Lightpanda vs opensandbox
Two of the top projects in Sandboxes, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
Lightpanda
Headless browser written in Zig for agents and scraping, with CDP and MCP
opensandbox
Sandbox API for running AI agent code, commands and browsers in isolation
Verdict
Lightpanda ranks higher, 94 to 87. Of the 4 score parts we measure for both, Lightpanda leads on 2, opensandbox on none and 2 are even.
- AdoptionLightpanda leads by 21 points, 95 to 74: a wide gap.
- FreshnessEven at 100.
- MaintenanceLightpanda leads by 1 point, 94 to 93: close to even.
- Agent-readyEven at 70.
Pick Lightpanda if you are
Engineers running browser automation, scrapers or web agents at scale
- README benchmark: 123MB peak vs 2GB for headless Chrome over 100 pages
- Speaks CDP, WebDriver BiDi and MCP, so Puppeteer and Playwright clients can connect
Pick opensandbox if you are
Engineers needing isolated code execution for agents on their own infrastructure
- SDKs in five languages plus osb CLI and MCP server
- Same lifecycle API for local Docker and Kubernetes deployments
| What we compare | Lightpanda | opensandbox |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 95, widely used | 74, popular |
| Freshness | 100, active | 100, active |
| Maintenance | 94, healthy | 93, healthy |
| Agent-ready | 70, partly | 70, partly |
| Facts from GitHub and the README | ||
| Stars | 42k | 17.2k |
| License | AGPL-3.0 (copyleft) | Apache-2.0 (permissive) |
| Last commit | Nov 2026 | Nov 2026 |
| Last release | Nov 2026 | Oct 2026 |
| Language | Zig | Go |
| Docker | Yes | Yes |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Mentioned | Not stated |
Lightpanda
Lightpanda is a headless browser written from scratch in Zig, using V8 for JavaScript, libcurl for HTTP and html5ever for parsing, with no graphical rendering. It exposes a CDP server for Puppeteer and Playwright, WebDriver BiDi, an MCP server over stdio or HTTP, and a fetch command that dumps pages as HTML or Markdown. An agent mode records sessions as replayable scripts.
Who it is for: Engineers running browser automation, scrapers or web agents at scale
Strengths
- README benchmark: 123MB peak vs 2GB for headless Chrome over 100 pages
- Speaks CDP, WebDriver BiDi and MCP, so Puppeteer and Playwright clients can connect
- Agent mode supports many LLM providers and local Ollama or llama.cpp, or runs with --no-llm
- Agent sessions export to deterministic scripts that replay without a model
Weaknesses
- No graphical rendering; web platform coverage is partial (see WPT results)
- No native Windows binary; needs WSL2, and Linux binaries need glibc
- Usage telemetry is on by default and must be disabled via environment variable
- AGPL-3.0 license and a CLA required for contributions
- no GPU
- Docker
- Needs Puppeteer or Playwright (optional client), LLM provider API key (agent mode only)
- Models: Anthropic, OpenAI, Gemini, Google Vertex AI, Mistral
- port 9222
opensandbox
OpenSandbox provides isolated environments where agents execute code, run shell commands, manage files and drive browsers or desktops, through a single lifecycle API. It runs locally on Docker and scales to Kubernetes, with SDKs for Python, Java/Kotlin, TypeScript, C#/.NET and Go, plus an `osb` CLI and an MCP server. Egress policies, an ingress gateway and a credential vault control network access.
Who it is for: Engineers needing isolated code execution for agents on their own infrastructure
Strengths
- SDKs in five languages plus osb CLI and MCP server
- Same lifecycle API for local Docker and Kubernetes deployments
- Per-sandbox egress policies and a credential vault keep real secrets out of workloads
- Firecracker runtime with pause/resume; reported 64 ms P50 creation time
Weaknesses
- Docker required for local use; Kubernetes setup needed for the fast runtime
- No hosted demo or playground listed in the README
- Firecracker and pause/resume features documented only for the Kubernetes fast runtime
- Server needs separate install and TOML configuration before first use
- no GPU
- Needs Docker, Python 3.10+, Kubernetes (optional, for cluster deployment)
More in Sandboxes
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