GPU CLI

Run any command on a remote GPU from your terminal

[GPU CLI @gpucli]

Searching for a faster way to find the best deal to rent that GPU you need?

https://t.co/8jdIIeP2Rl just shipped 🚢

Now you can now compare prices from @runpod, @vast_ai, @ThunderCompute & more in one place.

[GPU CLI @gpucli]

@ideogram_ai This is incredible, excited to try it!

[James Lal @lightsofapollo2]

What was used to rewrite Bun into Rust apparently

[James Lal @lightsofapollo2]

I wanted faster builds so I explored how to conditionally build our rust monorepo based on the cargo dependency graph - packaged it up as a github action for reuse across projects https://t.co/eZ8IMp7b1d

[Brendan Falk @BrendanFalk]

To check if your Google Workspace has been compromised by the same tool that compromised Vercel:

1. Go to https://t.co/TpuIOW5Fwg
- This is Google Admin Console > Security > Access and Data Control > API Controls > Manage app access > Accessed Apps
2. Filter by ID = https://t.co/uqJnCqp5Ah
- This is the ID of the compromised OAuth app

If you see an app after filtering, you have potentially been compromised

[vLLM @vllm_project]

We're proud to share that @NVIDIA submitted the first-ever MLPerf Vision Language Model (VLM) performance benchmark using vLLM. This achievement showcases the strength of our ongoing collaboration with NVIDIA Engineering.

Check out their MLPerf blog and watch our On Demand Talk at GTC to learn more about how we are delivering the best performance on NVIDIA hardware.

🔗 Blog: https://t.co/sImlVjkMKW
🔗 Talk: https://t.co/dyDnQUG3AX

[Min Choi @minchoi]

Netflix just dropped VOID.

This AI removes objects from video...

And even corrects the physics after objects/people are removed.

Demo in commets👇

[GPU CLI @gpucli]

Find this template and many others in our repo here https://t.co/VORt85DBD1

[GPU CLI @gpucli]

We're excited to announce we've just made working with #Unsloth Studio on cloud GPUs way easier with our new dedicated template.

This means training and running models is as simple as working with your local device and as powerful as the hardware you want to use.

#LLM #MLOps

[GPU CLI @gpucli]

Then, just run `gpu use unsloth-studio` and wait for the build to finish.

Now you're ready to go!

[GPU CLI @gpucli]

One of the tougher parts of running OSS models is knowing what you can actually run on your hardware (or what hardware you need to run a specific model).

If that's you, check out this gem by Alex Jones

https://t.co/7D2pfZ6F1o

[GPU CLI @gpucli]

But what about the setup overhead? Thankfully GPU CLI makes running these models and many others from your terminal as easy as copy + paste, then selecting a machine.

Find us here https://t.co/qZEiw1X2Dh

[GPU CLI @gpucli]

Many people using the OpenAI API don't need to be.

OSS models have closed the gap for everyday tasks and the hardware to run them is cheap to rent with services like RunPod and VastAI.

If you don't need a top tier model, here are some alternatives that could save you money.

[GPU CLI @gpucli]

2. A100 80GB on RunPod + Qwen3-32B
- Price: $1.19/hr
- Nearest OpenAI tier: GPT-5.4 at $15/million output tokens.

Closer to frontier quality, still meaningfully cheaper at scale for most tasks.

[Rohan Joshi @ron_joshi]

Introducing Kitten TTS V0.8: open-source TTS that fits in 25MB.

Three variants: 80M | 40M | 14M (<25MB)

Highly expressive. Runs on CPU. Built for edge.

No GPU? No problem. Ship voice anywhere.

Check it out:

[Angus Bezzina @angus1192]

Check it out here https://t.co/tMtgyZBKHK

[GPU CLI @gpucli]

What’s the most important aspect of an AI agent’s memory to you?

[vLLM @vllm_project]

🎉 Congrats to @MistralAI on releasing Mistral Small 4 — a 119B MoE model (6.5B active per token) that unifies instruct, reasoning, and coding in one checkpoint. Multimodal, 256K context.

Day-0 support in vLLM — MLA attention backend, tool calling, and configurable reasoning mode, verified on @nvidia GPUs.

🔗 https://t.co/eDfQadxmiC