Vs · Windsurf

Anvaya vs Windsurf.

Cascade flows in a polished IDE against memory-first terminal autonomy. Flow state vs compound knowledge.

Direct answer

Anvaya vs Windsurf: Windsurf is the flow-state IDE, a VS Code fork whose Cascade agent runs multi-step, multi-file flows with visual diffs and persistent session memory, on subscription tiers. Anvaya is the memory-first terminal agent: a local Ollama path with no account or key, fully offline-capable, 21 native tools, subagents and swarm orchestration with merge gates, and a local knowledge graph (typed nodes with half-lives, git drift detection, Beta-Bernoulli utility) targeting 2–4K packed tokens per turn. Windsurf wins in-editor flow and review UX; Anvaya wins autonomy depth, privacy (local by default), and knowledge that compounds across sessions rather than resetting per flow. Many teams will keep Windsurf for daily flows and add Anvaya for deep refactors, CI runs, and shared memory over MCP.

The Table

Side by Side.

DimensionWindsurfAnvayaWinner
Primary surfaceIDE fork + CascadeTerminal TUI + headlessDifferent layers
Multi-file UXVisual diffs, flowsSubagents + merge gatesWindsurf on review
Memory modelSession-persistent flowsTyped graph, calibratedAnvaya on compounding
Autonomy depthFlow-boundedSwarm + CI + 100+ roundsAnvaya on depth
Offline/privateCloud-routedFully localAnvaya
Entry priceFree tier + Pro$0 local loopTie

Questions

Asked About the Two.

Q

How is Anvaya different from Windsurf?

Windsurf is an AI-native IDE (VS Code fork) whose Cascade agent orchestrates multi-file flows with persistent session memory inside the editor. Anvaya is terminal-first and local-first: Ollama-first with no account or key, offline-capable, a static binary, plus a memory graph that compounds across sessions (typed nodes, decay, drift detection, outcome calibration) instead of per-flow session state.

Q

Which handles multi-file work better?

Windsurf's Cascade is purpose-built for in-editor multi-file orchestration with visual diffs, the smoother review experience. Anvaya's subagents plus swarm packs handle larger autonomous multi-file missions with merge gates, grounded in repomap call graphs and calibrated project memory. Editor review vs autonomous depth.

Q

Can Windsurf use Anvaya's memory?

Any MCP-capable client can: point Windsurf at Anvaya's memory server and its flows arrive with packed project memory (decisions, bug threads, conventions) instead of re-deriving them per session.

Q

What about openness and lock-in?

Windsurf is closed-source and cloud-routed with subscription tiers. Anvaya defaults to local execution (nothing leaves your machine, offline capable) with open memory formats. Different answers for regulated or NDA codebases.

Run Agents That Fit On Your Laptop.

25.6 MB median RSS. 25 agents ran in parallel on a Core 2 Duo with 4 GB RAM. Hundreds on your machine. Zero cloud required on the Ollama path.

Get Started →Read the FAQ

Requires Rust/cargo to build from source. Linux and macOS today, Windows not yet supported. Pre-1.0, public beta. Pricing TBD.