Comprehensive side-by-side LLM comparison
Qwen3-VL-235B-A22B offers 6.1K more tokens in context window than Kimi K2. Qwen3-VL-235B-A22B is $2.10 cheaper per million tokens. Qwen3-VL-235B-A22B supports multimodal inputs. 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-VL-235B-A22B, released by Alibaba's Qwen team in September 2025, is a natively multimodal Mixture-of-Experts large language model with 235 billion total parameters and 22 billion active parameters. It features a 256K token context window (with extrapolation to 1M tokens), native support for text, image, and video input, and joint visual-textual reasoning capabilities. Qwen3-VL-235B targets complex visual reasoning, video understanding, and multimodal agentic tasks under the Apache 2.0 license.
2 months newer
Kimi K2
Moonshot AI
2025-07-11
Qwen3-VL-235B-A22B
Alibaba / Qwen
2025-09-23
Cost per million tokens (USD)
Kimi K2
Qwen3-VL-235B-A22B
Context window and performance specifications
Available providers and their performance metrics
Kimi K2
Moonshot AI
Qwen3-VL-235B-A22B
OpenRouter
Kimi K2
Qwen3-VL-235B-A22B
Kimi K2
Qwen3-VL-235B-A22B