Compare / Amp vs Vertex AI Agent Builder
Head-to-head
Amp vs Vertex AI Agent Builder.
Side-by-side on ratings, pricing, pros, cons, and the honest take on which to pick. Cross-category comparison: Amp is a coding agent and Vertex AI Agent Builder is a enterprise platform.
| Amp | Vertex AI Agent Builder | |
|---|---|---|
| Rating | 4.0 / 5 | 3.5 / 5 |
| Category | Coding Agent | Enterprise platform |
| Tech level | developer | developer |
| Open source | No | No |
| Pricing | Free tier with usage limits. Paid tiers via Sourcegraph subscription. Bundled with Sourcegraph Code Search for teams already on the platform. | Usage-based on Google Cloud: per-token Gemini model costs + Vertex AI infrastructure. Free tier credits available for new accounts. |
| Best for | Engineering teams already paying for Sourcegraph Code Search who want to add an AI agent that reuses the existing codebase index. Free tier is generous enough for individual evaluation. | Engineering teams on Google Cloud who want to build agents using Gemini's long-context capabilities and integrate directly with BigQuery, Cloud Storage, and Google Workspace. |
| Not for | Teams not on Sourcegraph — the standalone story is less differentiated than Claude Code or Augment. Builders who want a simpler CLI experience. | Teams not on Google Cloud — Vertex's value proposition is integration depth that doesn't transfer. Teams that want model flexibility — Vertex is Gemini-only. |
Our verdict on Amp
Sourcegraph's agentic coding tool built on years of code-search investment. Strong for teams already on Sourcegraph; less compelling as a standalone.
Full Amp review →Our verdict on Vertex AI Agent Builder
Google's enterprise agent platform on Vertex AI. Best for Google Cloud teams wanting Gemini-native agents with BigQuery integration. Less useful elsewhere.
Full Vertex AI Agent Builder review →Amp
What works
- Built on Sourcegraph's mature code-search and indexing infrastructure
- Free tier with meaningful usage allowance
- Strong codebase-context story without separate indexing setup
- Native integration with Sourcegraph Code Search
- Sourcegraph's enterprise compliance story (SOC 2, on-prem options) carries over
What doesn't
- Standalone value less compelling than Claude Code or Augment for non-Sourcegraph teams
- Newer to agentic coding than competitors with longer track records
- Smaller community vs Cursor or Copilot
- Locked into Sourcegraph as the indexing/context layer
- Best fit narrows to teams already paying for Sourcegraph
Vertex AI Agent Builder
What works
- Gemini's 1M+ token context window — the largest on the market
- Native integration with BigQuery, Cloud Storage, Google Workspace
- Grounding with Google Search built in (real-time web data)
- Google Cloud security, compliance, and IAM
- Free tier credits for new accounts make evaluation easy
What doesn't
- Gemini-only — no Claude, GPT, or Llama support
- Only makes sense if you're already on Google Cloud
- Slower iteration than Anthropic or OpenAI direct
- Documentation is dense and assumes Google Cloud familiarity
- Enterprise contract overhead at scale
Which to pick
We'd default to Amp (4.0/5 vs 3.5/5) for most builders. Pick Vertex AI Agent Builder if you fit its best-for case specifically: engineering teams on google cloud who want to build agents using gemini's long-context capabilities and integrate directly with bigquery, cloud storage, and google workspace.
Honest middle: most serious operators end up using more than one tool. If you're early in your AI agent journey, our five-question picker recommends a starting platform from your specific situation.
Common questions
Amp vs Vertex AI Agent Builder — which should I pick?
We rate Amp 4.0/5 vs 3.5/5 for Vertex AI Agent Builder. Amp wins for engineering teams already paying for sourcegraph code search who want to add an ai agent that reuses the existing codebase index. free tier is generous enough for individual evaluation. — but pick Vertex AI Agent Builder if you fit its specific best-for case (Engineering teams on Google Cloud who want to build agents using Gemini's long-context capabilities and integrate directly with BigQuery, Cloud Storage, and Google Workspace.). See the head-to-head table above for the full breakdown.
Is Amp or Vertex AI Agent Builder cheaper?
Amp's pricing: Free tier with usage limits. Paid tiers via Sourcegraph subscription. Bundled with Sourcegraph Code Search for teams already on the platform. Vertex AI Agent Builder's pricing: Usage-based on Google Cloud: per-token Gemini model costs + Vertex AI infrastructure. Free tier credits available for new accounts. The right "cheaper" pick depends on usage volume and what's included — see the pricing row in the table above.
What's Amp best for?
Engineering teams already paying for Sourcegraph Code Search who want to add an AI agent that reuses the existing codebase index. Free tier is generous enough for individual evaluation.
What's Vertex AI Agent Builder best for?
Engineering teams on Google Cloud who want to build agents using Gemini's long-context capabilities and integrate directly with BigQuery, Cloud Storage, and Google Workspace.
Why compare Amp and Vertex AI Agent Builder if they're different categories?
Amp is a coding agent and Vertex AI Agent Builder is a enterprise platform. The comparison still matters because builders evaluating one often consider the other for adjacent jobs. See the recommendation section above for how to think about the cross-category choice.
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