Foundational research powering efficient inference at scale
As AI moves from research to production, the challenge for AI-native teams shifts from building models to running them — efficiently, reliably, and at scale.
Together AI Blog
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Announcing Together AI and Adaption Partnership
Together AI and Adaption partner to bring Together Fine-Tuning natively into Adaptive Data, helping teams optimize datasets, run fine-tuning, evaluate results, and deploy stronger open models.
From 732 bytes to nowhere: shutting down Copy Fail in production
How Together AI responded to the Copy Fail Linux kernel bug (CVE-2026-31431): disabling the affected crypto interface fleet wide and patching safely.
DeepSeek-V4 Pro now available on Together AI
DeepSeek-V4 Pro is now available on Together AI with 512K context, controllable reasoning modes, and cached-input pricing for long-context reasoning workloads like code agents, document intelligence, and research synthesis.
Together AI Brings NVIDIA Nemotron 3 Nano Omni to Developers on Day 0
NVIDIA Nemotron 3 Nano Omni is now on Together AI: a single open model that reasons across video, images, audio, and text, built for agentic workloads at scale.
Accelerate RL rollouts by up to 50% with distribution-aware speculative decoding
Rollout is the silent bottleneck in RL post-training. DAS fixes it with adaptive speculative decoding — up to 50% faster, zero degradation in reward quality.
Capacity without conflict: A guide to multi-tenant GPU cluster design for AI-native teams
Learn how AI-native companies design multi-tenant GPU clusters that pool capacity without sacrificing team isolation — and how Together AI makes it work in practice.
Parcae: Doing more with fewer parameters using stable looped models
Parcae is a stable looped language model that matches the quality of a Transformer twice its size — a 770M model reaching 1.3B-level performance. We introduce the first scaling laws for looping and show that increasing recurrence, not just data, is a compute-efficient path to bet
EinsteinArena: Harnessing the collective intelligence of agents in the wild to advance science
EinsteinArena is a platform where AI agents collaborate and compete on open math problems. AI agents on EinsteinArena have already set 11 new state-of-the-art results on open math problems — including pushing the kissing number lower bound in dimension 11 from 593 to 604.
What is an AI Native Cloud?
AI-native companies need infrastructure built for models, not legacy workloads. Learn what defines an AI Native Cloud and why it matters for the next platform shift.
AI for Systems: Using LLMs to Optimize Database Query Execution
New research shows LLMs can optimize database query execution plans—achieving up to 4.78x speedups by correcting the cardinality estimation errors that statistical heuristics miss.
Inside the Together AI kernels team
The team behind FlashAttention and ThunderKittens — how Together AI's kernel researchers close the gap between GPU hardware and production AI.
Aurora
1.25x over a well-trained static speculator. Aurora is an open-source RL framework that turns speculative decoding from a one-time offline setup into a self-improving system that learns from every request it serves.
Plan, divide, and conquer: How weak models excel at long context tasks
As context windows grow, LLM performance degrades in unexpected ways. We show how a "Divide & Conquer" framework — breaking long documents into parallel chunks with a planner, workers, and manager — lets smaller models like Llama-3-70B and Qwen-72B outperform GPT-4o single-shot.
Together AI expands fine-tuning service with tool calling, reasoning, and vision support
Together AI expands fine-tuning with native support for tool call, reasoning, and vision-language models, plus 100B+ model training, up to 6× higher throughput, and job cost and ETA estimates.
Mamba-3
Meet Mamba-3: the SSM built for inference. Faster than Transformers at decode, stronger than Mamba-2, and open-source from day one.
Together AI at NVIDIA GTC 2026: Explore our latest innovations across research and products
Together AI arrives at NVIDIA GTC 2026 with new launches in inference, agents, voice AI, and open models — plus technical sessions from its research and engineering leaders.
Build real-time voice agents on Together AI
Build real-time voice agents on Together AI with co-located STT, LLM, and TTS infrastructure, native Deepgram and Cartesia support, and end-to-end latency under 500ms.
Together AI Brings NVIDIA Nemotron 3 to Developers on Day 0
NVIDIA Nemotron 3 Super is now available on Together AI Dedicated Inference, delivering efficient multi-agent reasoning, a 1M-token context window, and production-grade deployment on managed infrastructure.
New in Together GPU Clusters: Autoscaling, observability, and self-healing
Together GPU Clusters now include built-in autoscaling, RBAC, full-stack observability, and self-healing node repair—giving teams production-ready GPU infrastructure that scales efficiently, stays resilient, and supports shared enterprise workloads.