Model introduction
Kimi K3 is Moonshot AI's 2.8T-parameter native multimodal reasoning model with a 1M context window, built for long-horizon coding, knowledge work, and deep reasoning.
Model capabilities
Specifications come from the cited model material. Catalog tags help identify access features; use the source documentation for exact limits.
Verified specifications
- Official positioning
- Long-horizon coding, knowledge work, and deep reasoning
- Context window
- 1,000,000 tokens
- Model size
- 2.8T parameters, 16 / 896 experts active
- Input modalities
- Text, image
Sources: Moonshot AI Kimi K3 technical blog
Model pricing and access
Prices are read directly from the MoleAPI console catalog and shown by current billing group and context tier.
Your final charge follows the account group shown in the console.
Live pricing source
Pricing table
USD / 1M tokensStandardx1defaultInput $3 · Output $15
Input
$3 / 1M tokens
Output
$15 / 1M tokens
Cache read
$0.3 / 1M tokens
Discountx0.8discountInput $2.4 · Output $12
Input
$2.4 / 1M tokens
Output
$12 / 1M tokens
Cache read
$0.24 / 1M tokens
Relayx0.3relayInput $0.9 · Output $4.5
Input
$0.9 / 1M tokens
Output
$4.5 / 1M tokens
Cache read
$0.09 / 1M tokens
Access protocols
Available billing groups: Standard, Discount, Relay
- openai
- POST
- /v1/chat/completions
- openai-response
- POST
- /v1/responses
- anthropic
- POST
- /v1/messages
- gemini
- POST
- /v1beta/models/{model}:generateContent
About k3
This introduction is transcreated for clarity and cross-checked against the cited model material.
Kimi K3 is Moonshot AI's 2.8T-parameter native multimodal reasoning model with a 1M context window, built for long-horizon coding, knowledge work, and deep reasoning.
Core strengths
- A 2.8T architecture, 1M context, and native vision support unusually long agent workflows.
- Its independent composite score is very strong, especially for long-horizon coding and knowledge work.
- An open-weight path and OpenAI-compatible API support migration and future self-hosting.
Limitations
- It currently defaults to maximum reasoning effort; independent testing shows slow output and high token use.
- Moonshot notes that the model can be overly proactive, so bounded agents need explicit system constraints.
- Switching models mid-session or dropping thinking history can make quality unstable.
Selection and production evaluation
Start a k3 evaluation by mapping its official positioning to real work: Large repositories, long-running agents, research-heavy knowledge work, and coding or creation loops that use visual feedback. The first pass should exercise both its main strength, "A 2.8T architecture, 1M context, and native vision support unusually long agent workflows.", and its known limitation, "It currently defaults to maximum reasoning effort; independent testing shows slow output and high token use.", instead of relying on a single subjective general-chat comparison.
For access, MoleAPI currently lists openai, openai-response, anthropic, gemini protocols and the Standard, Discount, Relay billing groups for this Moonshot model; the default price summary is Input $3 / 1M tokens · Output $15 / 1M tokens. Pricing, protocols, and groups come from the live catalog, so production planning should still price representative requests using real context length, output size, and cache-hit assumptions.
No independent ranking is shown unless it matches this exact model ID and reasoning profile, so nearby variants are not used as a proxy. Before launch, pin the model ID, prompt, and sample set, then compare task accuracy, structured-output validity, tool-call success, and timeout rates under the same conditions.
The model material on this page was last checked on 2026-07-23. When upstream model cards, context limits, or tool support change, update the cited bilingual facts before changing the recommendation; live MoleAPI price changes remain separate and update from the catalog automatically.
Code examples
These examples use MoleAPI's Responses API endpoint and run after you replace the API key.
curl https://api.moleapi.com/v1/responses \
-H "Authorization: Bearer $MOLEAPI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "k3",
"input": "Explain this problem step by step."
}'Frequently asked questions
How is k3 priced?
This page reads prices from the MoleAPI console API and updates with model prices, context tiers, and account groups.
How can I access k3?
Protocols and endpoints come from the supported_endpoint_types field in the MoleAPI model catalog.
How do I switch an existing project to k3?
Keep the MoleAPI API address and key, replace the model parameter with the model ID on this page, then check protocol-specific parameter differences.
Where do the k3 model details come from?
Capabilities and limitations are checked against Moonshot AI and the other cited pages. Pricing and available protocols come only from the MoleAPI console.