According to a recent LinkedIn post from Together AI, the company is making the Qwen3.5 native multimodal large language model available on its platform. The post highlights capabilities across text, images, and video, emphasizing use cases in advanced reasoning, coding support, and visual understanding for production workloads.
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The LinkedIn post also points to efficiency gains via hybrid architectures, noting faster decoding speeds with a 17B-parameter configuration and broad language coverage across more than 200 languages. For investors, this suggests Together AI is strengthening its AI infrastructure stack and model catalog, potentially increasing usage from AI-native customers and enhancing its competitive position against other inference and AI-cloud providers.
The post further indicates that Qwen3.5 is available on Together AI’s serverless and dedicated infrastructure, with a referenced 99.9% service-level target aimed at production deployments. If adopted by enterprise and global developers, this integration could drive higher consumption-based revenue, deepen partnerships with leading model developers, and support Together AI’s ambitions in the multimodal AI and inference-as-a-service markets.