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QualGent
Shares tags: ai, code, image-generation
AI Tool
Agent Sandbox Review
Agent Sandbox is a secure code execution tool for AI agents that supports Python and Bash.
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aicodeimage-generation
1Supports secure execution of Python and Bash code.
2Operates on a freemium model with costs only $0.00025/sec for compute.
3Delivers file processing and artifact generation capabilities.
4Compatible with various AI agent frameworks.
overview
What is Agent Sandbox?
Agent Sandbox is a secure coding tool developed by Virgent.ai that enables AI developers to ship AI agents that execute Python & Bash code securely. It features a Sandbox API with file storage, dependency installation, and artifact generation.
quick facts
Quick Facts
| Attribute | Value | |-----------|-------| | Developer | Virgent.ai | | Pricing | Freemium | | Platforms | Web | | API Available | Yes | | Languages | Python, Bash |
features
Key Features of Agent Sandbox
Agent Sandbox provides a variety of features suitable for executing code securely while facilitating interaction among AI agents.
- 1Secure execution environment for Python and Bash code.
- 2Artifact generation for output files.
- 3Dependency installation management.
- 4File storage capabilities.
- 5Integration with existing agent frameworks.
- 6Support for runtime evaluation metrics.
- 7Direct API access with 70B model integration.
- 8Flexible interaction modes (API and WebLLM).
- 9Auto-tracking of tasks and agent interactions.
use cases
Who Should Use Agent Sandbox?
Agent Sandbox is ideal for a range of users who need a secure environment to experiment and deploy AI agents effectively.
- 1AI Developers exploring new agent functionalities.
- 2Agent Builders needing to validate code interactions.
- 3Data Analysts requiring secure code execution for data processing.
- 4Educators and researchers in AI coordination studies.
- 5Professionals designing interactive AI simulations.
pricing
Agent Sandbox Pricing & Plans
Agent Sandbox operates on a freemium pricing model. The first $10 of usage is free, which facilitates initial experimentation without immediate costs. Subsequent use incurs charges of $0.00025 per second for compute and $0.0005 per megabyte for storage.
- 1Freemium: $10 free credits upon sign-up.
- 2Compute: $0.00025/sec.
- 3Storage: $0.0005/MB.
competitors
Agent Sandbox vs Competitors
Agent Sandbox distinguishes itself from various competitors in its focus on secure multi-agent collaboration and cost-effective experimentation.
1
E2B↗
Open-source Firecracker microVM sandbox infrastructure with specialized AI agent SDKs for Python and JavaScript execution.
E2B is a direct competitor offering similar Python/JavaScript code execution with strong AI agent tooling, but limits sessions to 24 hours maximum and lacks persistent state beyond that window. Both target AI agents, but E2B emphasizes open-source flexibility while Agent Sandbox focuses on perpetual sandboxes with indefinite state persistence.
2
Blaxel↗
Perpetual sandbox environments with sub-25ms resume times from standby, maintaining complete filesystem and memory state indefinitely without idle compute charges.
Blaxel directly competes on AI agent code execution with superior standby performance and cost efficiency through perpetual state retention. Unlike Agent Sandbox, Blaxel eliminates the cost tension between instant availability and infrastructure expenses by charging zero compute during idle periods.
3
Modal↗
Serverless platform optimized for Python ML workflows with gVisor container isolation, massive autoscaling to 20,000+ concurrent instances, and GPU support.
Modal is a broader serverless compute platform where sandboxing is one capability, making it less agent-focused than Agent Sandbox. Modal excels at Python-first ML workloads and autoscaling but lacks BYOC options and self-hosting, whereas Agent Sandbox targets lightweight agent code execution.
4
Daytona↗
Fastest cold starts in the market at sub-90ms provisioning using Docker containers with Kata optional isolation for AI workflows.
Daytona competes on speed and ease of use with Docker ecosystem integration, but uses container-based isolation rather than microVMs and offers limited persistence compared to Agent Sandbox's file storage and artifact generation capabilities. It targets quick AI iterations rather than production-grade persistent agent environments.
5
Runloop↗
Enterprise devbox infrastructure for AI coding agents with SOC 2 compliance, snapshot capabilities, and support for 10,000+ parallel instances with custom environment images up to 10GB.
Runloop targets enterprise AI coding assistants with compliance requirements and massive parallel scaling, whereas Agent Sandbox appears more focused on general-purpose agent code execution. Runloop's 2-second startup time and coding-agent specialization differ from Agent Sandbox's broader Python/Bash execution model.
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Frequently Asked Questions
+What is Agent Sandbox?
Agent Sandbox is a secure coding tool developed by Virgent.ai that enables AI developers to ship AI agents that execute Python & Bash code securely. It features a Sandbox API with file storage, dependency installation, and artifact generation.
+Is Agent Sandbox free?
Agent Sandbox operates on a freemium model with $10 free credits upon sign-up. Subsequent usage costs $0.00025/sec for compute and $0.0005/MB for storage.
+What are the main features of Agent Sandbox?
Agent Sandbox provides secure execution of Python and Bash code, artifact generation, file processing capabilities, dependency installation, and an API for flexible interaction.
+Who should use Agent Sandbox?
Agent Sandbox is suitable for AI developers, agent builders, data analysts, educators, and researchers interested in AI systems.
+How does Agent Sandbox compare to alternatives?
Agent Sandbox differentiates itself with browser-based interaction and free usage for initial experiments compared to competing products focused primarily on cloud execution.