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Qwen2.5 72B InstructOPEN
Qwen2.5 72B is the latest series of Qwen large language models.
Prices update automatically — checked daily against provider list prices.
- $0.37 per 1M tokens, assuming 3 input for 1 output the convention used by Artificial Analysis
- cheaper than 51% of the 191 open-weight models tracked here
- 19 of 51 Alibaba models tracked here, from cheapest
Benchmarks & performance
Independent benchmark scores for Qwen2.5 72B Instruct, measured by Artificial Analysis. Higher is better.
For the same budget, Qwen2.5 72B Instruct delivers 3.1 times more capability. Open weights also mean you can self-host it and pay nothing per token.
Models at this level cost $0.2 per 1M tokens (median of 27) — this one costs $0.37.
Cheaper and better on this index: GLM 5.3 Flash · GPT-5.6 Luna (batch) · DeepSeek V4 Flash 0731 and 43 more
About this model
Qwen2.5 72B Instruct is an open-weight AI model by Alibaba. You can download and self-host it for free; the prices below are hosted-API list prices, tracked daily, for when you prefer convenience over self-hosting.
Frequently asked questions
What is Qwen2.5 72B Instruct?
Qwen2.5 72B Instruct is an AI language model from Alibaba. It is open-weight: you can download it and run it on your own hardware, for free. It scores 9.4 on the Artificial Analysis intelligence index.
Is Qwen2.5 72B Instruct free?
The weights are free and open — you can self-host Qwen2.5 72B Instruct and pay nothing per token. If you prefer a hosted API, list prices are $0.36 per million input tokens and $0.4 per million output tokens.
What is Qwen2.5 72B Instruct good at?
Independent benchmarks from Artificial Analysis give it GPQA 49.1%, MMLU-Pro 72%, Humanity's Last Exam 3.6%, Long Context Reasoning 20%, LiveCodeBench 27.6%, SciCode 26.7%, MATH-500 85.8%, AIME 16%, AIME 2025 14%, IFBench 36.9%, τ²-Bench 34.5%, Terminal-Bench Hard 4.5%. It is particularly used for mathematical reasoning.
Can I self-host Qwen2.5 72B Instruct?
Yes. Qwen2.5 72B Instruct has open weights, so you can download it and run it on your own GPU or server with tools like Ollama, vLLM or llama.cpp — with no per-token cost.