Gpt

TL;DR GPT-5.5 (“Spud”) is the first fully retrained base model since GPT-4.5, with architecture and pretraining reworked from scratch with agentic objectives in mind It takes the top spot on Terminal-Bench 2.0 (82.7%) and GDPval (84.9%), narrowly beating Anthropic’s Claude Mythos Preview on agentic coding benchmarks A 1M-token context window is new for OpenAI, enabling whole-codebase reasoning and long multi-step agent runs without context collapse Pricing is competitive ($5/$30 per million input/output tokens) but the strategic story is about OpenAI building an integrated super app - chat, code, browser agent - all driven by one model The gains are incremental, not a leap - but the full retraining signals OpenAI is betting the next two years on autonomous agentic work, not chat OpenAI released GPT-5.5 on April 23, 2026, weeks after GPT-5.4 and only months after GPT-5. The cadence is starting to feel relentless. Codenamed “Spud” internally, GPT-5.5 is the first fully retrained base model since GPT-4.5 - architecture, pretraining corpus, and agent-oriented objectives all reworked from scratch. ...

TL;DR An LLM is the underlying reasoning engine; a chatbot is the product experience wrapped around it - they are related but not the same thing LLMs excel at summarizing, rewriting, generating drafts, and coding, but should be treated as fast collaborators rather than infallible oracles The main model families are frontier models (GPT, Claude, Gemini), open-weight / self-hostable models (Llama), and product-specific assistants (ChatGPT, Cursor, Copilot) Choose the right tool for the job: chatbots for convenience and exploration, APIs for automation, coding-native tools for repo-aware work The market is now split between AI as a consumer product and AI as programmable infrastructure - understanding both layers makes the landscape far less confusing Most people still talk about chatbots and large language models as if they are the same thing. ...