Feature update Provisional 90% confidence first seen
Together AI expanded its fine-tuning service to support tool calling, reasoning, and vision-language model training capabilities. The company upgraded its infrastructure to handle models up to 1 trillion parameters and achieved up to 6× higher throughput for 100B+ parameter models, while supporting datasets up to 100GB in size.
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TLDRocket
3 August 2026
The story of AI in August 2026 is one of consolidation meeting enforcement. Alibaba's Qwen3.8-Max, a 2.4-trillion-parameter mixture-of-experts model with a million-token context window, arrives as a direct challenge to OpenAI and Anthropic's frontier offerings—priced at $2 per million input tokens, it's positioning itself as the capable-and-cheaper alternative that China's AI push has long promised. But the more consequential development is structural: enterprises are finally getting the plumbing to actually deploy these models. June, backed by Salesforce's Marc Benioff, raised $20 million to automate AI integration into legacy systems, scanning corporate infrastructure and generating deployment workflows without expensive consultant fees. This solves what's become clear as the real bottleneck—not model capability, but implementation friction in messy, heterogeneous corporate environments.
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