kimi-k2.5

39.1K Downloads Updated 1 week ago

Kimi K2.5 is an open-source, native multimodal agentic model that seamlessly integrates vision and language understanding with advanced agentic capabilities, instant and thinking modes, as well as conversational and agentic paradigms.

vision tools thinking cloud

ollama run kimi-k2.5:cloud

curl http://localhost:11434/api/chat \
  -d '{
    "model": "kimi-k2.5:cloud",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='kimi-k2.5:cloud',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'kimi-k2.5:cloud',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Applications

Claude Code ollama launch claude --model kimi-k2.5:cloud

Codex ollama launch codex --model kimi-k2.5:cloud

OpenCode ollama launch opencode --model kimi-k2.5:cloud

OpenClaw ollama launch openclaw --model kimi-k2.5:cloud

Models

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Name

1 model

Size

Context

Input

kimi-k2.5:cloud

256K context window · Text, Image · 1 week ago

kimi-k2.5:cloud

256K

Text, Image

Readme

Kimi K2.5 is an open-source, native multimodal agentic model built through continual pretraining on approximately 15 trillion mixed visual and text tokens atop Kimi-K2-Base. It seamlessly integrates vision and language understanding with advanced agentic capabilities, instant and thinking modes, as well as conversational and agentic paradigms.

Key Features

Native Multimodality: Pre-trained on vision–language tokens, K2.5 excels in visual knowledge, cross-modal reasoning, and agentic tool use grounded in visual inputs.
Coding with Vision: K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.
Agent Swarm: K2.5 transitions from single-agent scaling to a self-directed, coordinated swarm-like execution scheme. It decomposes complex tasks into parallel sub-tasks executed by dynamically instantiated, domain-specific agents.