Comprehensive side-by-side LLM comparison
GPT-4.1 nano offers 810.0K more tokens in context window than Qwen3-235B-A22B. Both models have similar pricing. GPT-4.1 nano supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
OpenAI
GPT-4.1 nano is OpenAI's smallest member of the GPT-4.1 family, released in April 2025 alongside GPT-4.1 and GPT-4.1 mini as the latency-optimized, cost-minimized option for high-throughput applications. Positioned below GPT-4.1 mini in both size and cost, it was designed for use cases where speed and affordability dominate over raw capability — including tool calling, intent classification, short-form instruction following, and retrieval-augmented lookup tasks. Unlike its larger siblings, it supports fine-tuning, making it a practical candidate for task-specific customization at scale without incurring the cost of fine-tuning larger models.
Alibaba / Qwen
Qwen3-235B-A22B, released by Alibaba's Qwen team on April 28, 2025, is a Mixture-of-Experts large language model with 235 billion total parameters and 22 billion active parameters per inference. It features a 256K token context window, hybrid thinking capabilities (both reasoning and direct generation modes), and was trained on 36 trillion tokens across 119 languages. Qwen3-235B targets complex reasoning, multilingual tasks, and open-source deployments under the Apache 2.0 license.
14 days newer

GPT-4.1 nano
OpenAI
2025-04-14
Qwen3-235B-A22B
Alibaba / Qwen
2025-04-28
Cost per million tokens (USD)
GPT-4.1 nano
Qwen3-235B-A22B
Context window and performance specifications
GPT-4.1 nano
2024-06
Available providers and their performance metrics
GPT-4.1 nano
OpenAI
Qwen3-235B-A22B
GPT-4.1 nano
Qwen3-235B-A22B
GPT-4.1 nano
Qwen3-235B-A22B
OpenRouter