Available worldwide · Popular in: US
What is PearAI?
A visual IDE built on VSCode that leverages AI agents to automatically generate and modify code, fix bugs, and construct complete projects adhering to modern development best practices. Intelligently routes between multiple AI models to optimize performance.
PearAI pricing
We don't have PearAI's full plan breakdown yet (its pricing page resisted automated reading). Here's what we could confirm. Always check live pricing for exact numbers.
Free tier available. Subscription-based pricing with automatic pay-as-you-go model when users exceed their allocated credits.
What PearAI does
The capabilities that matter for ai coding agents, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Architecture model
- Standalone ide fork cursor
- Terminal bash execution and self correction loops
- ✓
- Mcp model context protocol integration
- -
- Bring your own key byok API support
- -
- Multi file diff generation and automated apply
- ✓
- Workspace indexing and semantic codebase search
- ✓
- Browser automation support for visual qa
- -
- Privacy mode zero data retention for enterprise
- -
- Rag on external documentation urls
- -
- Local LLM support via ollama or lmstudio
- -
- SOC2 type ii
- -
- Mit or apache permissive oss license
- -
- Pricing model
- Flat monthly subscription
Platform & deployment
Independently observed- Web
- Cloud / SaaS
PearAI alternatives
Other ai coding agents we track, ranked by the same independent score.
Compare PearAI
Side by side against other ai coding agents, attribute by attribute, with a source on every value.
The Vioscale score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for PearAI, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Release cadence | 96 | 0.05 | 5.0 | ✓ |
| Capabilities | 58 | 0.08 | 4.9 | ✓ |
| Price level | 80 | 0.05 | 4.2 | ✓ |
| Pricing transparency | 25 | 0.08 | 2.1 | ✓ |
| Stars | 54 | 0.03 | 1.4 | ✓ |
| Reliability | 0 | 0.07 | 0.0 | - |
| Integrations | 0 | 0.09 | 0.0 | - |
| Dependent projects | 0 | 0.06 | 0.0 | - |
| Development activity | 0 | 0.09 | 0.0 | - |
| Security posture | 5 | 0.07 | 0.0 | - |
| Package downloads | 0 | 0.14 | 0.0 | - |
| Security score | 0 | 0.04 | 0.0 | - |
| Developer Q&A activity | 0 | 0.06 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Adoption
| Attribute | Value | Evidence |
|---|---|---|
| Github stars | 766 | highsource · 2026-08-26 · 90% |
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Pricing model: flat_monthly_subscription · Architecture model: standalone_ide_fork_cursor · Multi file diff generation and automated apply: Yes · Workspace indexing and semantic codebase search: Yes · Terminal bash execution and self correction loops: Yes | mediumsource · 2026-08-21 · 60% |
Language
| Attribute | Value | Evidence |
|---|---|---|
| Primary | Shell | highsource · 2026-08-26 · 90% |
Market
| Attribute | Value | Evidence |
|---|---|---|
| Availability | PrimaryMarkets: … · AvailabilityScope: global · AvailableCountries: … · NotAvailableCountries: … | mediumsource · 2026-08-21 · 50% |
Pricing
Release
Security
| Attribute | Value | Evidence |
|---|---|---|
| Gdpr | Yes | highsource · 2026-08-21 · 75% |