Qwen2.5-Math 7B Instruct via Alibaba (China)
Specifications
Context Window
4,096 tokens
Release Date
2024-09
Capabilities
Tool callingTemperature
Availability
Open Weights
Model Overview
Alibaba Cloud (China) offers the Qwen family of models for the domestic Chinese market, providing optimized access within China's network infrastructure.
Qwen2.5-Math 7B Instruct is a qwen-family model by Alibaba (China) with a 4k token context window and up to 3k output tokens. It is priced at $0.1440/1M input tokens and $0.2870/1M output tokens.
Key capabilities include: tool calling, temperature. It can call external tools and functions for agentic workflows.
Details
ProviderAlibaba (China)
Model IDqwen2-5-math-7b-instruct
Familyqwen
Release Date2024-09
Last Updated2024-09
Knowledge Cutoff2024-04
Context Window4,096 tokens
Max Output3,072 tokens
Input Cost / 1M$0.1440
Output Cost / 1M$0.2870
More models from Alibaba (China)
Frequently Asked Questions
How much does Qwen2.5-Math 7B Instruct cost to use?
Qwen2.5-Math 7B Instruct is priced at $0.1440/1M input tokens and $0.2870/1M output tokens. Use the cost estimator on this page to calculate your expected spend based on your usage pattern.
What is a token and how does it relate to pricing?
A token is a chunk of text — roughly ¾ of a word in English. For example, "chatbot" is two tokens. LLM API pricing is based on the number of tokens you send (input) and receive (output). Input tokens include your prompts, uploaded documents, and images, while output tokens are the model's generated responses.
Why are input and output tokens priced differently?
LLM providers charge separately for input and output tokens. Output tokens are typically more expensive because generating each token requires more compute — the model must run a full forward pass for every token it produces, while input tokens are processed in parallel.
What is the context window of Qwen2.5-Math 7B Instruct?
Qwen2.5-Math 7B Instruct supports a context window of 4,096 tokens. This is the maximum number of tokens (input + output combined) the model can process in a single request. Larger context windows let you send longer documents or maintain longer conversation histories.
How accurate is this cost estimation?
This tool provides a ballpark estimate based on per-token pricing. Actual costs may differ due to prompt caching, batched API calls, volume discounts, reasoning token overhead, and provider-specific billing rules. Use it for budgeting and comparison, not as an invoice prediction.
How does Qwen2.5-Math 7B Instruct pricing compare to other models?
You can compare Qwen2.5-Math 7B Instruct with other models on our LLM API pricing calculator. Use the cost estimator to see side-by-side cost breakdowns across different providers and models to find the best fit for your budget and requirements.
What factors affect my total API cost?
Your total cost depends on several factors: the number of API calls you make, the length of your prompts (input tokens), the length of generated responses (output tokens), whether you use features like image or document uploads (which add input tokens), and any provider-specific charges for caching or batch processing.
How can my team use Qwen2.5-Math 7B Instruct via API?
You can connect your own Alibaba (China) API key and give your entire team access to Qwen2.5-Math 7B Instruct through TypingMind Teams. It lets you build a unified AI workspace where team members can use Qwen2.5-Math 7B Instruct and other models — without needing their own API keys. You stay in control of usage limits, costs, and permissions, all from a single dashboard.
