KymaKyma
Moonshot

Moonshot

Kimi K3

Kimi K3 is a 2.8T open-weight reasoning model built for long-horizon agentic workflows and large-repo analysis. Developers should reach for it when they need a million-token context window with vision input and reliable tool execution.

Modalities

Text+Image → Text

Input

$4.05 /1M

Output

$20.25 /1M

Cached input

$0.405 /1M90% off

Context

1M

Speed

medium

Performance

Live production data from real requests on Kyma — not synthetic benchmarks.

Rank

#46

of 87 active models

Tokens served

99.7K

all-time

Success rate

100%

last 7 days

Median throughput23 tok/s
Total requests109
Platform share0.0%
Tokens · last 15 daysJul 19 → Aug 2

Pricing

Pay per token. Cached input is billed at 10% of the input rate.

$4.05 /1M input$20.25 /1M output
Hobby10 req/day · 2K in / 500 out
~$5.47/mo
Production1,000 req/day · 2K in / 500 out
~$547/mo
Scale20,000 req/day · 2K in / 500 out
~$10,935/mo
+ Estimate your workload
1,000
2,000
500
30%

Estimated monthly cost

$481

$16.04 / day on Kimi K3

Same workload on:

Kimi K2.7 Code$132-73%
Kimi K2.6$101-79%

Estimates use list pricing with cached input billed at the 90%-discount rate. Actual bills depend on real token counts — every response includes its exact cost.

When to use Kimi K3

Updated 2026-07-29

Where this model earns its cost — and where it doesn't.

Kimi K3 is Moonshot’s 2.8T open-weight multimodal model, designed as a successor to K2.7. It accepts text and image inputs and outputs text, with native support for structured outputs, tool calling, and explicit reasoning steps. The model operates with a 1,048,576-token context window and a maximum output length of 32,768 tokens.

On Kyma, the model runs through an OpenAI-compatible endpoint with automatic request failover and exact cost reporting in the usage.cost field. Prompt caching is supported, reducing repeated prefix costs to 10% of the standard input rate. The platform serves it at a medium speed tier, averaging around 12 tokens per second in production.

The 32,768-token output cap means it is not suited for generating extremely long documents in a single pass. As a premium-tier model, it carries higher per-token costs than lighter alternatives, and its medium throughput requires planning for latency-sensitive applications.

Agentic Workflow Execution

Handles multi-step coding and tool execution across extended sessions without losing context.

Large Repository Analysis

Ingests entire codebases or documentation sets within its million-token window for cross-file reasoning.

Vision-Enabled Document Review

Processes image inputs alongside text to extract and reason over multimodal data.

Structured Data Extraction

Outputs strictly formatted JSON or XML for reliable downstream parsing and API integration.

Not ideal for: It is not the right choice for high-throughput, low-latency chat or generating outputs longer than 32,768 tokens.

How it compares

Against the peers people actually weigh it against.

SpecKimi K3Kimi K2.7 CodeKimi K2.6
Input /1M$4.05$1.009$0.776
Output /1M$20.25$4.774$3.622
Context1M262K262K
ToolsYesYesYes
ReasoningYesYesYes
Speedmediummediummedium

Quick start

Up and running in under two minutes.

  1. 1

    Create an API key

    Sign up and grab a key from the dashboard — $0.50 free credit, no card required.

    Get API key →
  2. 2

    Make your first request

    Drop in your key and send a chat completion — fully OpenAI-compatible.

    curl https://kymaapi.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k3",
    "messages": [
      {"role": "user", "content": "Explain prompt caching in one paragraph."}
    ]
  }'
  3. 3

    Stream responses

    Add "stream": true to receive tokens as they arrive.

    curl https://kymaapi.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k3",
    "stream": true,
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

FAQ

Common questions about this model.

What is the context window of Kimi K3?

Kimi K3 has a 1M-token context window — roughly 1542 pages of text in a single request.

How much does the Kimi K3 API cost?

$4.05 per 1M input tokens and $20.25 per 1M output tokens, with cached input at $0.405/1M — a 90% discount on repeated prompt prefixes. No subscription; you pay only for what you use.

Does Kimi K3 support function calling?

Yes — Kimi K3 supports tool/function calling and structured outputs (JSON mode), so it works with agent frameworks out of the box.

How do I use Kimi K3?

Kyma is OpenAI-compatible: point your SDK's base URL at https://kymaapi.com/v1, use your Kyma API key, and set the model to kimi-k3. Signing up is free and includes $0.50 of credit — no card required.

Does Kyma support prompt caching for this model?

Yes, repeated prompt prefixes are cached automatically and billed at 10% of the standard input rate.

What happens if the serving path fails during a request?

Kyma routes every request through automatic failover, so degraded paths are silently rerouted without dropping the call.

Can I use this model for image analysis?

Yes, Kimi K3 accepts both text and image inputs, though it only outputs text.

Start with $0.50 free credit — no card required.Create account →

More models by Moonshot

ModelContextInputOutput
MoonshotKimi K2.7 Code262K$1.009$4.774
MoonshotKimi K2.6262K$0.776$3.622
MoonshotKimi K2.5262K$0.6075$3.038