OpenAI just launched two new embedding models—text-embedding-3-small and large—bringing stronger retrieval benchmarks and adjustable dimensions to cut storage costs. It also slashed GPT-3.5 Turbo input pricing by 50% and shipped an updated GPT-4 Turbo preview to tackle code completion laziness. Why it matters: Developers get better RAG retrieval and cheaper tokens across the board.
OpenAI just launched fine-tuning for GPT-3.5 Turbo, allowing developers to customize models with their own proprietary data. Early testers managed to shrink prompt sizes by up to 90% by baking instructions directly into the model, speeding up API calls while slashing operational costs. Why it matters: Developers can now achieve consistent, tailor-made outputs without blowing their token budget.
OpenAI just made the GPT-4 API generally available to all paying developers, rolling out the 8K context model right away. It is also sunsetting older completion models by January 4, 2024, pushing everyone toward the structured Chat Completions API that now handles 97% of its GPT traffic.
OpenAI just overhauled its Chat Completions API with native function calling, letting GPT-4 and GPT-3.5 reliably output structured JSON to trigger external tools. The update also introduces a 16k context window for GPT-3.5 Turbo and slashes embedding costs by 75%. Why it matters: developers can now build real-world agents and database workflows without hacking fragile prompts.
OpenAI just made GPT-3.5 Turbo and Whisper available via API, slashing ChatGPT costs by 90% down to $0.002 per 1,000 tokens. Whisper speech-to-text runs at $0.006 per minute, and OpenAI will no longer train on developers' API data by default.
