July 2026 Summaries

Provisioned Throughput, a new offering from Together AI, provides reserved inference capacity for open models with token-based pricing and a 99% uptime SLA, aimed at companies seeking cost-effective AI solutions without compromising reliability. By offering a middle ground between serverless inference and dedicated inference, it allows businesses to use pre-optimized models with the predictability of guaranteed capacity, significantly reducing costs—up to 90% lower than proprietary alternatives like Claude Opus 4.8. Available for models such as MiniMax M3 and GLM-5.2, with capacity across North America and EMEA, it allows companies to optimize their inference spend according to traffic patterns without the complexity of managing infrastructure. As businesses increasingly adopt open models for diverse tasks like coding, finance, and marketing, Together AI's Provisioned Throughput provides a simplified API and pricing model, enabling them to shift from closed APIs and benefit from frontier open models' performance and cost advantages.

Together AI was founded with the vision of making generative AI widely accessible rather than dominated by a few corporations, and it has since developed a full-stack AI platform grounded in open-source principles and advanced research. The company has now secured $800 million in Series C funding from prominent investors such as Aramco Ventures, NVIDIA, and Salesforce Ventures, along with commitments for substantial compute capacity to support future growth. As AI becomes integral to production infrastructure, companies face economic challenges with proprietary models, which Together AI addresses by providing open-weight models that are cost-effective while maintaining high performance. Their platform has proven to deliver significant cost reductions, as demonstrated by companies like Decagon. The success of Together AI is driven by continuous innovation in its research-to-production pipeline, offering optimized solutions like FlashAttention-4 and Together Megakernel, which enhance the performance and economics of AI production. The company emphasizes the importance of the entire AI stack, including models, kernels, and training infrastructure, to provide comprehensive generative AI capabilities, and it continues to expand its influence in the global open-source AI ecosystem while actively recruiting talent to support its mission.