New models, open releases and updates: flagship launches, open weights, and price and performance changes as they happen.
The deepseek-chat model has been upgraded to DeepSeek-V3 with no change to the interface. Existing integrations keep calling it with model=deepseek-chat; the full update is covered in the DeepSeek-V3 release post.
Why it matters: DeepSeek swapped deepseek-chat to DeepSeek-V3 while keeping the interface, so existing integrations can keep their current call parameters.
OpenAI launched an API distillation workflow on October 1, 2024, letting developers use outputs from GPT-4o and o1-preview to fine-tune cheaper models such as GPT-4o mini. The suite includes Stored Completions, Evals in beta, and fine-tuning; setting store:true auto-saves input-output pairs with no added latency, per the post. Pricing includes 2M free GPT-4o mini training tokens per day and 1M for GPT-4o through October 31; Evals are free up to 7 runs per week through year-end if shared with OpenAI.
Why it matters: Turns distillation into a built-in API step instead of a pipeline teams build themselves.
OpenAI released o1-preview and o1-mini on Sept. 12, 2024, with access for ChatGPT Plus, Team, and tier-5 API developers. The post cites 83% vs 13% on an IMO qualifier, 84 vs 22 on a jailbreak test, and says o1-mini is 80% cheaper than o1-preview. The tradeoff is clear: the API lacks function calling, streaming, and system messages, and the models do not yet support browsing or file and image uploads.
Why it matters: OpenAI's o1 models trade speed for deliberation, lifting math olympiad accuracy from GPT-4o's 13% to 83% and reaching Codeforces top 11%.
DeepSeek V2 Chat and DeepSeek Coder V2 have been merged and upgraded into DeepSeek V2.5. API users reach the new model through either deepseek-coder or deepseek-chat.
Why it matters: DeepSeek merged its chat and code models into V2.5 while keeping both existing API names so current call patterns still work.
The deepseek-chat model has been upgraded to DeepSeek-V2-0628. Reasoning improved, and role-play got a clear boost. HumanEval Pass@1 rose from 79.88% to 84.76%, MATH ACC@1 from 55.02% to 71.02%, and BBH from 78.56% to 83.40%.
Why it matters: The math benchmark gain is larger than the code and reasoning gains, and the win rate against GPT-4-0314 on Arena-Hard also improved.
The deepseek-coder model has been upgraded to DeepSeek-Coder-V2-0614, with a clear gain in coding ability. The company says its code generation, code understanding, code repair and code completion reach the level of GPT-4-Turbo-0409, with strong math and reasoning, while general ability matches DeepSeek-V2-0517.
Why it matters: DeepSeek upgrades its code model and benchmarks code generation, understanding, repair and completion against GPT-4-Turbo-0409.