Kimi K2: Leading Open-Source Model Now Available on Together AI

Use Kimi K2 on Together's frontier AI cloud with high performance, reliability and scale

Starting today on Together AI, you can access Kimi-K2-Instruct from Moonshot AI — arguably the best open-source model available. With 1 trillion parameters, Kimi K2 delivers frontier performance across diverse AI applications, from autonomous reasoning and native tool use to creative writing that rivals proprietary models.

TL;DR:

• ‍Kimi-K2-Instruct now available on Together AI: Leading open-source model with 1T parameters and broad capabilitie
• Frontier performance: #1 on EQ-Bench3 and Creative Writing, 65.8% on SWE-bench Verified, leading among open models
• Deploy on Together's Frontier Platform with 99.9% reliability, instant scaling, and continuous performance optimizations
• Available now via standard APIs with serverless deployment benefits

Kimi K2's Breakthrough Performance

While most open-source models excel in specific domains, Kimi K2 delivers frontier performance across the full spectrum of AI capabilities.

Recent benchmark wins demonstrate this broad leadership:

• Empathy & Expression: #1 on EQ-Bench3 and Creative Writing — Best creative writer among all open and proprietary models
• Autonomous Coding: 65.8% on SWE-bench Verified vs. 38.8% (DeepSeek-V3) and 34.4% (Qwen3)—autonomous bug fixes and repo navigation.
• Tool Mastery: 76.5% on AceBench—seamless multi-tool orchestration across domains
• Production-Ready Code: 53.7% on LiveCodeBench v6—real tasks, real code execution.
• Superior performance on customer benchmarks — consistently outperforming alternatives in production deployments

What makes Kimi K2 particularly powerful: it's agentic by design with native tool use, autonomous workflows, and CLI integration. When you need to analyze salary trends, traditional AI provides explanations and recommendations. Kimi K2 loads the data, runs the analysis, generates charts, and writes the report — seamlessly executing complex workflows without hand-holding.

These results compete directly with major including Claude Sonnet and Opus 4, but as an open-source model with superior economics.

This performance comes from rethinking how agentic AI gets built. Instead of learning about tool use from static text, Kimi K2 learned by doing — simulating interactions with hundreds of domains and thousands of tools through Large-Scale Agentic Data Synthesis. This training approach creates agents that reason about which tools to use, in what sequence, and how to adapt when plans don't work as expected.

The architecture delivers on this training approach:

• 1T total parameters with 32B active per token
• Mixture-of-Experts design selecting 8 experts from 384
• Trained on 15.5 trillion tokens with zero instability using MuonClip optimizer

Deploy on Together's Frontier AI Cloud Platform

Kimi K2 is now available serverlessly on Together AI, removing the friction of deploying large agentic models. No infrastructure setup. No throttling. Just access via standard APIs — instantly production-ready.

Together's frontier AI cloud was designed for deploying the world's most advanced AI models with uncompromising performance and reliability. When you deploy Kimi K2 with us, you get:

Start experimenting immediately: Access Kimi K2 through our playground and chat application to test capabilities, then move seamlessly to production APIs when ready.

Economics that make sense: Deploy Kimi K2 at ＄1.00 per 1M input tokens and ＄3.00 per 1M output tokens - 60-70% lower than comparable closed models like Anthropic Sonnet and Opus 4. Use our Batch API for even more cost-effective distillation and synthetic data generation.

Deploy with confidence: 99.9% availability SLA with multi-region deployment and enterprise security hosted on SOC 2 compliant servers in North America ensures your agentic workflows complete successfully, even during unexpected traffic surges.

Scale without limits: Seamless scaling from serverless to dedicated clusters handles everything from prototyping to full production during peak traffic, without throttling.

Optimize for your needs: Our research team's innovations — from FlashAttention to custom kernels — deliver up to 50% cost savings and 2x performance improvements. Access Kimi-K2-Base as a dedicated endpoint for custom fine-tuning, or use our Fine-Tuning API to tailor the model to your specific use cases.

This isn't just model hosting. It's a platform built to make cutting-edge AI models like Kimi K2 production-ready from day one with the security, performance, and cost advantages that enterprise applications require.

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Applications & Getting Started

Kimi K2's broad capabilities enable diverse applications. For autonomous workflows, you provide tools and goals rather than step-by-step instructions.

This unlocks applications across domains:

• Autonomous workflows: Customer support agents that resolve issues across multiple systems
• Creative applications: Content generation, storytelling, and narrative development that rivals proprietary models
• Research and analysis: Tools that explore datasets and generate comprehensive insights
• Development environments: Describe a feature and get working code, tests, and documentation
• Model development: Cost-effective distillation and synthetic data generation for training custom models
• Enterprise applications: Fine-tuned versions for domain-specific tasks with Together AI's custom deployment options

Kimi K2 represents a new standard for open-source AI — delivering leading performance across creative writing, emotional intelligence, autonomous workflows, and complex reasoning. Together's frontier AI cloud makes this frontier model accessible with enterprise-grade deployment

Try Kimi-K2-Instruct today in our playground or connect via our APIs:

• Use it now on Together Chat
• Try it now on our Playground
• Deploy via our Serverless API

Compatible with existing Together AI workflows.

Use our Python SDK to quickly integrate Kimi-K2-Instruct into your applications:

    
from together import Together

client = Together()

response = client.chat.completions.create(
    model="moonshotai/Kimi-K2-Instruct",
    messages=[],
    stream=True
)
for token in response:
    if hasattr(token, 'choices'):
        print(token.choices[0].delta.content, end='', flush=True)