Well, Actually: A 22 Billion Parameter Model You Can Run on Your Own Hardware Now Beats OpenAI's GPT-4o Mini
Mistral has released Mistral Small 3.1, an open-weight model with 22 billion parameters designed for local deployment or affordable cloud GPU usage. It outperforms GPT-4o Mini on standard benchmarks in coding, mathematics, and reasoning tasks. This eliminates the need for proprietary API access.
This teaches you that open-weight models have reached parity with closed commercial offerings on practical tasks. Your workflow should now include evaluating whether local deployment reduces latency, cost, and dependency on external services. The 'open source is inferior' assumption is, well, outdated.
Mistral, a French AI company, developed and released this model. Their announcement specifies the 22B parameter count and benchmark categories where it surpasses GPT-4o Mini.
Step 1: Install Ollama from ollama.com, a tool for running local models. Step 2: Open your terminal and run 'ollama run mistral-small', which downloads the model automatically. Step 3: Ask it a coding question you previously sent to ChatGPT, compare the responses, and note the absence of API latency or usage limits.