Continue vs Vellum
Compare coding AI Tools
Continue is an open-source AI coding platform with VS Code and JetBrains extensions plus a CLI, letting developers build custom code agents, choose model providers, and launch background workflows triggered by events or schedules while keeping control of keys and compute.
Vellum is an AI agent building platform that combines a prompt playground, evaluation tools, and hosted agent apps so teams can iterate on LLM workflows with debugging and knowledge base support, starting with a free tier and upgrading for more credits.
Feature Tags Comparison
Key Features
- Open-source extensions: Use VS Code and JetBrains extensions to run Continue agents directly in your editor workflow daily
- Custom AI agents: Build and share reusable agents and blocks with prompts and tools tailored to your stack and repo rules
- Bring your own models: Choose from many model providers and assign roles like chat edit autocomplete embed and rerank per task
- Background automation: Launch background agents and trigger workflows on events or schedules with monitoring and interventions
- Hub Solo plan: Solo hub plan is $0 per developer per month and supports agent sharing plus use of open-source extensions
- Team governance: Team plan adds allow and block lists so admins control which agents and blocks developers can run safely
- Free and Pro plans: Pricing starts at $0 with 50 credits and Pro at $25 with 200 builder credits so solo builders can scale testing
- Prompt playground: Compare models side by side and iterate prompts systematically instead of relying on subjective testing
- Evaluations framework: Run repeatable quality tests at scale to detect regressions and track improvements across prompt versions
- Hosted agent apps: Share working agents with teammates through hosted apps for demos
- reviews
- and stakeholder feedback cycles
Use Cases
- Standardize agents: Create shared agents for code reviews migrations or scaffolding so every developer uses the same playbook
- Model flexibility: Swap providers for chat edits and autocomplete without changing the workflow when requirements shift over time
- Security remediation: Trigger agents from Snyk alerts to propose fixes and open pull requests for review in GitHub quickly
- Incident response: Use Sentry issue triggers to generate candidate patches and create PRs while engineers validate behavior
- Slack workflows: Mention the agent in Slack to kick off tasks and receive updates without manual status chasing later on
- Org key management: Use the managed proxy so developers can run agents with shared keys without exposing secrets to users
- Agent prototyping: Build an agent by chatting with AI then refine logic with low code steps and controlled prompt versions
- Prompt iteration: Compare LLM outputs side by side and select prompts that improve accuracy and reduce unwanted variation
- Regression testing: Run evaluations on a saved dataset before release to catch quality drops after model or prompt changes
- RAG apps: Attach a knowledge base and test retrieval behavior with representative questions and strict document scope rules
- Stakeholder demos: Publish hosted agent apps so product and compliance reviewers can test behavior without local setup steps
- Model selection: Evaluate providers and self hosted options with the same tasks to choose the best cost and latency mix for production
Perfect For
software engineers, platform engineers, developer experience teams, AI tooling leads, security teams automating fixes, startups needing model choice, enterprises needing SSO and on-prem controls
product managers, ML engineers, software engineers, data scientists, AI platform teams, prompt engineers, QA and reliability teams, startups building LLM features, teams shipping agent workflows
Capabilities
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