Ok I was wrong – 5.4 Mini and 5.4 Nano are out. Mini is 1/3 of 5.4 and nano is 1/10 the price
LLMS
-
OpenAI Releases GPT-5.4 Mini and Nano Models
By
–
BREAKING : OpenAI released GPT-5.4 Mini and GPT-5.4 Nano on the APIs. A mini version is also available on ChatGPT and Codex apps. Check intelligence
-
OpenAI Launches GPT-5.4-Nano and Mini Models on Poe
By
–
OpenAI's GPT-5.4-Nano and GPT-5.4-Mini are now live on Poe. GPT-5.4-Nano is a strong fit for fast, high-volume tasks like summarizing transcripts, labeling tickets, rewriting content, quick RAG answers, and running @openclaw flows with Poe where latency and cost matter most.
-
GPT-5.4 nano now available on OpenAI API
By
–
GPT-5.4 nano is also available starting today in the API. [Translated from EN to English]
-
OpenAI Launches GPT-5.4 mini, Twice as Fast
By
–
GPT-5.4 mini is available today in ChatGPT, Codex, and the API. Optimized for coding, computer use, multimodal understanding, and subagents. And it's 2x faster than GPT-5 mini. https://openai.com/index/introducing-gpt-5-4-mini-and-nano/ [Translated from EN to English]
-
Princeton Review Highlights Persistent LLM Reliability Issues
By
–
BREAKING: Reliability, which I have been harping on here since 2019, continues to be deep problem, even with the latest models. A new @Princeton review below offers a taxonomy of some of the many ways in which reliability continues to haunt LLMs seven years and a trillion
-
Open Models Panel at GTC: Industry Leaders Discuss Future
By
–
Open Models Panel at GTC with Harrison & Jensen: Join us tomorrow, Wednesday March 18th at 12:30pm at GTC for “Open Models: Where We Are and Where We’re Headed”, a panel featuring Harrison, Jensen, and the CEOs of Cursor, Thinking Machines Lab, Perplexity, and more. Add it to
-
Framework-specific challenges with VRAM, disk, and quantization options
By
–
Thanks for the feedback. The only problem with VRAM, disk, and quant options is that they are framework specific. Disk is maybe the most obvious or feasible one for a given precision (like bf16)
-
LLM Slop: Repetitive Words Across Different Contexts
By
–
one thing people miss about LLM slop is the slop is NOT in the actual words. it’s that the same words get used over and over in very different contexts. anything can be slop
-
Inference VRAM Complexity Depends on Framework Implementation
By
–
I was thinking about inference VRAM as well, but this one is so tricky because it depends on the implementation/framework one is using