Amp vs NOVA (2026)

Amp

by Amp Frontier Corporation

NOVA

by Bridgeye

Pros

• ✓Each thread can run in a cloud orb set up with the project's code, tools and plugins, so agents keep working after the laptop closes, and threads can be started or followed from the web, Mac, iPhone or the CLI.
• ✓Multi-model by design: four modes route work across OpenAI, Anthropic and fast models, and on Hobby, Individual and Teams developers can bring a ChatGPT subscription or their own keys with no Amp token fees.
• ✓Team features come at no extra charge, including shared threads, multiplayer, shared portals, plugins and skills and pooled credits, and a GitHub App lets agents open pull requests and read CI status.

Limitations

• –Model usage beyond a tier's included credits is paid separately, through the developer's own provider subscription or keys or through Amp credits at provider API prices, and purchased credits expire after twelve months.
• –Paid tiers are billed monthly and orb time is metered by the minute: Megawatt's 45,000 minutes go faster on larger orbs, and the largest orb size is limited to Gigawatt and Enterprise.
• –SCIM, audit logs, IP allowlisting and regional endpoints are on the quote-based Enterprise tier, and SAML or OIDC SSO needs at least one workspace member on a paid tier.

Pros

• ✓NOVA's self-healing execution loop automatically detects runtime failures, analyzes tracebacks, identifies the failing file, and proposes fixes including missing dependency installation, reducing the manual debug cycle that typically requires copying errors between a terminal and an AI chat window.
• ✓The free tier includes 40,000 tokens per day with 25 healer runs and 25 janitor runs, enough for individual developers to evaluate the tool on real projects before committing to a paid plan starting at $14/month.
• ✓Installation is frictionless via pip, npm, or native macOS and Windows installers with no account required to start, and the privacy policy confirms that user code is not stored on Bridgeye's servers and is not used to train AI models.

Limitations

• –NOVA's GitHub repository has only 5 stars, 3 commits, and 0 forks, indicating extremely early-stage development with no meaningful community adoption, no contributor ecosystem, and significant risk that the project may not be actively maintained long-term.
• –Integration depth is terminal-only with no IDE plugins for VS Code or JetBrains, no MCP support, no team collaboration features, and no integrations marketplace, limiting NOVA to solo developers comfortable working entirely in the CLI.
• –The self-healing loop handles single-file errors and dependency resolution but lacks the deep multi-file contextual reasoning, codebase-wide refactoring, and pull request automation that more mature alternatives like Cursor, Claude Code, and GitHub Copilot provide at comparable or lower price points.