ReadyGPU TEE

MoonshotAI: Kimi K2 Thinking

Model IDmoonshotai/kimi-k2-thinking

Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on the trillion-parameter Mixture-of-Experts (MoE) architecture introduced in Kimi K2, it activates 32 billion parameters per forward pass and supports 256 k-token context windows. The model is optimized for persistent step-by-step thought, dynamic tool invocation, and complex reasoning workflows that span hundreds of turns. It interleaves step-by-step reasoning with tool use, enabling autonomous research, coding, and writing that can persist for hundreds of sequential actions without drift. It sets new open-source benchmarks on HLE, BrowseComp, SWE-Multilingual, and LiveCodeBench, while maintaining stable multi-agent behavior through 200–300 tool calls. Built on a large-scale MoE architecture with MuonClip optimization, it combines strong reasoning depth with high inference efficiency for demanding agentic and analytical tasks.

Start building Docs

input

$2.00/M

output

$2.00/M

context

262K

created

Jan 9, 2026

Supported API shape

input

text

output

text

tools

Supported

json mode

Supported

Verification

signature

response ID

attestation

GPU TEE

provider

1 routes

Providers

tinfoil

GPU TEE

input

$2.00/M

output

$2.00/M

context

262K

$ pip install openai

1from openai import OpenAI
2import os
3
4MODEL = "moonshotai/kimi-k2-thinking"
5
6client = OpenAI(
7    base_url="https://api.redpill.ai/v1",
8    api_key=os.environ["REDPILL_API_KEY"],
9)
10
11response = client.chat.completions.create(
12    model=MODEL,
13    messages=[{"role": "user", "content": "Run this privately."}],
14)
15
16print(response.id)
17print(response.choices[0].message.content)

$ npm install openai

1import OpenAI from "openai"
2
3const MODEL = "moonshotai/kimi-k2-thinking"
4
5const openai = new OpenAI({
6  baseURL: "https://api.redpill.ai/v1",
7  apiKey: process.env.REDPILL_API_KEY,
8})
9
10const response = await openai.chat.completions.create({
11  model: MODEL,
12  messages: [{ role: "user", content: "Run this privately." }],
13})
14
15console.log(response.id)
16console.log(response.choices[0].message.content)

1curl https://api.redpill.ai/v1/chat/completions \
2  -H "Authorization: Bearer $REDPILL_API_KEY" \
3  -H "Content-Type: application/json" \
4  -d '{
5    "model": "moonshotai/kimi-k2-thinking",
6    "messages": [
7      { "role": "user", "content": "Run this privately." }
8    ]
9  }'

More models

Other private inference routes.

View catalog

encrypted

MoonshotAI: Kimi K2.6

Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and demonstrates strong performance in agentic workflows.

context

262K

input

$1.09/M

encrypted

MoonshotAI: Kimi K2.5

Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed visual and text tokens, it delivers strong performance in general reasoning, visual coding, and agentic tool-calling.

context

262K

input

$0.60/M

encrypted

Qwen: Qwen3.5-27B

The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its overall capabilities are comparable to those of the Qwen3.5-122B-A10B.

context

262K

input

$0.30/M

encrypted

Z.AI: GLM 4.7 Flash

As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning, and tool collaboration, and has achieved leading performance among open-source models of the same size on several current public benchmark leaderboards.

context

203K

input

$0.10/M