Together AI
PulseAugur coverage of Together AI — every cluster mentioning Together AI across labs, papers, and developer communities, ranked by signal.
- uses Nvidia Blackwell B200 90%
- founded Vipul Ved Prakash 90%
- developed Together Code Interpreter 90%
- developed Gemma-4-31B-it-Pearl 90%
- uses Deepgram 90%
- partners with Pearl Research Labs 90%
- used by DeepSeek-R1 70%
- affiliated with Nvidia Blackwell B200 70%
- instance of Qwen 70%
- used by Together Code Interpreter 70%
- used by Zoom 70%
- uses RiMe. Rivista dell'Istituto di Storia dell'Europa Mediterranea 70%
- 2026-05-22 product_launch Together AI launched updates to its Fine-Tuning Platform, adding support for new LLMs and extending context lengths. 来源
- 2026-05-22 product_launch Together AI announced the addition of 1,000 NVIDIA H100 and H200 GPUs to its infrastructure. 来源
- 2026-05-22 product_launch Together AI launches GPU clusters with NVIDIA Blackwell platform and optimized kernel collection, achieving significant performance gains. 来源
- 2026-05-22 product_launch Together AI released FlashAttention-3 and FlashAttention-4, optimized attention mechanisms for GPUs. 来源
- 2026-05-22 product_launch Together AI launched major upgrades to its Batch Inference API. 来源
- 2026-05-22 product_launch Together AI launched access to the Qwen3.7-Max model. 来源
- 2026-05-15 partnership Together AI and Pearl Research Labs formed a partnership to integrate blockchain for AI inference cost reduction. 来源
- 2026-05-14 research_milestone Together AI's speech-to-text models achieved top rankings for transcription speed on a benchmark leaderboard. 来源
- 2026-05-08 product_launch Together AI launched a new feature enabling deployment of any Hugging Face model via their Dedicated Container Inference infrastructure using the Goose CLI agent. 来源
- 2026-04-30 research_milestone Together AI details its rapid response and mitigation strategy for the Copy Fail Linux kernel vulnerability. 来源
- 2026-04-30 partnership Together AI announced a partnership with Adaption to integrate their data optimization and model fine-tuning services. 来源
- 2026-03-26 research_milestone Together AI researchers published a framework for using smaller LLMs on long context tasks. 来源
- 2026-03-18 product_launch Together AI launched an enhanced fine-tuning service with support for tool calls, reasoning, and vision-language models. 来源
- 2026-03-16 product_launch Together AI announced new integrations and product offerings at NVIDIA GTC 2026.
- 2026-03-10 product_launch Together AI introduced significant enhancements to its GPU clusters, including multi-tenancy, autoscaling, observability, and self-healing features. 来源
11 天有情绪数据
Together AI to announce enterprise-focused cloud offering within 90 days
The recent launch of self-service GPU clusters and the ATLAS inference system, combined with enhanced fine-tuning capabilities and a brand refresh emphasizing 'builders', suggests Together AI is positioning itself for a more robust enterprise offering. These services are foundational for enterprise AI development and deployment, indicating a strategic move towards capturing a larger market share.
Together AI's ATLAS system shows strong performance against specialized hardware
The reported performance of Together AI's ATLAS system, achieving up to 500 TPS on DeepSeek-V3.1 and outperforming specialized hardware like Groq, is a significant technical achievement. This suggests their adaptive inference approach is highly effective and could set a new benchmark for LLM inference speed and efficiency.
Together AI to integrate NVIDIA Blackwell features into all core services
The 90% training speed boost achieved with NVIDIA Blackwell and custom kernels indicates a deep integration. It's likely Together AI will leverage Blackwell's capabilities across their entire platform, including their new instant clusters and fine-tuning services, to offer a performance edge over competitors.
