Comprehensive side-by-side LLM comparison
Qwen3-Coder-480B offers 6.1K more tokens in context window than Kimi K2. Qwen3-Coder-480B is $1.60 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
Moonshot AI
Kimi K2, released by Moonshot AI on July 11, 2025, is an open-weight Mixture-of-Experts large language model with 1 trillion total parameters and 32 billion active parameters per inference. It features a 256K token context window (expanded from 128K in an September 2025 update) and demonstrated strong performance on agentic coding benchmarks. Kimi K2 targets software engineering agents, tool-use workflows, and open-source deployments under a modified MIT license.
Alibaba / Qwen
Qwen3-Coder-480B-A35B-Instruct, released by Alibaba's Qwen team on July 22, 2025, is a Mixture-of-Experts large language model with 480 billion total parameters and 35 billion active parameters per inference, specifically designed for agentic coding tasks. It features a 256K token native context window (extendable to 1M tokens with extrapolation) and demonstrated competitive performance on agentic coding, browser automation, and tool-use benchmarks. Qwen3-Coder-480B targets automated software engineering, multi-step code agents, and open-source coding deployments under the Apache 2.0 license.
11 days newer
Kimi K2
Moonshot AI
2025-07-11
Qwen3-Coder-480B
Alibaba / Qwen
2025-07-22
Cost per million tokens (USD)
Kimi K2
Qwen3-Coder-480B
Context window and performance specifications
Available providers and their performance metrics
Kimi K2
Moonshot AI
Qwen3-Coder-480B
OpenRouter
Kimi K2
Qwen3-Coder-480B
Kimi K2
Qwen3-Coder-480B