Moonshot AI
on Orq.ai
Access Moonshot AI models through Orq.ai for reasoning, coding, long-context, and other AI workloads through one API.
Capabilities:
Chat
Reasoning
Code
Models Supported:
Kimi K3
kimi-k2.7-code-highspeed
moonshot-v1-128k
moonshot-v1-128k-vision-preview
moonshot-v1-32k
moonshot-v1-32k-vision-preview
moonshot-v1-8k
moonshot-v1-8k-vision-preview
kimi-k2.7-code
kimi-k2.6
...
Provider HQ:
Beijing, China
Access Moonshot AI through Orq.ai’s AI Router
Moonshot AI develops language models for reasoning, coding, and long-context applications. Its models are particularly suited to workloads involving large documents, extensive conversational context, and multi-step analysis.
Moonshot AI models available on Orq.ai
Compare the Moonshot AI models currently available through Orq.ai, including their supported capabilities, context windows, pricing, and regional availability.
Model
Type
Context
Input / 1M
Output / 1M
Kimi K3
chat
Reasoning
Vision
Video
1M
$3.00
$15.00
kimi-k2.7-code-highspeed
chat
Reasoning
Vision
Video
262K
$1.90
$8.00
moonshot-v1-128k
chat
131K
$2.00
$5.00
Why use Moonshot AI through Orq.ai?
Using Moonshot AI through Orq.ai lets teams add long-context reasoning and coding models to a wider model stack without maintaining separate routing, evaluation, observability, and cost-control logic for each provider.
Capability | Provider | Direct | Through Orq.ai |
|---|---|---|---|
Chat | Moonshot AI models | Call supported models directly for chat, reasoning, coding, and other language-model workloads. | Use Moonshot AI models through Orq.ai’s OpenAI-compatible endpoint while applying routing, tracing, evals, budgets, and governance controls around each request. |
Code | Moonshot AI models | Use supported models for code generation, debugging, refactoring, and agentic coding workflows. | Route coding workloads through Orq.ai, compare Moonshot AI with other providers, and monitor cost, latency, and quality from a shared control layer. |
Long-context analysis | Moonshot AI models | Use supported models for workloads involving large documents, extended conversations, and multi-step analysis. | Route long-context workloads to Moonshot AI where appropriate while using other providers for tasks with different cost, latency, or capability requirements. |
Pricing
Moonshot AI pricing varies by model, context requirements, usage volume, provider configuration, and billing setup.
You can connect supported Moonshot AI credentials to Orq.ai or use other available access options depending on your workspace configuration. Check Orq.ai and your Moonshot AI setup for current per-model rates, quotas, and billing details.
Compatible frameworks and tools
Orq.ai works with OpenAI-compatible clients and common AI development frameworks. Supported Moonshot AI models can be incorporated into Orq.ai workflows depending on the model, endpoint, and integration configuration.
Check the Orq.ai integration documentation for the latest setup options and compatibility information for Moonshot AI.
FAQs
Do I need a separate Moonshot AI / Kimi account to use Moonshot through Orq.ai?
You can connect supported Moonshot AI credentials to Orq.ai or use other available access options depending on your workspace, plan, and region. Orq.ai provides a shared layer for routing, observability, evaluations, and cost controls around that usage.
Can I route only some workflows to Moonshot and others to different providers?
Yes. Orq.ai lets you route different workloads to different providers, so you can use Moonshot AI where long-context processing, reasoning, coding, or other model capabilities fit the workload while routing other requests elsewhere.
Does using Moonshot AI through Orq.ai add latency?
Orq.ai adds a routing layer between your application and the model provider. Teams can monitor end-to-end latency and use routing, caching, and provider controls where appropriate to manage performance.
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