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Together AI 增加 1,000 块 H100/H200 GPU 用于推理
Together AI 通过增加一千台 NVIDIA H100 和 H200 实例，显著扩展了其 GPU 容量。这些强大的 GPU 现已通过 Together 的按需 GPU 集群和专用端点服务提供。此次扩展旨在为 AI 推理和开源模型开发提供更强大的基础设施。
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Together AI 将批量推理 API 的速率限制提高了 3000 倍
Together AI 已显著升级其批量推理 API，引入了更用户友好的界面，并将模型兼容性扩展到包括所有无服务器和私有部署模型。此次更新将速率限制大幅提高了 3000 倍，从每位用户每个模型的 1000 万个排队令牌增加到 300 亿个，从而能够进行更大规模的数据处理。这些增强措施旨在使高吞吐量的工作负载更具成本效益和可访问性，对于大多数无服务器模型，成本通常是其实时 API 的 50%。
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Together AI 推出面向 AI 开发的自助式 GPU 集群
Together AI 推出了 Together Instant Clusters，一项提供现成可用、自助式 GPU 集群以支持 AI 开发和部署的新服务。该服务旨在简化设置多节点 GPU 基础设施的复杂过程，允许用户通过 API、CLI 或控制台在几分钟内配置包含数百个 GPU 的集群。该服务包括用于分布式训练和推理的预配置组件，支持 NVIDIA 的最新 GPU 架构和高性能网络解决方案。
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Together AI 推出自适应 LLM 推理系统 ATLAS
Together AI 推出了 ATLAS，一个新颖的自适应学习系统，用于推测性解码，可在无需手动调整的情况下动态提高 LLM 推理性能。与标准或自定义推测器不同，ATLAS 可持续从运行时使用和不断变化的工作负载中学习，以实时优化 token 草稿。该系统实现了显著的加速，在 DeepSeek-V3.1 上达到高达 500 TPS，在 Kimi-K2 上达到 460 TPS，甚至超越了 Groq 等专用硬件。
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Together AI发布FlashAttention-3和-4，加速大语言模型处理
Together AI发布了FlashAttention-3和FlashAttention-4，这是其用于大语言模型的GPU加速注意力机制的重大升级。FlashAttention-3专为Hopper GPU设计，通过利用张量核心（Tensor Cores）和张量内存加速器（Tensor Memory Accelerator）等新硬件特性并支持FP8精度，实现了高达75%的利用率和比前代产品快1.5-2倍的速度。FlashAttenti…
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Together AI 提供 Alibaba 的 Qwen3.7-Max，支持 1M 上下文
Together AI 现已提供对 Alibaba 的 Qwen3.7-Max 模型的访问权限。该模型是专为智能体时代设计的旗舰产品。该模型拥有百万级 token 的上下文窗口，并在智能体编码、推理和长时自主性等领域展现出领先性能。用户现在可以在 Together 的 Serverless Inference 平台上使用 Qwen3.7-Max 来构建生产规模的应用。
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MiniMax AI launches 600+ new voices via Speech 2.8 Turbo on Together AI
MiniMax AI has released over 600 new voices through its Speech 2.8 Turbo model. These voices are now accessible on the Together AI platform. This expansion aims to provide a wider range of synthetic speech options.
