Moonshot's Kimi K2 for Coding: Our First Impressions in Cline

Moonshot AI's Kimi K2 is now available in Cline. This 1T parameter open-source model has been making waves with its benchmark results, particularly in coding tasks. For developers curious about whether these benchmarks translate to real-world performance, Cline offers the perfect environment to find out.

Kimi K2's Impressive Benchmark Performance

Let's start with what the benchmarks tell us. Kimi K2's coding performance is genuinely impressive and SOTA for open-source models:

The model achieves 65.8% single-attempt accuracy on SWE-bench Verified, which tests a model's ability to solve real GitHub issues. To put that in perspective, this outperforms GPT-4.1 (54.6%) and trails only Claude Sonnet 4 among the top models. On the multilingual version of SWE-bench, Kimi K2 leads the pack with 47.3% accuracy.

On LiveCodeBench, Kimi K2 scores 53.7%, positioning it at the top of open-source models. The EvalPlus benchmark shows a state-of-the-art score of 80.3, significantly outperforming comparable models like DeepSeek-V3 and Qwen 2.5.

After analyzing over a week of production data from thousands of Cline users, Kimi K2 is delivering surprising results. In real-world diff editing tasks — the complex search-and-replace operations that challenge even frontier models — Kimi K2 is achieving failure rates as low as 3.3%, matching and occasionally outperforming Claude 4 Sonnet.

Kimi K2 was Trained for Tool-Calling Agents

Behind these impressive benchmarks is a unique training approach. Kimi K2's agentic capabilities come from large-scale synthetic data generation that simulates real-world tool use across thousands of scenarios. This includes training on MCP (Model Context Protocol) tools – the same protocol Cline uses for its tool ecosystem. This means Kimi K2 isn't just good at writing code; it's specifically optimized for the kind of tool-calling and multi-step execution that makes Cline a powerful agent.

Getting the Most from Kimi K2 in Cline

Testing confirms that Kimi K2 excels at tool calling and execution – critical capabilities for agentic coding. As an open-source model competing directly with the best proprietary options, it represents a significant step forward for accessible AI coding, priced at a fraction of the cost of Sonnet-4 ($0.14/$2.49 per million input/output tokens).

Based on our testing and community feedback, we see Kimi K2 as a strong model in Act Mode. While Kimi K2 has strong reasoning capabilities, its real strength appears to be in executing well-defined plans. Let a planning-optimized model (like Gemini 2.5 Pro with its massive context window) map out the strategy, then let Kimi K2 execute with its strong coding abilities.

That said, we encourage you to play with Kimi K2 in Cline and reach your own conclusions for how it's useful for you!

How to Use Kimi K2 in Cline

Option 1: The Official Cline Provider (Easiest Method)

For the most seamless experience, you can use the official Cline provider. This is the recommended approach.

Simply select cline:moonshotai/kimi-k2 from the model dropdown menu.

Option 2: The Free OpenRouter Endpoint (Great for Testing)

OpenRouter provides a free, rate-limited endpoint. This is perfect for trying out the model, but be aware that you may experience higher latency due to high demand.

Select openrouter/moonshotai/kimi-k2 from the model dropdown.

Ready to try Kimi K2? Download Cline and experience the latest in open-source coding AI.