GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
BudgetML is a Python library that facilitates the deployment of machine learning inference services using Google Cloud Preemptible instances, offering significant cost reductions.
Good fit when
- When you need to deploy machine learning inference services with a tight budget, as BudgetML can reduce costs by up to 80 percent using Google Cloud Preemptible instances.
- If your project involves memory-intensive tasks like ML model inference functions and you are looking for cost-effective solutions, BudgetML can save you up to $370 per month with the highest instance
Avoid when
- If your application cannot tolerate the risk of instance preemption, as BudgetML relies on Google Cloud Preemptible instances that can be terminated with short notice.
- When you require high availability and reliability, as preemptible instances can be interrupted, which might not be suitable for mission-critical applications.
- Pricing:
- freemium - BudgetML is free to use under the Apache-2.0 license, but users must cover the cost of Google Cloud Preemptible instances, which can be up to 80 percent cheaper than regular instances.
- Requirements:
- Min 4 GB RAM; Requires access to Google Cloud Preemptible instances.
Observed Sep 18, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (948d since push)
- As of Sep 18, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 18, 2026
- Security (OSV)
- No criticals
- As of Sep 18, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install budgetmlSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
BudgetML is a Python library that enables users to deploy machine learning inference services using Google Cloud Preemptible instances to significantly reduce costs.
Capability facts
- Languages
- python
Source: github.language · Sep 18, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Tags
README
Cost comparison BudgetML uses Google Cloud Preemptible instances under the hood to reduce costs by 80%. This can potentially mean hundreds of dollars worth of savings. Here is a screenshot of the GCP series, which is regular family of instances to be using for memory intense task...
For agents
This page has a .md twin and JSON over the API.