Faiss vs Vellum
Compare coding AI Tools
High performance vector similarity search and clustering library from Meta with CPU and GPU support under the MIT license.
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
- Efficient CPU and GPU indexes for dense vectors
- Algorithms like IVF PQ HNSW for speed and memory
- Python wrappers for fast prototyping
- Scales to billion plus vectors with sharding
- Rich evaluation and tuning utilities
- Mixed precision and quantization support
- 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
- Build local RAG retrieval for LLM apps
- Speed up product and content recommendation
- Detect near duplicates and spam in large sets
- Cluster embeddings to discover segments
- Run similarity search on edge or on prem
- Compress indexes to fit tight memory budgets
- 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
ml engineers search infra teams applied researchers and startups building RAG recommendation or deduplication using permissively licensed tooling
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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