Search: “together-ai--x”

I'm finally launching this agent tomorrow! Will be free, open source, and powered exclusively by open models on @togethercompute. Will also drop a full guide on how it works! Building an agent that ca

Anthropic's Claude 3.5 Sonnet (M3) model features sparse attention mechanisms, 1 million token context length, and multimodal capabilities, with Together AI optimizing the serving infrastructure to en

Amazing deep dive from the @togethercompute team on serving MiniMax M3 in production. M3 with its 1M context, native multimodality and MiniMax Sparse Attention requires real work across paged decode,

This post likely provides technical insights and optimization strategies for running or fine-tuning the MiniMax M3 model efficiently, discussing performance enhancements and practical implementation t

Everyone talks about 1M context. The harder part is making 1M context actually usable. Serving MiniMax M3 required optimizing for long-context, multimodal, and agentic workloads simultaneously. Excite

First technical Deepdive on M3 on the internet😎 MiniMax-M3 combines 1M context, native multimodality, and MiniMax Sparse Attention. The next layer is serving it efficiently: KV-block-major sparse atte

Together AI announced a live event featuring MiniMax AI, likely discussing a partnership, integration, or collaborative development initiative. The announcement was made via X Spaces, Twitter's audio

MiniMax-M3 combines 1M context, native multimodality, and MiniMax Sparse Attention. The next layer is serving it efficiently: KV-block-major sparse attention, paged MSA decode, optimized index scoring

We wrapped a live session on M3 yesterday with the @togethercompute team & our researchers @zpysky1125 and @HaohaiSun A few highlights 🧵 1. MSA (MiniMax Sparse Attention) is the star ⭐️. Unlike CSA/HC

Make sure to join our live Spaces chat on MiniMax M3 starting in 4 hours. You can pre-submit questions by replying to this tweet. MiniMax M3 is live and Together AI is powering its inference 🚀 Tomorro

Minimax M3 is a remarkable model in many ways, but esp for inference efficiency. Minimax model designers and @togethercompute inference team will discuss it tomorrow live. MiniMax M3 is live and Toget

MiniMax M3 is live and Together AI is powering its inference 🚀 Tomorrow at 6pm PT we're going live on X Spaces with the teams behind the model and the infrastructure to give you a deep dive. https://x

See you tomorrow night. Come with questions. We're going LIVE tomorrow with @togethercompute 🔥. @zpysky1125 is pulling back the curtain on M3: sparse attention, 1M context, all of it. You don't want t

Speakers: Pengyu Zhao, Head of Research at MiniMax Haohai Sun, Research Scientist at MiniMax Ce Zhang, Founder/CTO at Together Yineng Zhang, Senior Director at Together Dan Fu, VP of Kernels at Togeth

We'll get into @MiniMax_AI M3's model performance, the MSA architecture and what it means for long context, and how Together is optimizing inference and KV-cache for this new architecture. Set your re

We're going LIVE tomorrow with @togethercompute 🔥. @zpysky1125 is pulling back the curtain on M3: sparse attention, 1M context, all of it. You don't want to miss this. MiniMax M3 is live and Together

Learn more about the latest from @james_y_zou and our Frontier Agents Research team! To evaluate frontier AI agents, we need more complex tasks. But such tasks are also more prone to have design mista

We took the Hot Wings Challenge to NVIDIA GTC 🌶️ @realDanFu (VP of Kernels) and @sarung (VP of Customer Success) answered some questions around AI, one spicy wing at a time. Some people sweat. Some pe

Together AI serves the two fastest STT models measured by @ArtificialAnlys NVIDIA Parakeet-TDT 0.6B v3 can transcribe 20 hours of speech in under 10 seconds. This deep dive shows the systems work behi

Every LLM API call depends on the inference engine underneath it. Tokenization, scheduling, prefill, decode, KV cache, batching, and streaming determine whether the experience is fast, scalable, and p

The best research labs are building what comes after static models. Congrats to @trajectorylabs on the launch! Excited to have them training on the AI Native Cloud as they push the frontier on Continu

Our inference stack, optimized for Blackwells, with a novel attention kernel and many new optimizations has started rolling out! It's already charting on Artificial Analysis, eg: #1 speed and latency

Highlights: 👉 Long-horizon autonomy: maintained coherent execution across a 35-hour autonomous kernel optimization run 👉 Agentic coding: leading Terminal-Bench 2.0-Terminus performance for terminal-ba

