Together
A cloud platform company focused on inference and training of open-source large language models. It provides API services for open-source models and distributed inference infrastructure, enabling enterprises to deploy and fine-tune open-source AI models.
Core Facts
The core of the OpenAI-compatible protocol is the /v1/chat/completions REST interface specification, which defines fields such as model, messages, and temperature, as well as the streaming response (Server-Sent Events) format.
从预训练检查点到可商用产品需经历监督式指令微调（SFT）和基于人类反馈的强化学习（RLHF）两个后训练阶段
Timeline (last 90 days)
openai-compatible is a kind of "protocol adapter base" that lets any vendor following the OpenAI Chat Completions interface style (Z.ai, DeepSeek, Together, etc.) integrate with very little code.
On Together's post-training platform, Deel's data science team went from environment setup to running real RL experiments in just a few hours (about "a couple of hours").
Together's post-training platform packages environment setup, compute scheduling, and experiment management into easier-to-use interfaces, lowering the barrier to starting RL experiments.
The Deel team shared information about using Together's post-training platform on social media.
The Deel team ran as many as five RL experiments simultaneously on the same GPU capacity.
Beam is a model or model service that has not yet been officially released, with early access provided through the Together platform.
Together sometimes opens early access channels for not-yet-officially-released models to select partners, usually under a confidentiality agreement.
Together is a platform that provides model hosting and inference services, and developers can access a variety of open-source or third-party models through a unified API.
Before Beam's official release, the AI coding platform Factory obtained early access to the model through Together.
Together has launched a Post-Training service that allows developers to post-train open-source models such as Qwen, GLM, and Kimi through custom training loops, with the platform handling the underlying infrastructure.
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All Facts (20)
The core of the OpenAI-compatible protocol is the /v1/chat/completions REST interface specification, which defines fields such as model, messages, and temperature, as well as the streaming response (Server-Sent Events) format.
65%Partially Verified从预训练检查点到可商用产品需经历监督式指令微调（SFT）和基于人类反馈的强化学习（RLHF）两个后训练阶段
65%Unverifiedopenai-compatible is a kind of "protocol adapter base" that lets any vendor following the OpenAI Chat Completions interface style (Z.ai, DeepSeek, Together, etc.) integrate with very little code.
50%UnverifiedTogether's post-training platform packages environment setup, compute scheduling, and experiment management into easier-to-use interfaces, lowering the barrier to starting RL experiments.
50%UnverifiedThe Deel team shared information about using Together's post-training platform on social media.
50%UnverifiedBeam is a model or model service that has not yet been officially released, with early access provided through the Together platform.
50%UnverifiedTogether sometimes opens early access channels for not-yet-officially-released models to select partners, usually under a confidentiality agreement.
50%UnverifiedTogether is a platform that provides model hosting and inference services, and developers can access a variety of open-source or third-party models through a unified API.
50%UnverifiedIn its post-training service, Together handles infrastructure work such as distributed training orchestration, GPU cluster management, and checkpoint saving and restoration.
50%UnverifiedTogether's post-training service supports developer customization of training loop components such as data loading, loss functions, and reward computation, rather than using fixed fine-tuning templates.
50%UnverifiedTogether's post-training service covers major open-source model families such as Qwen, GLM, and Kimi.
50%UnverifiedGlimpse's model name on OpenRouter is elorian/glimpse; endpoint data shows the provider is Together, the context window is 262,144 tokens, it supports text, image, and video input and outputs text, and the cached input read price is $0.06 per million tokens.
50%UnverifiedTogether's preemptible compute provides a five-minute drain window, giving jobs five minutes to save state before being preempted.
50%UnverifiedTogether cuts the price to 50% of the on-demand rate, with identical compute specifications, but with the possibility of preemption.
50%UnverifiedTogether's DMI solution provides engineering teams with autonomous control across three dimensions: scaling control, freedom of model selection, and testing and validation capabilities.
50%UnverifiedThis article is based on a single-source case description and lacks specific performance data and cost comparisons.
50%UnverifiedTogether proposed a five-stage framework for migrating from closed-source to open-source models: discovery, evaluation, adaptation, decision, and production deployment.
50%UnverifiedTev1-4B-experimental is deployed on Together's serverless platform, so users do not need to maintain their own GPU clusters.
50%UnverifiedTogether, Fireworks, and Groq are third-party inference service providers that offer hosted APIs and charge per token
50%UnverifiedOn Together's post-training platform, Deel's data science team went from environment setup to running real RL experiments in just a few hours (about "a couple of hours").
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