Pricing, Performance & Features Comparison
google/gemma-2-9b-it is a text-to-text, decoder-only large language model optimized for tasks such as question answering, summarization, and reasoning. It was trained on 8 trillion tokens with 9 billion parameters, aiming for efficient inference and strong performance despite its size. Its design supports flexible deployment for applications like chatbots, code generation, and research in NLP.
Devstral Medium 2507 is a high-performance, code-centric large language model designed for agentic coding capabilities and enterprise use. It features a 128k token context window and achieves a 61.6% score on SWE-Bench Verified, outperforming several commercial models like Gemini 2.5 Pro and GPT-4.1. The model excels at code generation, multi-file editing, and powering software engineering agents with structured outputs and tool integration.