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Cursor AI launches Composer 2.5 with Together AI partnership
Together AI has partnered with Cursor AI to launch Composer 2.5, a significant advancement for agentic coding models. This new version is noted for its speed and quality, pushing the boundaries of what coding agents can…
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Together AI hosts MLSys 2026 social event
Together AI is hosting an event called "Inference After Dark" during the MLSys 2026 conference. The event will take place on Tuesday, May 19th, from 7:30 PM to 10:00 PM at Tavern Hall in Bellevue, WA. It is intended as …
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Together AI releases Pearl-powered Gemma-4-31B-it-Pearl model
Together AI has released Gemma-4-31B-it-Pearl, an open-source model with enhanced capabilities. This model supports a 32K context window, configurable thinking processes, function calling, and JSON mode. It marks Togeth…
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Pearl Labs partners with Together AI for inference optimization
Pearl Research Labs has announced its first major enterprise partnership with Together AI, focusing on optimizing inference workloads. This collaboration aims to transform hyperscalers' inference capital expenditures in…
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Together AI launches Pearl-integrated Gemma model with Proof of Useful Work
Together AI has released Gemma-4-31B-it-Pearl, an instruction-tuned model based on Gemma 4 31B. This model integrates the Pearl Network's Proof of Useful Work protocol, which generates proofs from existing matrix multip…
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Together AI 与 Pearl Research Labs 合作，通过加密货币降低 AI 推理成本
Together AI 已与 Pearl Research Labs 合作，将区块链技术整合到 AI 推理成本中。此次合作推出 Gemma-4-31B-it-pearl 模型的新推理端点，通过 Pearl Network 的加密货币排放抵消成本，提供超过 25% 的折扣。Pearl Network 使用有用工作量证明机制，其中用于 AI 任务的 GPU 计算同时生成一种名为 PRL 的加密货币，旨在通过降低每代代币的价格来从根本上改变…
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Together AI models lead speech-to-text speed benchmarks
Together AI's speech-to-text models have achieved the top two positions on the Artificial Analysis leaderboard for transcription speed. The NVIDIA Parakeet TDT 0.6B V3 model, running on Together AI, is currently ranked …
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Together AI发布Violin，一款开源视频翻译工具
Together AI推出了Violin，这是一款开源视频翻译工具，旨在打破语言障碍，使在线视频内容更易于访问。该系统利用先进的AI技术，包括语音识别、大型语言模型和语音合成，提供高质量的翻译。Violin还具有交互式功能，如内容感知聊天助手和个性化语音选择，旨在扩大视频内容的全球覆盖范围。
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Together AI 发布 Voice Finder，支持 600 多种 TTS 语音
Together AI 推出了 Voice Finder，这是一款旨在帮助开发者从 600 多种选项的目录中快速选择最适合其应用程序的声音的新工具。该工具允许用户通过描述所需特征或上传音频样本进行比较来搜索声音。Voice Finder 针对音高、口音和情感等 15 个以上属性对每种声音进行分类，以简化语音代理的选择过程。
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DeepSeek-V4 的 100 万 token 上下文窗口是一个推理系统挑战
Together AI 详细介绍了 DeepSeek-V4 处理一百万 token 上下文窗口的能力背后的架构创新。该模型采用混合注意力设计，在将上下文压缩后存储在 KV 缓存中，显著降低了内存压力。这种架构转变将长上下文推理的挑战从模型能力问题转变为推理系统问题，需要优化的服务引擎来有效管理缓存布局和批处理。
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Together AI 通过代理驱动的 CLI 简化模型部署
Together AI 推出了新功能，允许开发人员使用其专用容器推理 (DCI) 基础设施部署和运行 Hugging Face 上的任何模型。这通过一个名为 Goose 的基于代理的 CLI 工具实现，该工具可自动完成复杂的设置过程，包括推理服务器配置和容器生成。该系统旨在显著缩短模型发布与其实际使用之间的时间延迟，Netflix 的 void-model 的快速部署即为此例。
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Artificial Analysis offers MiniMax-M2.7 with SambaNovaAI leading inference speed
Artificial Analysis has made its MiniMax-M2.7 model available through six different inference providers, highlighting significant differences in speed and cost. SambaNovaAI leads in performance, achieving 435 tokens per…
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Together AI 与 Adaption 合作，简化模型微调流程
Together AI 已与 Adaption 达成合作。Adaption 由前 Cohere 和 Google DeepMind 的领导者 Sara Hooker 和 Sudip Roy 联合创立。此次合作将 Adaption 的数据优化工具与其微调基础设施相结合。该合作旨在通过提高数据集质量并简化实验和部署工作流程，使用户能够更轻松地创建高质量、微调后的开源模型。