Hopscotch vs ZergRouter: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Hopscotch and ZergRouter — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Hopscotch

Hopscotch Labs

Paid

OpenAI-compatible LLM gateway giving one API and one balance for 500+ models, with fallbacks and spend limits per key, teammate and workspace.

Unified OpenAI-Compatible API: Call 500+ models from Anthropic, OpenAI, Google and others by changing only the base URL, API key and model name in the OpenAI SDK.
Routing Profiles and Fallbacks: Define an ordered list of backup models so requests fail over automatically when a provider errors or returns a 429.
Spend Limits: Set resetting credit limits per API key, monthly limits per teammate and workspace, and a cap on how fast the account can spend.
Activity Log and Usage Analytics: See every request with serving provider, outcome, tokens, cost and latency, export to CSV, and break spend down by model, key and teammate.
Model Catalog with Upstream Pricing: Each model lists context window and per-million-token price, including multiple upstream providers for open-weight models.
Side-by-Side Playground: Run one prompt on up to three models and compare answers and cost before changing code.
Bring Your Own Keys: Use your own provider keys free with no monthly cap alongside Hopscotch credit.

Multi-Provider Apps: Letting an application switch between Claude, GPT and Gemini without maintaining separate SDKs, accounts or bills.
Resilient Production Traffic: Automatically falling back to another model when a primary provider is rate-limited or down.
Team Budget Governance: Giving each developer or environment its own key with a spend ceiling so costs cannot run away.
Model Evaluation: Comparing output quality and cost of several models on real prompts in the playground before switching.
Cost Auditing: Exporting per-request logs to attribute LLM spend by model, provider, key and teammate.

Zerg AI

Freemium

Model router that lets you run DeepSeek in Codex and other coding tools via one endpoint, with API key budgets and Codex quota tracking.

Single Router Endpoint: One OpenAI-compatible endpoint (/v1) that connects Codex, OpenCode, Pi and other compatible apps to your chosen models.
DeepSeek in Codex: Run DeepSeek 4.1 Flash inside Codex through native Responses API forwarding.
API Key Budgets: Scoped Router keys with daily budgets and monthly usage caps to control spend.
Fallback Chains: Configure explicit fallback routes for supported chat requests.
Codex Quota Monitoring: Compare connected Codex accounts by remaining weekly quota, reset dates and banked resets, with stale data flagged.
Usage Analytics: Explore routed usage by model, date and client, including input, cached input and output tokens.
Bring Your Own Keys: Use your own provider credentials, billed directly by the provider.

Cheaper Coding Agents: Swapping Codex's default model for low-cost DeepSeek for routine coding tasks.
Team Spend Control: Issuing budgeted Router keys to developers to cap daily API costs.
Multi-Account Codex Management: Choosing which Codex subscription to use based on remaining quota and reset times.
Provider Failover: Keeping coding tools working by routing to fallback models when a provider is unavailable.
Usage Auditing: Tracking which clients and models consume tokens over time.