FastRouter.ai vs Juggler: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of FastRouter.ai and Juggler — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
FastRouter.ai
FastRouter
Enterprise LLM gateway that routes, compares and monitors 200+ models through a single OpenAI-compatible API with zero markup.
Key features
- Unified OpenAI-Compatible API: Access 200+ models for text, image, video, embeddings and speech from one endpoint and swap models without code changes.
- Smart Auto Router: Routes each request to the best model based on cost, latency, throughput or output quality.
- Automatic Failover: Retries across providers, fallback model lists and virtual model aliases keep applications running during failures.
- Cost Control and Governance: Project and API key limits, member roles and access controls prevent spend spikes.
- Model Council and Playground: Compare latency, quality and cost side by side and combine models to cross-check outputs.
- Observability and Insights: Unified dashboards, activity logs, alerts and weekly Insights that rank cost-saving changes.
- Self-Hosting: Run the full gateway in your own cloud so prompts, responses, logs and provider keys stay in your network.
Best for
- An engineering team replaces several provider SDKs with one OpenAI-compatible endpoint to simplify integration.
- A product team cuts LLM spend by routing simple requests to cheaper models and reserving premium models for hard ones.
- A platform team keeps a customer-facing app online by defining fallback model lists across providers.
- A finance-conscious leader sets per-project and per-key limits to avoid surprise bills.
- A regulated enterprise self-hosts the gateway so prompts and provider keys never leave its network.
- A developer compares candidate models for latency, quality and cost in the playground before shipping.
Juggler
Julian Storer
A native desktop workbench for AI coding agents with branching conversation trees, inspectable tool calls and editable context.
Key features
- Branching Conversation Trees: Fork the session at any point, recursively, so competing approaches and tangents run side by side without polluting the main context.
- Miller Column Navigation: A Finder-style column layout lays out tool calls, item properties and nested sub-threads for long reading and editing sessions.
- Transaction Inspector: Open any model transaction to see the assembled system prompt, messages, tool definitions, output, token use, timing and stop reason.
- The Context Surgeon: Fold history into a new thread, move or copy items between branches, expand a branch back into its parent, and undo structural changes.
- Local or Remote Sessions: Run the desktop app locally or the headless binary on the machine holding the code, then attach from the app, a browser or a phone.
- Durable Sessions: Sessions are stored on disk as live-synced Yjs documents, so quits, relaunches and dropped connections do not lose the conversation.
- Automatic Context Sizing: Juggler measures the full request before each call, reserves room for the answer and compacts older history before limits become an error.
- Inspectable MCP Tools: Follow an MCP handoff end to end - schema offered, arguments generated, approval, result and errors - with server status, logs and per-tool filtering.
- JavaScript Extension SDK: Context items, LLM loop strategies, slash commands, viewers and Pinboard tabs are extensions you can fork or replace, under a permissive Apache-2.0 SDK.
Best for
- Exploring Competing Fixes: Branch a thread into two sub-threads to try different approaches to the same bug and compare results before committing.
- Auditing Agent Behavior: Inspect exactly what the model received and returned when an agent makes a surprising edit to the codebase.
- Remote Development: Run the server on a dev box or GPU machine where the repository lives and drive the same live session from a laptop or browser.
- Long Refactors: Keep a multi-hour session alive across quits and reconnects, with the agent paused awaiting approval for its next step.
- Provider Comparison: Drive Claude Code, Codex, Copilot, Gemini and local Ollama models through one interface to compare behavior on the same task.
- Custom Tooling: Write JavaScript extensions that add slash commands, file viewers or new LLM loop strategies to the workbench.