According to a recent LinkedIn post from Together AI, the company is highlighting the availability of Qwen3.7-Max on its serverless inference platform. The post positions the model as geared toward “AI natives,” emphasizing capabilities for long-duration coding, reasoning, and autonomous workflows.
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The LinkedIn post underscores technical benchmarks such as maintaining coherent execution over a 35-hour autonomous kernel optimization run and leading performance on Terminal-Bench 2.0-Terminus for terminal-based engineering tasks. It also points to strengths in tool orchestration, office automation, spreadsheet reasoning, and a 1M-token context window designed for extended, persistent agent workflows.
For investors, the post suggests Together AI is deepening its portfolio of high-end inference offerings aimed at complex, agentic use cases, which may enhance its appeal to enterprise and developer customers with advanced automation needs. If adoption of Qwen3.7-Max on Together’s serverless infrastructure scales, this could support higher usage-based revenue, strengthen the firm’s competitive position in AI infrastructure, and increase switching costs for customers building on its stack.