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Together AI details latency optimization with NVIDIA Blackwell

Together AI has detailed its approach to optimizing inference latency, highlighting the integration of various NVIDIA technologies with their own platform. Their system, Together ATLAS, leverages NVIDIA Blackwell, CUDA, TensorRT-LLM, and Dynamo, along with custom kernels, to achieve sub-100ms response times for users. This optimization is crucial for enabling faster inference and long-context code generation. AI

IMPACT Demonstrates how existing hardware and software can be integrated for improved AI inference performance.

RANK_REASON A company details its use of existing hardware and software for optimization, rather than a new release or significant industry event.

Read on X — Together (inference / OSS) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Together AI details latency optimization with NVIDIA Blackwell

COVERAGE [1]

  1. X — Together (inference / OSS) TIER_1 English(EN) · togethercompute ·

    This is what latency optimization looks like below the API 👇

    This is what latency optimization looks like below the API 👇 Together ATLAS, NVIDIA Blackwell, CUDA, TensorRT-LLM, Dynamo, and custom kernels all working together to make inference faster for users. Proud of @realDanFu and our team!