Knowledge catalogue
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
Together AI STT models now hold the top two spots for transcription speed on the @ArtificialAnlys Speech to Text leaderboard. NVIDIA Parakeet TDT 0.6B V3 on Together AI ranks #1, transcribing 303 seco
Try Rime Mist v3 in voice finder directly: https://findtherightvoice.com/rime-labs--rime-mist-v3 Model pages: http://www.together.ai/models/rime-mist-v3 http://www.together.ai/models/rime-mist-v3-omni
AutoScientist is an AI system developed by Together AI that automates the complete research workflow to enable model training and scientific discovery outside of well-resourced frontier laboratories.
💡 Why did @togethercompute choose NVIDIA Blackwell to serve DeepSeek-V4? Because NVIDIA Blackwell is built for the bottlenecks that matter most in long-context inference: → KV-cache pressure during de
Highlights: 👉 600+ voices across MiniMax, Cartesia, Deepgram, Rime, and more 👉 Search by prompt or audio sample 👉 Filter by 15+ attributes, including pitch, accent, language, age, emotion, and speakin
Introducing voice finder from Together AI, a new tool to search, filter, and audition 600+ voices across leading TTS models. AI natives can now find the right voice for their app faster by describing
Voice selection significantly impacts user perception and experience across various applications, including financial services support, healthcare intake processes, and entertainment platforms. Togeth
DeepSeek V4 Pro brings long-context reasoning and SOTA coding performance to Together AI serverless. The next layer is serving it efficiently: KV cache, prefix reuse, hybrid attention, batching, kerne
For browser-use AI agents, every task is dozens of model calls in a tight loop. The inference layer isn’t background infrastructure. It’s what the product runs on. @yutori_ai runs Scouts, Delegate, an
Read the full blog: https://www.together.ai/blog/serving-deepseek-v4-why-million-token-context-is-an-inference-systems-problem# Watch the full webinar on DeepSeek v4: https://www.youtube.com/watch?v=D
Excited to speak at PyCon US @pycon about production LLM inference systems, runtime optimization, and next-gen engine design — including some of the new ideas behind the recently open-sourced project
The gap between 'this looks cool' and 'I'm actually running it' used to be a day or two of setup. Not anymore. Deploy any Hugging Face model on the AI Native Cloud in a single session 👇🏼 https://www.t
Together AI has long been a proud supporter of open-source innovation in inference. We're excited for the new TokenSpeed inference engine, available in preview today with MIT licence, and can't wait t
Deepgram STT is now natively available on @togethercompute. One platform, full voice-agent stack: Deepgram transcription, Together-hosted LLMs, Aura-2 TTS. Sub-3-second round trip on reference builds.
Inference is 80-90% of the lifetime cost of a production AI system. Most AI-native teams are leaving performance and margin on the table. Here’s how Together AI, the AI Native Cloud, fixes that on @nv
On 5/5 @realDanFu and team will discuss DSV4’s hybrid attention and KV cache efficiency, should be a great session! Join us Tue 5/5: #DeepSeek-V4's hybrid attention + sparse MoE reduces KV cache up to
@profdanklein spent 20 years studying how language forms intelligence. When LLMs exploded, he saw something everyone missed. These systems were fluent, confident, and wrong. And no one could tell the
Together AI reported significant improvements after switching from AWS, achieving zero training-blocking failures, approximately 50% cost savings, and rapid issue resolution within hours through share
The AI industry is racing toward superintelligence. Dan and Scaled Cognition built something more : Super-Reliable Intelligence. 'The smartest model in the world is useless if it can’t get the answer
Adaptive Data is a Together AI tool designed to help teams improve the quality of datasets before fine-tuning language models by enabling analysis, adaptation, and refinement of training data. The pla
Join us Tue 5/5: #DeepSeek-V4's hybrid attention + sparse MoE reduces KV cache up to 90%, enabling 1M-token context. We'll cover why that makes it great for agentic workflows, what it took to serve at
Most model trainings outside of frontier labs fail. 📈 Because of bad or insufficient data. 🚮 Or just data for what you want + not general capabilities. 🎯 Most builders give up + become elevated prompt
We believe that intelligence should not arrive preconfigured. @togethercompute is now available directly inside the Adaption platform, connecting Adaptive Data with large-scale training in a single wo
We’re excited to partner with @adaption_ai to make Together Fine-Tuning natively available in Adaptive Data. AI natives can now move from optimized training data in Adaptive Data to fine-tuned open mo
