u/Safe-Introduction946

Vast ships as a plugin for Claude Code, Codex, and Cursor. Search, launch, monitor, and tear down GPU instances without leaving your editor — tell the agent what you want, or run a slash command directly. Safe defaults keep it from doing anything expensive by accident.

And once you're on a box, the instance explains itself. Every image hands the agent a short guide plus a vast-capabilities command — what's installed, what's running, how to reach it — so the agent can drive the machine instead of guessing its way around. Point it at GPU work and walk away.

No plugin? Install the skill in any agent that supports them:

npx skills add vast-ai/vast-cli --skill vastai

Get started here: docs.vast.ai/guides/get-started/agents

A new guided terminal setup that replaces the CLI script. It walks you through each step, validates your driver, hardware, ports, and speed before installing, and gives plain-English fixes instead of stack traces.

Why we think you'll be excited about it:

• Checks run before the install, not during it. Driver/CUDA, GPU/CPU/RAM/OS, disk, upload speed, and port reachability are each validated on their own page. A bad config fails in seconds instead of 20 minutes in.
• Ports and network speed are tested up front. The two most common reasons a machine installs fine but never goes rentable. The wizard confirms your ports are reachable and that you're above the 500 Mbps minimum before you commit.
• API key is validated when you enter it. Not at the end. If the key's wrong, the daemon never starts and your machine never appears in your dashboard — so the wizard checks it early.
• A self-test confirms the machine is actually rentable. Pass/fail at the end, so you're not left guessing whether the install "worked" but the box still won't earn.
• Real logs, real errors. Live-tails vast_host_install.log during the run. On failure you get the last 500 lines inline, the full log path, and a suggested fix mapped to the error — not a raw stack trace.
• No setup to run it. Single self-contained binary (~30 MB, bundles its own Python 3.12). No venv, no pip, no dependencies on the host.

Find the guided TUI installer here: https://cloud.vast.ai/host/setup/

Blackwell Ultra architecture, 288GB HBM3e memory, 20,480 CUDA cores, and 8 TB/s bandwidth. Built for large-scale AI inference, reasoning models, and distributed training.

Absolute unit. Early supply is limited. First to spin one up wins
→ https://vast.ai/pricing/gpu/B300

Sitting on B300 capacity that isn't fully utilized? Demand is way ahead of supply right now — list them and put them to work.
→ https://vast.ai/data-center-application

Get a data-backed earnings estimate based on current GPU utilization and marketplace pricing. Set your price, see your range.

Check it out here: https://vast.ai/hosting/calculator

and give us feedback on discord, on the host ⁠feature-requests channel.

Disclaimer: Vast.ai does not guarantee any level of utilization or earnings.

Ramp tracks real spend data across 50,000+ businesses. Vast.ai landed in the Trending category — breakout growth relative to size — the same signal that flagged Anthropic and Perplexity before they became household names.

Read more here.

We've shipped a major upgrade to two-factor authentication on Vast. Five things to know:

• Authenticator app support: use any TOTP app (Google Authenticator, 1Password, Microsoft Authenticator, etc.) instead of SMS
• CLI 2FA: 2FA now works through the Vast CLI
• Team enforcement: team owners can now create roles with permissions that require 2FA to be used
• Backup codes: automatically generate one-time recovery codes so you're never locked out
• Multiple methods: register more than one per account

Migration notice — Action required if you use the old (legacy) SMS 2FA The legacy 2FA is being deprecated. So if you currently use 2FA, log in normally, go to the Settings Page, and click "Regenerate" on the backup codes section to migrate to the new 2FA. Takes under a minute.

How to set up: Enable 2FA in Settings → Full setup guide

Building on Vast? Get pricing alerts, beta features, and direct access to the team in our Discord — 10,000+ members → discord.gg/vast

Kimi K2.6 is an open-source, native multimodal agentic model from Moonshot AI that advances practical capabilities in long-horizon coding, coding-driven design, proactive autonomous execution, and swarm-based task orchestration. It is a Mixture-of-Experts model with 1 trillion total parameters and 32 billion activated per token, built on the Kimi K2.5 architecture.

Learn more about the Kimi K2.6 template in the model library: https://vast.ai/model/kimi-k2.6

Gemma 4 is Google DeepMind's next-generation family of open multimodal models.

The 26B A4B variant is a Mixture-of-Experts model with 25.2B total parameters but only 3.8B active per token, delivering frontier-level quality at the inference speed of a much smaller dense model. It handles text and image input natively, supports a 256K context window, and covers 140+ languages.

The 31B variant is the dense flagship of the family, built to deliver frontier-level reasoning, coding, and multimodal understanding on consumer GPUs and workstations. It natively handles text and image input, supports a 256K context window, and covers 140+ languages.

Read more about the Gemma 4 templates in the model library:

• Gemma 4 – 26B A4B: https://vast.ai/model/gemma-4-26b-a4b-it
• Gemma 4 – 31B IT: https://vast.ai/model/gemma-4-31b-it