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Together AI details latency optimization with NVIDIA Blackwell

By PulseAugur Editorial · [1 sources] ·

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

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

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