The hardware desk / DVIDIA × OWterminal

Your hardware.
A place to begin.

Find a machine for an open model. Connect a camera for a useful demonstration.

Find your machine.

Compare on OWterminal

16 community-reported setups · snapshot 2026-09-21. This is a research catalog; these machines are not a live fleet available to rent.

8 hardware entries

Product family pictured · exact reported configuration unverified
Product family pictured · exact reported configuration unverified

Apple / Unified memory

M4 Pro

Reported memory
Capacity not reported
Setup path
MLX / Metal
Explore 4 model reports
How to use this hardware
  1. Check your Mac’s chip and unified memory in About This Mac.
  2. Choose an Apple Silicon runtime and a model build it supports.
  3. Compare the report’s memory and context with your configuration, then try your own task.
MLX setup guide
Product family pictured · exact reported configuration unverified
Product family pictured · exact reported configuration unverified

Apple / Unified memory

M5 Max

Reported memory
Capacity not reported
Setup path
MLX / Metal
Explore 1 model report
How to use this hardware
  1. Check your Mac’s chip and unified memory in About This Mac.
  2. Choose an Apple Silicon runtime and a model build it supports.
  3. Compare the report’s memory and context with your configuration, then try your own task.
MLX setup guide
Two Spark units pictured · matches reported configuration
Two Spark units pictured · matches reported configuration

NVIDIA / Desktop AI system

2× DGX Spark

Reported memory
Capacity not reported
Setup path
Spark-compatible runtime
Explore 2 model reports
How to use this hardware
  1. Follow NVIDIA’s setup playbook for your Spark and chosen runtime.
  2. Check the model build and runtime support for the machine’s architecture.
  3. These reports use two Spark units. A single unit is a different configuration.
NVIDIA Spark playbooks
RTX 4090 pictured as a GPU reference · this model differs
RTX 4090 pictured as a GPU reference · this model differs

NVIDIA / Discrete GPU

RTX 5090 32GB

Reported memory
32 GB VRAM
Setup path
CUDA-compatible runtime
Explore 2 model reports
How to use this hardware
  1. Check the exact GPU, available VRAM and NVIDIA driver on your computer.
  2. Use a runtime build that supports your GPU and a compatible model format.
  3. Start with a build that fits your memory. Larger context and CPU offload change performance.
llama.cpp setup guide
RTX 4090 pictured · board designs vary
RTX 4090 pictured · board designs vary

NVIDIA / Discrete GPU

RTX 4090 24GB

Reported memory
24 GB VRAM
Setup path
CUDA-compatible runtime
Explore 1 model report
How to use this hardware
  1. Check the exact GPU, available VRAM and NVIDIA driver on your computer.
  2. Use a runtime build that supports your GPU and a compatible model format.
  3. Start with a build that fits your memory. Larger context and CPU offload change performance.
llama.cpp setup guide
RTX 4090 pictured as a GPU reference · this model differs
RTX 4090 pictured as a GPU reference · this model differs

NVIDIA / Discrete GPU

RTX 5060 Ti 16GB

Reported memory
16 GB VRAM
Setup path
CUDA-compatible runtime
Explore 4 model reports
How to use this hardware
  1. Check the exact GPU, available VRAM and NVIDIA driver on your computer.
  2. Use a runtime build that supports your GPU and a compatible model format.
  3. Start with a build that fits your memory. Larger context and CPU offload change performance.
llama.cpp setup guide
RTX 4090 pictured as a GPU reference · this model differs
RTX 4090 pictured as a GPU reference · this model differs

NVIDIA / Discrete GPU

RTX 3060 12GB

Reported memory
12 GB VRAM
Setup path
CUDA-compatible runtime
Explore 1 model report
How to use this hardware
  1. Check the exact GPU, available VRAM and NVIDIA driver on your computer.
  2. Use a runtime build that supports your GPU and a compatible model format.
  3. Start with a build that fits your memory. Larger context and CPU offload change performance.
llama.cpp setup guide
RTX 4090 pictured as a GPU reference · this model differs
RTX 4090 pictured as a GPU reference · this model differs

NVIDIA / Discrete GPU

GTX 1660 SUPER 6GB

Reported memory
6 GB VRAM + 40 GB RAM
Setup path
CUDA-compatible runtime
Explore 1 model report
How to use this hardware
  1. Check the exact GPU, available VRAM and NVIDIA driver on your computer.
  2. Use a runtime build that supports your GPU and a compatible model format.
  3. Start with a build that fits your memory. Larger context and CPU offload change performance.
llama.cpp setup guide

A report shows what someone ran on a specific setup. Check the exact model build, memory, operating system and runtime before downloading or buying. DVIDIA has not reproduced these reports.

Want to connect compute to DVIDIA?

Provider onboarding is in development. You can research hardware and run models locally now; connecting a machine to paid network requests is not available yet.

Explore inference