Qwen: Qwen2.5 Coder 7B Instruct
Qwen2.5 Coder 7B Instruct is a compact, extremely affordable coding-focused model from Alibaba's Qwen team, but its reasoning and general performance benchmarks are limited. It may suit lightweight code-assistance tasks on a tight budget, but businesses requiring reliable output quality should look to more capable alternatives. Note that availability through Western business APIs may be more limited than with established providers.
Assessment date: March 12, 2026
Our methodology takes into account a range of factors including pricing, functionality, capabilities, benchmark performance, and real-world applicability. Rankings are reviewed and updated regularly as new models are released. Issues with our rankings? Contact us
Qwen2.5-Coder-7B-Instruct is a 7B parameter instruction-tuned language model optimized for code-related tasks such as code generation, reasoning, and bug fixing. Based on the Qwen2.5 architecture, it incorporates enhancements like RoPE, SwiGLU, RMSNorm, and GQA attention with support for up to 128K tokens using YaRN-based extrapolation. It is trained on a large corpus of source code, synthetic data, and text-code grounding, providing robust performance across programming languages and agentic coding workflows. This model is part of the Qwen2.5-Coder family and offers strong compatibility with tools like vLLM for efficient deployment. Released under the Apache 2.0 license.
Architecture
| Modality | Text → Text |
| Tokenizer | Qwen |
| Parameters | 7B |
Benchmark Scores
Evaluations
Benchmark data from Artificial Analysis and Hugging Face
Model Information
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.03 | $0.000030 |
| Output | $0.09 | $0.000090 |
Live Performance
Live endpoint metrics — refreshed every 30 minutes.
