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kforge

by Gimlet Labs@gimletlabsSan FranciscoNo ratings yet

Autonomous PyTorch kernel generation for CUDA, ROCm, and Metal

Visit kforge.ai
Tool type
Autonomous PyTorch kernel generator
Made for
PyTorch developers and ML engineers
Runs on
Command-line interface
Delivered as a command-line interface; supported operating systems are not stated.
Last checked
29 Oct 2026
2 product sources

What it does

kforge generates optimized low-level kernels directly from PyTorch code, aiming to speed up both training and inference workloads. It is delivered as a command-line tool, so teams can pursue performance gains without leaving PyTorch or writing kernels by hand.

Under the hood, kforge uses a multi-agent system with shared memory to explore different kernel designs, enforce strict correctness checks, and automatically identify the fastest candidates. It supports the CUDA, ROCm, and Metal backends, which makes it relevant to teams working across heterogeneous hardware.

kforge is produced by the team at Gimlet Labs and is aimed at developers and ML engineers running PyTorch workloads. Access is currently gated through an early-access waitlist, so the product is pre-release. Pricing and plans are not published, so buyers should confirm cost and supported hardware with the vendor.

What it can do

  • Generates optimized low-level kernels directly from PyTorch code
  • Explores kernel designs with a multi-agent system using shared memory
  • Applies strict correctness checks to generated kernels
  • Automatically identifies the fastest kernel candidates
  • Targets CUDA, ROCm, and Metal backends

Works with

  • PyTorch

Before you choose

  • Access is through an early-access waitlist; pricing and general availability are not published
  • Backends are listed as CUDA, ROCm, and Metal; confirm your specific hardware is covered before committing
  • Generated kernels go through correctness checks, but achieved speedups depend on the target workload

Listed under

Get started

Early-access waitlist is the only start route shown on the page.

  1. Join the early-access waitlist at kforge.ai
  2. Use the kforge CLI once access is granted
  3. Point kforge at a PyTorch workload to generate optimized kernels
Join the waitlist

Plans and prices

Pricing is not published; buyers should confirm cost with the vendor when early access is granted.

kforge has a waitlist and no public prices yet.

Sources for this overview

Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.

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Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.