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Home/Models & Labs
Models & Labs

Together AI's Inference Engine Outperforms Competitors

Together AI Blog·May 19, 2026·high confidence

Why it matters

  • →Together AI's engine significantly improves performance in high-concurrency coding agent workloads.
  • →The benchmark addresses real-world production challenges, offering more relevant insights than traditional single-user tests.
  • →This advancement can lead to substantial cost savings and efficiency gains for developers using coding agents.
Together AI's Inference Engine Outperforms Competitors
©Together AI Blog

Together AI has released benchmark results showing its Inference Engine outperforms competitors in coding agent workloads. The engine delivers 31% more tokens per second than the next fastest open-source engine, thanks to optimizations like ThunderMLA and custom kernel rewrites. The benchmark simulates real-world production scenarios with high concurrency and long input contexts. This advancement allows coding agents to manage higher loads more efficiently, reducing latency and operational costs.

Read original

The story around this

Earlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.

CodeBuff: New Open-Source AI Coding Agent — Lev Selector1Live Demo of Multi-Agent Coding Workflows — Cole Medin2Key Requirements for Production-Ready AI Agents — Sam Witteveen3Parallel Coding Agents Enhance AI Development Workflow — Cole Medin4Cursor AI Introduces Agent-First Coding — Lev Selector5

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MIT Develops Fast Tool for AI Power Estimation — MIT News AI6AlphaEvolve: Scaling AI Impact Across Industries — Google DeepMind7Hugging Face Launches Open Agent Leaderboard — Hugging Face Blog8Together AI's Inference Engine Outperforms CompetitorsBenchmarking Open Models for Agentic Use — Hugging Face Blog9MIT and Microsoft Enhance AI Workflow Efficiency — MIT News AI10Together AI Enhances Model Inference Configuration — Together AI Blog11ThunderAgent Boosts Agentic Inference Efficiency — Together AI Blog12OpenAI's Coding Agents Boost Research Speed — OpenAI13Mar 6You are hereSep 6

How we got here

  1. 1
    CodeBuff: New Open-Source AI Coding Agent

    Lev Selector · March 6, 2026 · Related

  2. 2
    Live Demo of Multi-Agent Coding Workflows

    Cole Medin · April 2, 2026 · Related

  3. 3
    Key Requirements for Production-Ready AI Agents

    Sam Witteveen · April 15, 2026 · Related

  4. 4
    Parallel Coding Agents Enhance AI Development Workflow

    Cole Medin · April 23, 2026 · Related

  5. 5
    Cursor AI Introduces Agent-First Coding

    Lev Selector · April 24, 2026 · Related

  6. 6
    MIT Develops Fast Tool for AI Power Estimation

    MIT News AI · April 27, 2026 · Related

  7. 7
    AlphaEvolve: Scaling AI Impact Across Industries

    Google DeepMind · May 6, 2026 · Related

  8. 8
    Hugging Face Launches Open Agent Leaderboard

    Hugging Face Blog · May 18, 2026 · Related

What happened next

  1. 9
    Benchmarking Open Models for Agentic Use

    Hugging Face Blog · June 18, 2026 · Related

  2. 10
    MIT and Microsoft Enhance AI Workflow Efficiency

    MIT News AI · June 25, 2026 · Related

  3. 11
    Together AI Enhances Model Inference Configuration

    Together AI Blog · July 29, 2026 · Same story

  4. 12
    ThunderAgent Boosts Agentic Inference Efficiency

    Together AI Blog · July 29, 2026 · Same story

  5. 13
    OpenAI's Coding Agents Boost Research Speed

    OpenAI · September 6, 2026 · Related

Apple is finally unlocking its AI suite for Chinese users with the iOS 27.3 beta, marking a significant regulatory milestone after months of approval delays. The rollout relies on Alibaba’s Qwen model rather than OpenAI, integrating features like notification summaries and visual intelligence directly into the OS. By sidestepping the new Siri in favor of established text and image tools, Apple is prioritizing immediate utility over the full generative experience. This move effectively brings Apple’s AI capabilities to a massive new market, albeit with localized constraints that distinguish it from the global release.

The Verge AI·Oct 30, 2026
Google Releases Gemini 4 Carbon for Cost-Efficient Inference© Matt Wolfe
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Google Releases Gemini 4 Carbon for Cost-Efficient Inference

Google launched Gemini 4 Carbon, a new model variant aimed at providing high performance at a lower cost for inference tasks.

Matt Wolfe·Oct 30, 2026