With this integration, teams can optimize data, launch fine-tuning, evaluate results, and deploy on Together AI inference through a tighter workflow. Learn more: http://www.together.ai/blog/announcing
$3/million output tokens. Qwen 3.5 Plus is basically a frontier model. Let that sink in. Introducing Qwen3.6-Plus from @Alibaba_Qwen, a 1M-context model built for real-world agents, agentic coding, an
Highlights: 👉 1M context for long-horizon agentic workflows 👉 Stronger agentic coding across frontend, repo-level, and terminal-based tasks 👉 Multimodal reasoning across text, image, and video inputs
Introducing Qwen3.6-Plus from @Alibaba_Qwen, a 1M-context model built for real-world agents, agentic coding, and multimodal reasoning. AI natives can now use Qwen3.6-Plus on Together AI and benefit fr
Last week we announced DeepSeek-V4. Today we’re sharing a closer look at DeepSeek-V4 Pro on Together AI: 512K context, controllable reasoning modes, and cached-input pricing for long-context workloads
Qwen3.6-Plus, a large language model, is now available for use through Together AI's platform. Together AI has announced the availability of this model and is inviting users to try it via their models
DeepSeek V4 Pro is a language model available through Together AI's platform, with official quickstart documentation provided to help users get started with the model. The quickstart guide likely cove
@NVIDIA Nemotron 3 Nano Omni is now on Together AI. Enterprise multimodal AI — video, audio, image, documents & text — optimized for speed and scale. ✅ ~3B active params, 9x higher throughput ✅ Fully
Together AI announced the availability of NVIDIA Nemotron-3 Nano Omni models to developers on day zero of release, enabling early access to these multimodal AI models through their platform. The annou
NVIDIA Nemotron-3 Nano Omni is now available to try through Together AI's platform, offering access to a compact multimodal model capable of processing both text and audio inputs. This announcement hi
Together AI announced a partnership or initiative with the 17 DOE National Laboratories aimed at doubling American scientific productivity within a decade. The collaboration leverages Together AI's co
At #ICLR? Don’t miss @realDanFu 👇 Latent & Implicit Thinking Workshop (LIT) 🕐 Workshop at 1:30 PM BRT (local) Exploring what comes after chain-of-thought and how models may actually reason. 🔗 https://
A developer created an open-source, free web interface inspired by Reddit's r/explainlikeimfive community that allows users to submit simple questions to AI models for straightforward answers. The pro
Open models. National scale. Real scientific impact. Read more: https://www.prnewswire.com/news-releases/together-ai-joins-us-department-of-energys-genesis-mission-to-accelerate-american-scientific-di
We power 1M+ developers globally. Our researchers developed FlashAttention, Mixture of Agents, EinsteinArena, and more. Our platform is built for large-scale, latency-sensitive workloads on open-sourc
Inference that never sleeps, for agents that never stop. 'Why cowork when you can delegate?' That's @DhruvBatra_ on @yutori_ai's new Delegate — an always-on agent that monitors, researches, and acts a
4⃣4⃣4⃣4⃣ Introducing DeepSeek V4 Pro, a long-context model with hybrid attention, three reasoning modes, and SOTA coding performance. AI natives can now use DeepSeek V4 Pro on Together AI and benefit
DeepSeek V4 Pro is now available through Together AI's model platform, with the faster DeepSeek V4 Flash variant expected to launch soon. Together AI is offering users the ability to access and test D
Highlights: 👉 SOTA coding—93.5% LiveCodeBench, Codeforces 3206, and 80.6% SWE-Bench Verified 👉 Hybrid attention efficiency—27% FLOPs and 10% KV cache vs V3.2 for long-context inference 👉 Three reasoni
Introducing DeepSeek V4 Pro, a long-context model with hybrid attention, three reasoning modes, and SOTA coding performance. AI natives can now use DeepSeek V4 Pro on Together AI and benefit from reli
This has been the most anticipated event in OSS and it doesn't disappoint. Congratulations to @deepseek_ai team. DSV4 Pro is now available on @togethercompute and we'll be adding a lot of capacity beh
Together AI achieved a 10,000x increase in monthly token throughput over one year, scaling from 30 billion to 300 trillion tokens per month. This milestone demonstrates significant growth in their API
Together AI has launched Delegate, an AI agent designed to handle delegated tasks autonomously, allowing users to assign work and proceed with other activities. The agent appears to be positioned as a
zero shot Kimi K2.6, go try it out its a good model sir! this is @Kimi_Moonshot running on @togethercompute, @opencode harness prompt below👇 Media Introducing Kimi K2.6 from @Kimi_Moonshot, a multimod