Qwen 2.5 72B
AlibabaQwen 2.5 72B by Alibaba costs $0.4/M input, $1.2/M output with 128K context window. Updated February 2026. Compare with GPT-5, Claude, Gemini & 40+ models.
Input Price
$0.40
per 1M tokens
Output Price
$1.20
per 1M tokens
Context Window
128K
tokens
Specifications
| Provider | Alibaba |
| Model ID | qwen-2-5-72b |
| Input Price | $0.4 / 1M tokens |
| Output Price | $1.2 / 1M tokens |
| Context Window | 128K tokens |
| Max Output | 8K tokens |
| Capabilities | textfunction_calling |
| Release Date | 2025-09 |
| Notes | Open-source. Competitive with Llama 3.3 70B. |
Monthly Cost Estimates
Estimated monthly costs based on different daily usage levels (assuming 50% input / 50% output split).
| Daily Tokens | Monthly Cost | Annual Cost |
|---|---|---|
| 10K | $0.24 | $2.88 |
| 50K | $1.20 | $14.40 |
| 100K | $2.40 | $28.80 |
| 500K | $12.00 | $144.00 |
| 1.0M | $24.00 | $288.00 |
About Qwen 2.5 72B
Qwen 2.5 72B is a large language model by Alibaba. It features a 128K token context window with up to 8K tokens of output per request. The model supports 2 capabilities: text, function_calling.
At $0.4 per million input tokens and $1.2 per million output tokens, Qwen 2.5 72B is positioned as a cost-effective option in the Alibaba lineup. Use our Token Counter to estimate how many tokens your prompts use, and our Pricing Calculator to compare costs across all models.
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FAQ
How much does Qwen 2.5 72B cost?
Qwen 2.5 72B costs $0.4 per million input tokens and $1.2 per million output tokens. For a typical workload of 100K tokens/day, expect approximately $3.00/month.
What is Qwen 2.5 72B's context window?
Qwen 2.5 72B supports a context window of 128K tokens. This means your combined input prompt and output response can be up to 128K tokens. The maximum output per response is 8K tokens.
Is Qwen 2.5 72B good for my use case?
Qwen 2.5 72B supports text, function_calling. As a budget-friendly model, it works well for high-volume tasks like classification, summarization, and simple generation. Use our Pricing Calculator to compare with alternatives.