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Nvidia announced the Rubin CPX, a specialized GPU designed for the prefill phase of AI inference with 20 PFLOPS of FP4 compute but only 2TB/s memory bandwidth, compared to the R200's 33.3 PFLOPS and 20.5TB/s. The Rubin CPX uses 128GB of cheaper GDDR7 memory instead of HBM, reducing memory costs by more than 50% and total production costs significantly. Three new Vera Rubin rack configurations now available in 2026 will combine R200 and Rubin CPX GPUs for disaggregated inference serving, forcing competitors like AMD to redesign their entire roadmaps to develop competing prefill-specialized chips.
Together AI expanded its Fine-Tuning Platform to support training of large language models with over 100 billion parameters, including recent releases from DeepSeek, Qwen, and Meta. The platform now supports context lengths of up to 131,000 tokens for some models at no additional cost, and enables developers to fine-tune models from the Hugging Face Hub and save outputs directly back to it. These additions allow developers to customize state-of-the-art models for domain-specific tasks with lower inference costs and latency.
Together AI hired Mahadev Konar as Senior Vice President of Infrastructure Engineering. Konar previously served as VP of Infrastructure at Meta, where he led teams responsible for large-scale compute systems. The hire aims to strengthen Together AI's capabilities in building and managing GPU infrastructure for AI workloads.
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