💳 Per-request billing
fal.ai
The Kings of Real-Time Vision fal.ai has taken the AI…
Vision (SDXLSD3)AudioVideo
⚙ Custom SDK
from$0.99
/ request
Brev.dev
🤖 Managed InferenceDevelopers wanting one-click GPU environments without managing raw infrastructure.
The Developer Workstation, Reimagined
Brev.dev is fundamentally different from serverless inference APIs. It is a managed GPU workspace provider designed to solve the immense pain of configuring local AI environments. Instead of fighting with CUDA drivers, PyTorch versions, and Docker networking on a local machine, developers use Brev to spin up a dedicated cloud GPU (like an A10G or A100) that instantly connects to their local VS Code editor.
From Prototype to Production
Brev provides the perfect bridge between prototyping and deployment. Data scientists can interactively write code, fine-tune models, and run inference scripts on powerful hardware without worrying about serverless timeouts or strict API rate limits. Once the model is performing correctly in the Brev environment, the code can be seamlessly transitioned to a production inference provider.
Cost Efficiency
By aggregating compute from various cloud providers (including AWS and obscure boutique hosts), Brev offers highly competitive hourly rates for dedicated GPUs. They also provide auto-sleep functionality, meaning the massive GPU instances spin down automatically when the developer closes their laptop, preventing accidental weekend bills that plague traditional AWS deployments.
Supported Workloads
TrainingFine-TuningInference
Pros & Cons
Pros
- Instant VS Code environments on massive GPUs
- Eliminates local CUDA/driver configuration hell
- Incredibly cost-effective for dedicated development
Cons
- Not a managed serverless API
- Requires DevOps knowledge to push to production
Served Models
Bare Metal Access
Data Privacy Policy
Customer-managed
Custom SDK / Client
Custom Integration. This provider requires their own specific SDKs or libraries to interact with the models. See official documentation.
Quick Start Snippet
Python
import requests
headers = {
'Authorization': 'Bearer YOUR_API_KEY',
'Content-Type': 'application/json'
}
data = {
'model': 'your-chosen-model',
'prompt': 'Hello, world!'
}
response = requests.post('https://brev.dev/v1/completions', headers=headers, json=data)| Website | Visit Official Site ↗ |
Billing Model
Per-second billing
You are charged exclusively for the duration the GPU is actively processing your request. Excellent for bursty workloads.
NVIDIA Dynamo and Brev Scale AI Agent Inference to Planetary Level
What Does NVIDIA's Acquisition of Brev Mean for AI Developme
What New Features Does Brev 2.5 Offer for Developers?
Brev.dev (Acquired by NVIDIA) Revenue 2025: $440K ARR
State of Akash Q4 2024
Community Discussions
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Frequently Asked Questions
Brev.dev uses a per-second billing model. You pay only for what you use — no idle server costs.
Brev.dev has its own API. Check their documentation for integration guides.
Brev.dev supports Training, Fine-Tuning, Inference. Use the API to deploy custom models or use their pre-built endpoints.
Brev.dev does not have a publicly listed free tier. Contact them for trial access or pilot pricing.
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