CrbonFree vs ZergRouter: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of CrbonFree and ZergRouter — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
CrbonFree
Crbon Labs Inc.
CrbonFree meters the energy and carbon of every AI token across providers, with published factors, uncertainty bands and audit-ready retirement receipts.
Key features
- Per-Token Carbon Metering: Counts every token by model and provider and converts it to energy, CO2e and water using versioned, published factors.
- Multi-Provider Coverage: Connects OpenAI, Anthropic, OpenRouter, AWS Bedrock, Google Vertex AI, Azure Foundry, Vercel and Cloudflare AI Gateways into one report.
- Many Ingestion Surfaces: Read-only provider keys, TypeScript and Python SDKs, an OAuth-secured remote MCP server, a CLI for local coding agents and a Chrome/Edge extension for ChatGPT, Gemini and Claude.
- Layered Methodology with Uncertainty: Reports model energy, data-centre overhead and embodied hardware/training carbon separately, each with a ±28.3% uncertainty band.
- Metadata-Only Privacy: Receives only model, token counts and timestamps — prompt and completion content never leaves your systems.
- Signed Retirement Receipts: Paid plans issue receipts listing credit serial numbers on the American Carbon Registry or BCarbon Registry, publicly verifiable.
- Monthly Audit Packs: Zip exports with a manifest hash plus badges and certificates to back published climate claims.
- Dashboard & REST API: One view of tokens, cost and carbon across projects with CSV/JSON export and twelve read endpoints with an OpenAPI spec.
Best for
- Scope 3 Reporting: Sustainability teams produce defensible AI emissions figures for disclosures instead of spend-based guesses.
- Engineering Carbon Visibility: Track the footprint of coding agents like Claude Code across a dev team via the CLI.
- Model Selection by Footprint: Compare energy and carbon per provider and model tier when choosing models for production workloads.
- Carbon Offsetting with Proof: Retire credits against measured AI usage and share verifiable receipts with auditors or customers.
- Board and Auditor Requests: Hand auditors monthly audit packs with verifiable hashes when asked for AI emissions data.
- Personal Chat Usage Tracking: Individuals estimate the footprint of their ChatGPT, Gemini and Claude sessions with the browser extension.
ZergRouter
Zerg AI
Model router that lets you run DeepSeek in Codex and other coding tools via one endpoint, with API key budgets and Codex quota tracking.
Key features
- 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.
Best for
- 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.