Tag
Gpu tools
5 reviewed tools: 5 free or open source.
Order: free and open source first, then hosted products with a real free tier, then paid-led; catalog order inside each group, with quiet or archived repos last. Not a score, and no tool pays for its place.
5 tools
- ZedGPL-3.0 GPU-accelerated editor with first-party agents
Free / OSS · GPL-3.0 · 91.9k GitHub stars
VerdictThe fast open editor. GPL-3.0, agents in-process, no invented Cloud giveaway.
CatchGPL-3.0 is copyleft, not MIT. Hosted agent features that talk to Zed's models are a product on top of the editor — no Cloud free tier to count on. Web is not shipped.
- GhosttyMIT GPU-accelerated native terminal emulator
Free / OSS · OSS/MIT · 62.4k GitHub stars
VerdictMIT GPU terminal. Free forever; the window is Ghostty, the layouts are still Zellij.
CatchVs Zellij (Rust *workspace/layouts/plugins*) and Helix (modal *editor*): Ghostty is the *emulator*, not a muxer and not an editor. You still pick tmux/Zellij or Helix inside it. Official app is macOS + Linux; Windows GUI is not shipped.
- HAMiApache-2.0 CNCF project that shares and slices GPUs and other accelerators across Kubernetes workloads
Free / OSS · Apache-2.0 · 4.9k GitHub stars
VerdictThe CNCF way to pack many small GPU jobs onto shared cards — validate isolation per accelerator vendor.
CatchIt is a scheduling layer for a GPU cluster you already run, not a model server — you still bring vLLM, Triton or whatever serves the model. How limits are enforced depends on each vendor’s device backend, so isolation and overcommit behaviour differ between NVIDIA and other accelerators; test the limits on your hardware before you rely on them.
- SGLangApache-2.0 high-throughput LLM and multimodal serving
Free / OSS · Apache-2.0 · 37.3k GitHub stars
VerdictA top-tier open LLM serving engine beside vLLM — free software, the bill is GPUs; benchmark both on your workload.
CatchA GPU serving engine, not a laptop chat app — expect driver, CUDA/ROCm and multi-GPU ops, and you pay for the hardware. Install currently needs `--prerelease=allow`. Vs vLLM (same lane): both are open, OpenAI-compatible serving engines — benchmark your own model and traffic rather than trusting either side's charts. Vs llama.cpp: SGLang is for many concurrent users on accelerators; llama.cpp is for one machine.
- TokenSpeedMIT LLM inference engine built for agent workloads
Free / OSS · OSS/MIT · 2.7k GitHub stars
VerdictA fast-moving inference engine for agent traffic on top-end NVIDIA hardware — benchmark it beside vLLM before committing.
CatchVery early (v0.1.1), so expect breaking changes. The kernel work targets recent NVIDIA data-center GPUs such as Blackwell, so gains on older or consumer cards are unclear. It covers fewer models than vLLM — check yours is supported before you switch.
FAQ
- What is the top free pick among Gpu tools?
- Zed leads the Stack Gems list for Gpu tools. Verdict: The fast open editor. GPL-3.0, agents in-process, no invented Cloud giveaway.
- How many Gpu tools does Stack Gems review?
- 5: 5 free or open source. Each review has a verdict and an honest Catch; no tool pays for its spot.
- Which Gpu tools can I self-host for free?
- Zed, Ghostty, HAMi, SGLang and TokenSpeed.
- Which Gpu tools have the most GitHub stars?
- Zed (91.9k), Ghostty (62.4k), SGLang (37.3k), per GitHub on 2026-10-19. Stars measure attention, not fit; read the Catch.
- What is the catch with Zed?
- GPL-3.0 is copyleft, not MIT.