DeepInfra has announced the release of a new "Turbo" version of its Qwen3-Coder model, significantly reducing its operational cost and improving speed. The company stated that the new iteration is priced at $0.30 per million input tokens and $1.20 per million output tokens, making it more accessible for developers and enterprises. This development aims to enhance the efficiency of one of the leading open-source coding models available on the DeepInfra platform.
According to a tweet from DeepInfra, the Qwen3-Coder Turbo maintains "same accuracy (within 1% of original)" while being "2x faster & cheaper." This optimization positions the model as a highly competitive solution for various coding-related artificial intelligence tasks. The focus on speed and affordability without compromising performance is a strategic move in the rapidly evolving landscape of large language models.
Qwen3-Coder is part of the Qwen series of large language models, developed by Alibaba Cloud, known for its strong performance in agentic coding tasks. The model, particularly its 480B-A35B-Instruct variant, is recognized for its capabilities in function calling, tool use, and long-context reasoning, often drawing comparisons to models like Claude Sonnet. Its Mixture-of-Experts (MoE) architecture contributes to its efficiency by activating only a subset of its parameters during inference.
DeepInfra specializes in hosting and serving a wide array of machine learning models, providing infrastructure that enables developers to integrate advanced AI capabilities into their applications. By offering optimized versions like Qwen3-Coder Turbo, DeepInfra aims to cater to the growing demand for powerful yet cost-effective AI tools in software development and automation. This move underscores the ongoing trend of making high-performance open-source models more economically viable for broader adoption.
The introduction of the Turbo version reflects a broader industry push towards optimizing AI model deployment for practical, real-world applications where speed and cost are critical factors. As the market for coding-specific AI models continues to expand, DeepInfra's enhanced Qwen3-Coder is expected to attract users seeking a balance of cutting-edge performance and operational efficiency.