oMLX vs PageIndex: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of oMLX and PageIndex — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
oMLX
Jun Kim
An open-source native macOS LLM inference server built on MLX whose paged SSD KV cache drops coding-agent time-to-first-token from 30-90s to under 5s.
Key features
- Paged SSD KV Caching: Cache blocks persist to disk in safetensors format with hot blocks in RAM and cold blocks on SSD, so previously seen prefixes are restored in milliseconds and survive server restarts.
- Sub-5s Agent TTFT: Cuts time-to-first-token for coding agents from 30-90 seconds down to under 5 seconds from the second turn onward.
- Continuous Batching: Handles concurrent requests through mlx-lm's BatchGenerator, measured at up to 4.14x generation speedup at 8x concurrency.
- OpenAI and Anthropic Drop-In API: Serves both OpenAI-compatible endpoints and a native Anthropic /v1/messages endpoint so Claude Code, OpenClaw, and Cursor connect without adapters.
- Multi-Model Serving: Loads LLM, VLM, embedding, and reranker models at the same time with LRU eviction when memory is constrained.
- Native Menu Bar App: A signed and notarized macOS app with in-app auto-update to start, stop, and monitor the server, plus a web dashboard for model management and live metrics.
- Tool Calling and MCP: Supports JSON, Qwen, Gemma, GLM, and MiniMax tool-calling formats with MCP integration and configurable trimming of oversized tool results.
- Config Command Generation: The dashboard emits the exact configuration command for each supported client tool.
Best for
- Local Coding Agents: Run Claude Code or OpenClaw entirely against a local model without the 90-second waits that make local inference impractical for agents.
- Private Codebase Work: Keep proprietary source on-device by pointing an OpenAI-compatible IDE assistant at a local endpoint.
- Offline Development: Continue agent-assisted coding without network access or per-token API costs.
- Model Benchmarking: Compare Qwen3.5-122B, Qwen3-Coder-Next, MiniMax-M2.5, and GLM-5 throughput on the same Apple Silicon hardware.
- Multi-Client Serving: Serve several concurrent agent sessions from one Mac using continuous batching rather than queuing behind a single request.
- RAG on a Mac: Host an LLM alongside embedding and reranker models in a single process for local retrieval pipelines.
PageIndex
Vectify AI
Vectorless, reasoning-based RAG engine that indexes long documents as a tree and lets an LLM reason through it, with traceable citations.
Key features
- Tree Index Instead of Vectors: Builds a hierarchical index from the document's own sections, so there is no chunking, no embeddings and no vector database to maintain.
- Reasoning-Based Retrieval: An LLM agentically searches the tree using full context including conversation history and domain knowledge, rather than matching a query embedding.
- Traceable Citations: Answers carry explicit page-level references locally and line-level citations on Cloud, so every claim can be checked against the source.
- PageIndex Flash: Extracts tree structure from PDFs in seconds using the document's own layout information instead of building it with an LLM.
- Local or Cloud SDK: pip install pageindex runs indexing, retrieval and chat entirely on your machine with your own key, or points the same client at PageIndex Cloud with an API key.
- MCP Server and API: Connect document reasoning to Claude, Claude Desktop, Cursor or any MCP client, with API-key auth for developers and OAuth for chat users.
- PageIndex File System: A Cloud-only file-level tree indexing layer that lets retrieval reason across an entire corpus rather than one document at a time.
- Agent Framework Integrations: Ships integration paths for the OpenAI Agents SDK, the Anthropic SDK tool runner, the Claude Agent SDK and other frameworks.
Best for
- Financial Document QA: Answer questions about 10-Ks, earnings reports and filings with the page the figure came from, the workload where it set a 98.7% FinanceBench record.
- Legal and Regulatory Review: Retrieve the governing clause from contracts and regulatory filings where the relevant section is rarely the most semantically similar one.
- Technical Manual Lookup: Find the correct procedure in long technical manuals where context and document hierarchy determine which section actually applies.
- Medical and Academic Research: Reason over medical literature and textbooks that exceed a model's file size limits, with verifiable references.
- Agent Document Tooling: Give an AI agent long-document reasoning via MCP so it can handle PDFs that models cannot ingest directly.
- Enterprise Knowledge Bases: Index large document collections in the cloud with OCR and image understanding, and reason across the whole corpus with the File System layer.