Fume vs Amp (Sourcegraph)
Comprehensive side-by-side comparison — features, pricing, performance, and more.
Trust & Reliability
Fume
Amp (Sourcegraph)
Too Close to Call
Amp (Sourcegraph) (6.8) vs Fume (6.7) — difference of 0.2 points
Scores are AI-estimated from publicly available data — not an independent test or a verified user rating. How we rank →
Fume
6.7
avg score
Amp (Sourcegraph)
6.8
avg score
Both tools score very similarly overall — the best choice depends on your specific priorities.
Scores are AI-estimated from publicly available data — not an independent test or a verified user rating. How we rank →
Too close to call — it's a tie
Fume
Amp (Sourcegraph)
* Verdict is based on our algorithmic scoring of publicly available data. Learn about our methodology
Fume is best for
Amp (Sourcegraph) is best for
Filter by your use case:
Pros & Cons
FumePros
- Generates 100% Playwright code, ensuring full ownership and local execution
- Automates test design, writing, and maintenance, eliminating manual QA work
- Self-heals flaky tests using an AI agent fallback, improving test stability
- Supports migration of existing Playwright, Selenium, and Cypress tests
- Offers free cloud test runners, reducing infrastructure costs
- Integrates easily into existing CI/CD pipelines with a single API call
Cons
- Requires video input for test generation, which may not suit all testing methodologies
- Focuses primarily on browser testing, potentially limiting scope for other test types
- No visual builder or low-code option for non-developers, requiring some technical familiarity
- Pricing may be a barrier for very small teams or individual developers
- Relies on AI for test generation and maintenance, which may require trust in AI's accuracy
Amp (Sourcegraph)Pros
- Provides complete codebase context to AI agents, reducing missed changes and risks
- Enables large-scale code migrations and refactors in hours instead of days
- Offers enterprise-grade security with SOC 2 Type II and ISO 27001 compliance
- Supports both single-tenant cloud and self-hosted deployment options
- Features zero data retention and no model training on user data
Cons
- Requires technical expertise for full utilization of advanced features
- Pricing for enterprise plans starts at $16K, which may be prohibitive for smaller teams
- No explicit free tier for individual users, only enterprise-focused plans
- Relies on external AI models for agent capabilities, not an inherent LLM
- No mention of specific SDKs or client libraries for custom agent development beyond APIs
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Quick profiles:
Dimension Comparison
Fume
6.7
/ 10
Amp (Sourcegraph)
6.8
/ 10
Dimension Breakdown
Ease of Use
AIHow intuitive is onboarding, UI navigation, and day-to-day usage for the target audience?
Output Quality
AIHow accurate, reliable, and useful are the outputs this product generates?
Value for Money
AIHow well does the pricing match the features and output quality delivered?
Customization
CalculatedHow much can users tailor workflows, settings, prompts, or outputs to their needs?
Support
AIHow strong is the documentation, customer support, community, and learning resources?
Integration
CalculatedHow well does it connect with other tools, APIs, and workflows?
Accuracy & Reliability
AIFactual accuracy and hallucination resistance
Compliance & Data Protection
CalculatedCompliance certifications and data-protection posture, aggregated from verified compliance signals
Performance
CalculatedLatency + throughput speed
Task Completion
AIEnd-to-end task success rate
Tool Use Correctness
AIPicks the correct tool + correct arguments
Planning Quality
CalculatedMulti-step planning depth + replanning capability
Calculated = derived from structured signals (integration count, API/open-source config, compliance certs, response-time). AI = LLM-assessed from public website content. Methodology
Task Performance
Fume
Task
Amp (Sourcegraph)
* Task scores (1–10) are algorithmically generated from publicly available data.