume or by prompt length. Measured on AIHubMix over the last 30 days, counting the 34 model IDs listed on this page; traffic routed through upstream-specific IDs that are not in the public catalog is not included.

All 34 Moonshot AI Models

Open in model list
Moonshot AI models on AIHubMix with input and output modalities, context length, maximum output, price per million tokens including cache read and cache write rates, and measured throughput and latency.
Modalities
coding-kimi-k3-freeTakes text, vision, video, returns text.1.05MFreeFree/MFree/M73 tok/s0.91 s
coding-kimi-k3Takes text, vision, video, returns text.1.05M$0.44$1.61/M$0.07/M73 tok/s0.91 s
kimi-k3Takes text, vision, video, returns text.1.05M$3.00$15.00/M$0.30/M18 tok/s13.11 s
kimi-k2-thinkingTakes text, returns text.262K$0.55$2.19/M$0.14/M168 tok/s0.62 s
kimi-k2.6Takes text, vision, video, returns text.262K33K$0.95$4.00/M$0.16/M128 tok/s2.42 s
kimi-k2.7-codeTakes text, vision, video, returns text.262K33K$0.95$4.00/M$0.16/M83 tok/s0.91 s
kimi-k2-turbo-previewTakes text, returns text.262K$1.20$4.80/M$0.30/M20 tok/s3.06 s
kimi-k2.7-code-highspeedTakes text, vision, video, returns text.262K33K$1.90$8.00/M$0.32/M119 tok/s4.81 s
k2.6-code-preview-freeTakes text, returns text.256KFreeFree/M
kimi-for-coding-freeTakes text, returns text.256KFreeFree/M
alicloud-kimi-k2.5256K$0.55$2.88/M$0.10/M
sf-kimi-k2-thinking256K$0.55$2.19/M42 tok/s1.63 s
azure-kimi-k2.5256K$0.60$3.00/M
kimi-k2.5Takes text, vision, video, returns text.256K$0.60$3.00/M$0.10/M27 tok/s1.26 s
kimi-k2-0711Takes text, returns text.131K$0.54$2.16/M50 tok/s0.78 s
cc-k2.6-code-preview$0.20$0.20/M$0.02/M
cc-kimi-for-coding$0.20$0.20/M$0.02/M
moonshotai/Moonlight-16B-A3B-Instruct$0.20$0.20/M
cc-kimi-dev-72b$0.32$1.28/M
moonshotai/Kimi-Dev-72B$0.32$1.28/M
kimi-k2-instructTakes text, returns text.$0.54$2.16/M40 tok/s0.10 s
alicloud-kimi-k2-instruct$0.55$2.19/M
alicloud-kimi-k2-thinking$0.55$2.19/M
cc-kimi-k2-thinking$0.55$2.19/M
moonshot-kimi-k2.5$0.60$3.00/M$0.10/M
cc-kimi-k2-instructTakes text, returns text.$1.10$3.30/M
cc-kimi-k2-instruct-0905Takes text, returns text.$1.10$3.30/M
moonshot-v1-8k$2.00$2.00/M
moonshot-v1-8k-vision-preview$2.00$2.00/M
moonshot-v1-32k$4.00$4.00/M
moonshot-v1-32k-vision-preview$4.00$4.00/M
moonshot-v1-128k$10.00$10.00/M
moonshot-v1-128k-vision-preview$10.00$10.00/M
kimi-thinking-preview$30.00$30.00/M

Prices are USD per million tokens; cache read and cache write are the rates for prompt-cache hits and for writing a prompt into the cache. Throughput and latency are measured on AIHubMix — the same figures the model detail page shows — not vendor claims. A dash means the catalog does not publish that field for that model, which is not the same as the model not supporting it.

Moonshot AI on AIHubMix

Which Moonshot AI model should I start with?

coding-kimi-k3-free is free on input — the cheapest entry here that declares tool calling, and it carries a 1.05M context. Move up to kimi-thinking-preview when answer quality matters more than cost, or to coding-kimi-k3 for long-form reasoning.

Which of these models reason before answering?

10 of the 34 models here declare a reasoning phase — they work through the problem before producing an answer, which helps on multi-step problems at the cost of extra output tokens. Use the Reasoning filter above the table to see them. The catalog does not record anything further about how they differ, so this page does not sort them into families.

Why are there several entries for the same model?

Because each row is a route you can call, not a model release. Some IDs name an upstream (azure-, alicloud-, cc-), some are the open-weight repository form (moonshotai/…), and some differ only in capitalisation, kept so older integrations keep working.

The catalog does not carry a field saying which of those a given row is, so this page does not sort them into buckets it would have to invent. Every row shows that route’s own price, context and speed — compare those directly, and open a model to see the upstreams that serve it.

How is cached input billed?

The Cache read column is the rate for input tokens served from the prompt cache — for example cc-k2.6-code-preview bills cache hits at 10% of the input rate and cc-kimi-for-coding bills cache hits at 10% of the input rate. Cache write is the surcharge for putting a prompt into the cache in the first place, and only a few upstreams bill it separately. A dash in either column means the catalog carries no cache rate for that model, so plan on paying the full input rate.

Do I need a separate Moonshot AI account?

No. One AIHubMix key covers every model on this page, and switching between them is a change to the model string — billing, rate limits, and logs stay in one place.

Start calling Moonshot AI in one line

One key, one endpoint, 844 models across 35 providers.