
OpenAI is launching a preview of a sped up version of its latest, most powerful model, in an effort to court enterprise users.
OpenAI has launched a new mode called Ultrafast for its latest model that processes information at 14 times the standard speed, generating up to 750 output tokens per second. The company positions this as progress toward delivering more useful work per second while maintaining the power of its most advanced model, addressing the historical tradeoff where faster speeds typically required using smaller or more specialized models. The feature is currently available in preview to a limited group of customers and is powered by a partnership with chipmaker Cerebras, with plans to expand access as capacity grows. OpenAI suggests Ultrafast can be deployed across corporate workflows including incident response, customer service, financial market analysis, and e-commerce, while competitors like Anthropic offer similar accelerated versions of their own models.

In this tutorial, we implement an end-to-end supervised fine-tuning pipeline for the XYZ-Aquila-SFT dataset, Hugging Face Transformers, PyTorch, and PEFT. We stream and inspect the dataset, parse multi-turn tool-use trajectories, extract structured tool calls, analyze corpus characteristics, and preserve embedded reasoning and observation patterns. We then convert tool schemas between message-embedded and structured formats, render Qwen-compatible ChatML with assistant-only loss masking, prepar
Meta released Glimmer this week, an open-weight AI model anyone can download and run on their own hardware — a contrast to Muse Spark, the company’s more powerful model that stays locked behind its own APIs. The release landed alongside a letter from Mark Zuckerberg arguing AI should be “for everyone” rather than controlled by a handful of labs, but as Equity’s […]

Z.ai just released GLM-5.3. GLM-5.3 runs on the same 743B base model as GLM-5.2. Every reported gain comes from scaled post-training: more task environments, more environment types, longer training. The results land in two places. Coding jumps most on the longest-horizon benchmarks, with Terminal-Bench 3.0 moving from 4.6 to 28.3. Cybersecurity moved further than Z.ai says it expected, with CyberGym reaching 84.5%. Weights are not public yet. Is It Deployable? Partially, GLM-5.3 is live
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