SF Tensor

SF Tensor is a Coding & Development tool that reinvents the software and infrastructure stack for modern AI and HPC. It offers automatic kernel optimization and cross-cloud, cross-vendor compute to make code faster, cheaper, and portable.

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At a glance

Pricing

Likely Not Free · Enterprise

Free tier

API

Skill level

Technical

About

What is SF Tensor?

SF Tensor, also known as The San Francisco Tensor Company, is dedicated to reinventing the software and infrastructure stack for modern AI and High-Performance Computing (HPC). The platform provides automatic kernel optimization and cross-cloud, cross-vendor compute capabilities, ensuring code runs faster, cheaper, and is portable across various platforms. It supports a heterogeneous future where CPUs, GPUs, TPUs, and domain-specific accelerators are treated as first-class citizens. SF Tensor offers two main options: Tensor Cloud for experiments and medium-scale training jobs, and Forward-Deployed for scaling training runs with dedicated infrastructure support. Pricing is aligned with the savings delivered to customers.

Best used for

Ideal for developers and IT managers who need to accelerate AI and HPC workloads, ensure portability across diverse hardware, and optimize compute costs. Especially valuable for teams running experiments, medium-scale training jobs, or scaling large-scale training runs in their own cloud.

Common actions

optimize AI workloads

manage HPC infrastructure

run AI experiments

scale AI training

reduce compute costs

Capabilities

Key features

Automatic kernel optimization
Cross-cloud compute
Cross-vendor compute
Jupyter notebooks
Dedicated engineering support
Custom kernel optimization
Capacity planning

Target Audience

developer

Integrations

Not yet documented

Pricing & Plans

Likely Not Free · Enterprise

Not publicly disclosed. Check sf-tensor.com for current pricing.

FAQs

What is the core benefit of SF Tensor's automatic kernel optimization?

Automatic kernel optimization makes your code faster and more efficient across various hardware, including CPUs, GPUs, and TPUs. This reduces compute costs and improves performance without manual tuning, ensuring your AI and HPC workloads run optimally.

How does SF Tensor support cross-cloud and cross-vendor compute?

SF Tensor's infrastructure allows your applications to run seamlessly across different cloud providers and hardware vendors. This provides flexibility, prevents vendor lock-in, and ensures your code is portable, adapting to the best available compute resources.

What are the differences between Tensor Cloud and Forward-Deployed options?

Tensor Cloud is designed for running experiments and medium-scale training jobs, supporting up to 64 GPUs. Forward-Deployed is for large-scale training, supporting up to 10,000 GPUs in your own cloud, with dedicated engineering and 24/7 support.

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Open Source & Models Code Assistants No-Code / Low-Code Testing & QA Backend & APIs Prompt Engineering

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AI Agents & Automation › AI Frameworks & Infra

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