TokenRaAI Model Catalog
Kimi K2.8 Preview - Coding model via TokenRa

Kimi K2.8 Preview API Guide

Use one TokenRa API key to evaluate enabled Kimi models from Moonshot AI for research, document analysis, knowledge workflows, and conversational applications. Confirm the active model version, context behavior, and pricing in the console.

Create an API keyRead the integration guide

What Kimi K2.8 Preview is

Kimi K2.8 Preview is Moonshot AI's coding-focused model that became the default engine in Kimi Code on September 11, 2026. It is a silent upgrade to the default Kimi Code coding model rather than a standalone open-weight release, with a 1M-token context window, adjustable thinking, and multimodal input.

01

Coding and agents

Built for code completion, everyday development, and coding Agent tasks across long-running workflows.

02

1M-token context

Handle large repositories, long documents, and multi-turn history in a 1,048,576-token context window.

03

Adjustable thinking

Choose low, high, or max thinking, with max as the default.

Where Kimi K2.8 Preview API fits

Kimi models are candidates for workloads where context handling matters. Test with the same document sizes, languages, and retrieval noise that users will produce.

  • Research assistants that compare multiple supplied sources and return traceable conclusions.
  • Document review pipelines that extract clauses, entities, risks, or structured records.
  • Knowledge-base question answering with retrieved passages and explicit grounding rules.
  • Long-running agent or support conversations that need carefully managed history.

Kimi K2.8 Preview architecture and Agent capabilities

Kimi K2.8 Preview combines Kimi Delta Attention, Attention Residuals, Stable LatentMoE, and quantization-aware training with MXFP4 weights and MXFP8 activations. These are Moonshot AI technical claims; they describe architecture and scaling efficiency, not a guaranteed speedup for every workload.

  • Native multimodal: MoonViT-V2 vision encoding supports text, image, and video input for vision-in-the-loop work.
  • Reasoning: Thinking is always enabled; set reasoning_effort to low, high, or max.
  • Tools: Function calling, tool_choice, and JSON Schema structured output support Agent integrations.
  • Open weights: Kimi K2.8 Preview uses the Kimi K2.8 Preview License, not an unrestricted Apache or MIT license.

Integrate Kimi K2.8 Preview with a controlled context strategy

Use the enabled model ID from the console and send an OpenAI-compatible chat request where supported. Keep document assembly, retrieval, and citation verification in your application.

1

Prepare and label context

Separate instructions from source text, retain source identifiers, and remove irrelevant material before sending the request.

2

Measure grounded answers

Check whether each claim is supported by the supplied context and define how the application handles missing evidence.

3

Control context growth

Trim stale turns, summarize history carefully, cap output, and monitor usage as documents and conversations expand. 

curl https://tokenra.io/zen/go/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"kimi-k2.8-preview","messages":[{"role":"user","content":"Summarize the supplied research context with source labels."}]}'

Kimi K2.8 Preview pricing

Kimi K2.8 Preview is a paid model through TokenRa. Current rates are $0.80 per 1M input tokens, $3.35 per 1M output tokens, and $0.14 per 1M cached read tokens. Confirm current availability and account limits in the live console.

Input

$0.80 / 1M tokens

Standard input pricing.

Output

$3.35 / 1M tokens

Generated output pricing.

Cached read

$0.14 / 1M tokens

Cached input read pricing.

Moonshot AI model

Kimi K2.8 Preview is developed by Moonshot AI. TokenRa provides the API gateway and is not the model developer or owner.

Production checklist

  • Keep API keys on the server and separate credentials by environment or workload.
  • Set explicit timeouts, bounded retries, and request tracing before routing user traffic.
  • Evaluate model behavior with representative inputs instead of assuming versions are interchangeable.
  • Monitor usage and cost in the console, then add application-side budgets and limits.
  • Review provider terms, privacy requirements, and output rights for your use case.

Kimi K2.8 Preview API FAQ

Is Kimi API available through TokenRa?

Availability depends on the channels enabled for your account. Check the live directory and console for the current model identifier and access.

How do I integrate Kimi API?

Create a TokenRa API key, confirm the enabled model identifier, and use the request format documented for that capability. Applicable text models use an OpenAI-compatible endpoint; media models may use asynchronous tasks.

How much does Kimi API cost?

Pricing can vary by model version and active channel. Review the current billing unit and rate in the live model directory or console before testing.

Can I switch to another model later?

Yes. TokenRa keeps credentials and account-level usage in one place. Request fields and model behavior can still differ, so run regression evaluations before changing production traffic.

“Kimi”, “Moonshot AI”, and related names may be trademarks of their respective rights holders. TokenRa is an independent API gateway and this page is not an official vendor page or endorsement.