Amp vs OpenCode (2026)

Amp

by Sourcegraph

OpenCode

by Anomaly

Pros

• ✓Frontier-first design with unfettered token and tool access: Amp optimizes for output quality rather than minimizing cost, running multi-step threads, subagents, and remote agents that users frequently rate above Claude Code, OpenAI Codex, and Cursor.
• ✓Transparent pay-as-you-go pricing with zero markup: individuals and non-enterprise workspaces pay only pass-through LLM and tool costs from a $5 minimum, with an Amp Free tier and no subscription or commitment.
• ✓Meets developers in place across CLI, VS Code, Cursor, and Windsurf with MCP client support and a plugin system: no new UI to learn, and agents extend through local or remote MCP servers and custom subagents.

Limitations

• ⚠Usage-based pricing makes spend less predictable than per-seat subscriptions: because Amp deliberately spends tokens freely for better results, costs scale with consumption and heavy multi-agent use can add up quickly.
• ⚠Proprietary with no open-source or self-hosted edition: teams wanting a forkable, auditable agent they run on their own infrastructure cannot use Amp, unlike open-source alternatives.
• ⚠Terminal-centric with thin non-G2 signal: Amp is strongest for developers comfortable in the CLI, and independent validation outside its 91 G2 reviews (for example Product Hunt) remains limited for a product this new.

Pros

• ✓Multi-account architecture lets developers log in with GitHub Copilot or ChatGPT Plus/Pro to reuse existing subscription quotas: materially better unit economics than BYOK-only alternatives requiring separate API keys, and better than single-provider tools for teams already paying for Copilot.
• ✓Multi-session parallel agents run simultaneously on the same project, with MCP support for both local and remote servers including OAuth: developers can connect Sentry, GitHub, Linear, and any other MCP-compatible tool without leaving the terminal workflow.
• ✓Privacy-first architecture with no code or context storage, MIT license, and full source available on GitHub: enables deployment in regulated and privacy-sensitive environments where cloud-processing AI tools are prohibited by policy.

Limitations

• ⚠No commercial support, SLA, or compliance certifications: enterprise procurement teams requiring SOC 2, HIPAA, or contracted support cannot use OpenCode as a vendor-backed tool, limiting adoption in regulated industries regardless of technical capability.
• ⚠Multi-provider flexibility creates setup complexity: developers must manage API keys, billing relationships, and model selection across multiple providers, adding initial friction and ongoing account management compared to single-subscription tools like Cursor or Claude Code.
• ⚠No commercial enterprise features: there is no SSO, admin dashboard, centralized billing, or usage analytics, making it unsuitable for managing AI coding tool adoption across engineering teams where visibility and access controls matter.