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Together AI Compiler boosts inference throughput up to 2.7x on NVIDIA hardware

By PulseAugur Editorial · [1 sources] ·

Together AI has released benchmarks showcasing significant performance improvements with their compiler. When compared against optimized InferenceX configurations on NVIDIA B200 and B300 hardware, Together Compiler demonstrated up to 2.7 times higher throughput for various models. Specifically, Kimi K3 saw a 2.7x improvement, GLM-5.3 and DeepSeek V4.1 Flash both achieved 1.8x, and MiniMax M3.1 Flash reached 1.5x higher throughput. AI

IMPACT Demonstrates significant efficiency gains for AI inference, potentially lowering operational costs and increasing deployment speed.

RANK_REASON The item details benchmark results comparing a compiler's performance on specific hardware, which falls under research milestones. [lever_c_demoted from research: ic=1 ai=0.7]

Read on X — Together (inference / OSS) →

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

Together AI Compiler boosts inference throughput up to 2.7x on NVIDIA hardware

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The item details benchmark results comparing a compiler's performance on specific hardware, which falls under research milestones. [lever_c_demoted from research: ic=1 ai=0.7]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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infra, product
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High
Clearly on-topic for AI-industry coverage.
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3 days old
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COVERAGE [1]

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

    Up to 2.7× more throughput at the same speed per user.

    Up to 2.7× more throughput at the same speed per user. In our benchmarks comparing Together Compiler vs. the best InferenceX configs on NVIDIA B200 and B300: → Kimi K3: 2.7× → GLM-5.3: 1.8× → DeepSeek V4.1 Flash: 1.8× → MiniMax M3.1 Flash: 1.5× Read more: https://t.co/5QUdF70n…

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