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.
Timeline (last 90 days)
Together cuts the price to 50% of the on-demand rate, with identical compute specifications, but with the possibility of preemption.
Together GPU Clusters has announced support for preemptible compute, offering equivalent GPU resources at a fixed 50% discount off on-demand pricing.
Together's preemptible compute provides a five-minute drain window, giving jobs five minutes to save state before being preempted.
Together proposed a five-stage framework for migrating from closed-source to open-source models: discovery, evaluation, adaptation, decision, and production deployment.
Together published a case study on the financial institution's adoption of Dedicated Model Inference.
A global fintech company migrated from traditional shared inference services to self-managed Dedicated Model Inference (DMI) infrastructure.
Together's DMI solution provides engineering teams with autonomous control across three dimensions: scaling control, freedom of model selection, and testing and validation capabilities.
This article is based on a single-source case description and lacks specific performance data and cost comparisons.
Tev1-4B-experimental is deployed on Together's serverless platform, so users do not need to maintain their own GPU clusters.
Together released the together/Tev1-4B-experimental model.
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All Facts (11)
Together cuts the price to 50% of the on-demand rate, with identical compute specifications, but with the possibility of preemption.
50%UnverifiedTogether's preemptible compute provides a five-minute drain window, giving jobs five minutes to save state before being preempted.
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%UnverifiedTogether GPU Clusters has announced support for preemptible compute, offering equivalent GPU resources at a fixed 50% discount off on-demand pricing.
50%UnverifiedTogether published a case study on the financial institution's adoption of Dedicated Model Inference.
50%UnverifiedA global fintech company migrated from traditional shared inference services to self-managed Dedicated Model Inference (DMI) infrastructure.
50%UnverifiedTogether released the together/Tev1-4B-experimental model.
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