Comprehensive side-by-side LLM comparison
Qwen3-VL-235B-A22B offers 134.3K more tokens in context window than DeepSeek-R1. Qwen3-VL-235B-A22B is $1.74 cheaper per million tokens. Qwen3-VL-235B-A22B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
DeepSeek
DeepSeek-R1, released by DeepSeek on January 20, 2025, is a large reasoning model with 671 billion total parameters (37 billion active in its MoE architecture) designed for extended chain-of-thought reasoning. It features a 128K token context window and demonstrated strong performance on mathematics, coding, and scientific reasoning benchmarks at its release. DeepSeek-R1 targets complex analytical tasks, competitive programming, and applications requiring deep deliberative reasoning under an open 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.
8 months newer

DeepSeek-R1
DeepSeek
2025-01-20
Qwen3-VL-235B-A22B
Alibaba / Qwen
2025-09-23
Cost per million tokens (USD)
DeepSeek-R1
Qwen3-VL-235B-A22B
Context window and performance specifications
Available providers and their performance metrics
DeepSeek-R1
DeepSeek
Qwen3-VL-235B-A22B
DeepSeek-R1
Qwen3-VL-235B-A22B
DeepSeek-R1
Qwen3-VL-235B-A22B
OpenRouter