kimi-k2
Moonshot AI/Open weights/1 provider
Kimi K2 Thinking is an open-source model that operates as a "thinking agent," reasoning step-by-step while using tools to achieve state-of-the-art performance on various benchmarks. It is capable of executing up to 200-300 sequential tool calls without human intervention, allowing it to solve complex problems across a wide range of tasks. The model uses Quantization-Aware Training (QAT) to support INT4 inference, which provides a roughly 2x improvement in generation speed.MoreLess
Which id to call
vertex/kimi-k2This model has no managed policy yet, so call the provider endpoint directly. Every id in the endpoints table works the same way.
From /1M input
$0.60
Google LLC (Vertex AI)
Context
262K
262K output
Endpoints
1
1 region
Regions
1
chat
Capabilities 4/8
1 endpoint / 1 region
Providers serving kimi-k2
Provider prices, per 1M tokens. Pay as you go adds 5%, or 0% on your own keys.
| Rank | Privacy | ||||||
|---|---|---|---|---|---|---|---|
| 1 |  Google LLC (Vertex AI) | Global | 262K | $0.60 | $2.50 | $0.06 | zdr |
A column is blank where no qualifying sample exists, and every row links to that provider's endpoint page.
model=
Which id to call
One base url, https://router.requesty.ai/v1, and one key for every id here.
vertex/kimi-k2This model has no managed policy yet, so call the provider endpoint directly. Every id in the endpoints table works the same way.
OpenAI compatible
Call it in three lines
Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.
123456789101112131415from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="vertex/kimi-k2", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)
Artificial Analysis
Benchmark scores
Graduate-level physics, chemistry & biology questions designed to resist Googling.
Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.
Scores from artificialanalysis.ai. They measure the model, not the provider, so they are the same on every endpoint above.
6
More from Moonshot AI
Reference
kimi-k2 questions
Which providers serve kimi-k2?
kimi-k2 is available from 1 provider through Requesty: Google LLC (Vertex AI). All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.
How much does kimi-k2 cost?
Pricing starts at $0.60 per million input tokens and $2.50 per million output tokens on Google LLC (Vertex AI), the cheapest endpoint. Prices vary by provider and region; the table above shows every endpoint. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.
Is kimi-k2 open weights?
Yes. kimi-k2 is an open-weights model from Moonshot AI, which is why multiple inference providers can host it. Provider choice affects price, latency, and data-privacy terms, all compared above.
What is the context window of kimi-k2?
kimi-k2 supports up to 262K tokens of context, with up to 262K output tokens per response. Some providers expose a smaller window; check the per-endpoint context column above.
How do I use kimi-k2 with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "vertex/kimi-k2" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.
Route kimi-k2 through one endpoint
One key for 1 provider on this model and 600+ others. No markup on provider prices, automatic failover, caching built in.