Moonshot
Kimi K3 API
Kimi K3 is Moonshot AI's reasoning-oriented model, built for tasks that reward thinking through a problem before answering: multi-step coding, tool-using agents, and analysis over long documents. It carries a large context window, so extended transcripts, specifications, or codebases can be handled in one pass.
Its appeal on GlideflowAI is the combination of a capable reasoning route and a price well below the frontier Western flagships, shown above in USD. For teams that want deliberate, agentic behavior without a premium bill, it is a practical middle option between the cheapest chat models and the top Claude or GPT routes.
It runs behind the same OpenAI- and Anthropic-compatible interface as the rest of the catalog, so adopting it is a model-name change rather than an integration project. Keep your existing client and credentials and route the requests that benefit from reasoning to this model.
What Kimi K3 is good for
- Coding agents that need to plan, call tools, and revise across several steps.
- Working through long specifications or research documents that exceed a small context window.
- Drafting and then critiquing a solution in the same session before committing to it.
- Structured extraction and analysis where a short chain of reasoning improves accuracy.
- Cost-sensitive workloads that still want deliberate behavior rather than a one-shot reply.
New to the gateway? Start with the quickstart, then review authentication before putting a key in an application.
Before a production launch, keep credentials server-side, record each selected model, token use, and validation result, and define a per-run budget. Those traces let you compare models on the workflow that matters, diagnose failures with evidence, and change a routing rule without guessing when product requirements or traffic change.
When to choose Kimi K3
Choose Kimi K3 when you want reasoning and long-context handling at a lower price than the frontier flagships, and you do not need the absolute top tier for a high-consequence change. For the hardest investigations or the most costly mistakes, a premium Claude or GPT route still buys more headroom; for routine, latency-sensitive chat, a smaller model is cheaper.
Compare the current token rates on Pricing and test the nearest alternatives on your real prompts. The related models below are a useful starting set for that evaluation.
Pricing
USD per 1M tokens. No hidden markup.
Input
Output
Call Kimi K3 in seconds
It's OpenAI-compatible. Point your existing client athttps://api.glideflowai.com/v1and set the model tokimi-k3.
curl https://api.glideflowai.com/v1/chat/completions \
-H "Authorization: Bearer sk-xxx" \
-H "Content-Type: application/json" \
-d '{
"model": "kimi-k3",
"messages": [{"role": "user", "content": "Hello"}]
}'FAQ
Who makes Kimi K3?
Kimi K3 is developed by Moonshot AI. On GlideflowAI it is served through the standard OpenAI- and Anthropic-compatible interface, so you reach it the same way as every other route in the catalog.
How is Kimi K3 billed?
GlideflowAI bills input and output tokens separately at the USD rates shown above, per one million tokens. Because it is a reasoning model, an answer can include more generated tokens than a plain chat reply, so weight the output-side rate when estimating a workload.
Can I call it with the OpenAI SDK?
Yes. Set the SDK base URL to GlideflowAI's endpoint, use your GlideflowAI key, and pass kimi-k3 as the model name. No provider-specific SDK is required.
When should I pick it over a cheaper model?
Reach for Kimi K3 when a task benefits from a short chain of reasoning or tool use — planning a change, working through a long document, or running an agent loop. For simple, high-volume responses, a smaller route on the Models page will cost less per call.