Introducing Qwen3.7-Max from @Alibaba_Qwen, Qwen’s flagship model for the agent era with 1M context and leading performance across agentic coding, reasoning, and long-horizon autonomy. AI natives can

Together AI announced the addition of 1,000 H100 and H200 GPUs to their on-demand GPU clusters and dedicated endpoints, expanding their available compute resources for users accessing services through

Together AI announced the availability of Qwen3.7-Max, a large language model, on their platform. The announcement promotes users to try the model through Together AI's interface. Qwen3.7-Max is part

We turned this app into a real comic book booth at GTC! Had folks create their own comic books on-site, printed them, and gave them out! (this is using an unreleased version of the app that's a lot be

MiniMax Speech 2.8 Turbo is built for voice agents that need natural delivery, not just clean audio. → Sound Tags for laughter, breathing, sighs, gasps, and other vocal cues → 60% prosody improvement

MiniMax Speech 2.8 Turbo is a text-to-speech model available through Together AI's voice finder tool at voicefinder.together.ai, allowing users to preview and test different voice options directly. Th

We added 600+ new voices on Together AI! Introducing MiniMax Speech 2.8 Turbo on Together AI, an enterprise TTS model for expressive real-time voice agents. AI natives can now deploy @MiniMax_AI Speec

'One thing that we've been seeing recently is that inference benchmarks don't really match production workloads that well.' - @realDanFu, VP of Kernels When you're running dozens of concurrent coding

Voice 'cloning' is style transfer. Across three widely used systems — ElevenLabs V3, Coqui-XTTS, Chatterbox — clones don't just copy speakers, they reshape them to be warmer, more authoritative, more

Congrats to the @cursor_ai team on Composer 2.5 — a huge milestone for agentic coding models. Together AI, the AI Native Cloud, is proud to partner on this launch. Composer 2.5 is pushing the frontier

Gemma-4-31B-it-Pearl supports 32K context, configurable thinking, function calling, and JSON mode. This is Together AI’s first Pearl-powered endpoint. Eventually, we plan to expand our Pearl powered p

Heading to hashtag#MLSys2026? Come unwind with the Together AI team at Inference After Dark. Drinks, bites, shuffleboard, and a room full of researchers and AI-native builders. 🟠 Tuesday, May 19 🟠 7:3

A milestone for Pearl Research Labs: our first major enterprise partnership is live with Together AI. @togethercompute’s inference platform is an ideal demonstration of @prlnet's value proposition — O

As inference workloads dominate, what if these matmuls could also perform useful work and generate beneficial byproducts!? Similar to all the byproducts we get from crude oil distillation that are not

Gemma-4-31B-it-Pearl supports 256K context, configurable thinking, function calling, and JSON mode. This is Together AI’s first Pearl-powered endpoint. Eventually, we plan to expand our Pearl powered

Gemma-4-31B-it-Pearl supports text and image input, 256K context, configurable thinking, function calling, and JSON mode. This is Together AI’s first Pearl-powered endpoint. Eventually, we plan to exp

Inference is becoming the largest compute market and energy consumer in AI. Pearl turns inference CapEx of hyperscalers into a profit center: every LLM token produced by GPUs can simultaneously genera

Introducing Gemma-4-31B-it-Pearl on Together AI, Pearl Research Labs’ instruction-tuned checkpoint of Gemma 4 31B powered by @prlnet Proof of Useful Work protocol. AI natives can now use this Pearl mo

Pearl generates proofs from matrix multiplications that already happen during training and inference computations. Those proofs help secure Pearl Network, and the future value of Pearl emissions helps

Introducing Rime Mist v3 on Together AI, a production TTS family built for deterministic pronunciation and controllable voice output. AI natives can now deploy @rimelabs Mist v3 on Together AI dedicat

🌟Introducing🎻Violin — an Open-source Video Translation Skill. 📹Video is the dominant medium on the internet, yet most high-quality content (lecture, talk, podcast) is locked behind a single language,

Mist v3 is available across two endpoints: 👉 rime-labs/rime-mist-v3 for English TTS 👉 rime-labs/rime-mist-v3-omni for multilingual TTS across English, Spanish, French, and German 👉 Custom pronunciatio

Together AI will present seven research papers at MLSys 2026, showcasing projects that demonstrate the transition from research to production applications. The announcement highlights the company's co