FreeLLMAPI vs jurniti: Features, Pricing & Which Is Better (2026)

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

FreeLLMAPI

Tashfeen Ahmed

Freemium

Self-hostable router that aggregates free tiers from 34 LLM providers and 635 free model endpoints behind one OpenAI-compatible /v1 API.

Unified OpenAI-Compatible Endpoint: Exposes 635 free model endpoints from 34 providers behind a single /v1 API that existing OpenAI clients can use unchanged.
Smart Model Router: Selects the best available model per request and automatically falls over to another provider when one returns a rate limit.
Per-Key Quota Tracking: Monitors usage against each provider's free tier cap so requests are spread out and no individual key is exhausted.
Encrypted Key Storage: Provider API keys are stored encrypted rather than in plaintext configuration files.
Custom Endpoint Support: Any additional OpenAI-compatible chat, embedding, image or audio endpoint can be registered alongside the built-in providers.
Self-Hosting via Docker: Ships as a container image on GHCR with a Docker Compose setup, so the gateway runs entirely on your own infrastructure.
Desktop and Mobile Apps: Native builds for macOS and Windows plus an Android app on Google Play for running the router outside a server.
Signed Live Catalog: The model catalog updates itself from a signed feed, so new free models and quota changes arrive without pulling new code.

Zero-Cost Prototyping: Build and test an LLM application against free provider tiers before committing to a paid API contract.
Rate Limit Resilience: Keep a coding agent or chatbot running through provider rate limits by automatically failing over to another free endpoint.
Coding Agent Backend: Point Cursor, Claude Code or any OpenAI-compatible CLI at a single local endpoint instead of juggling provider keys per tool.
Model Comparison: Evaluate responses across hundreds of models from different labs through one consistent API surface.
Private Gateway Deployment: Self-host the router inside a network so provider keys and prompts never pass through a third-party proxy.
Multi-Provider Key Management: Consolidate scattered free-tier accounts into one encrypted store with visibility into remaining quota.

Paid

Managed 24/7 hosting for coding agents, each running in its own Firecracker microVM with your own model keys and no token markup.

Firecracker microVM Isolation: Every agent runs in its own KVM-backed virtual machine with hardware-enforced tenant isolation instead of a shared-kernel container.
Bring Your Own Key: OpenRouter, OpenAI or Anthropic keys live only inside the customer's VM — jurniti never sees them, never proxies calls and never marks up model spend.
Multi-Harness Support: Runs Claude Code, Codex CLI, OpenClaw, Hermes, OpenCode, Devin CLI, Mastra and Pi, each in its own dedicated microVM.
Fleet CLI: A jurniti command-line tool to boot agents, list fleet status, dispatch work and copy results back, so the whole fleet is managed from a terminal.
Swarm Runtime: Boots dozens of isolated microVM workers at once and dispatches the same brief to every worker, with results collected in a single command.
Flat Per-VM or Hourly Billing: A flat monthly or annual price per agent VM, or per-second metered On-Demand and Spot pricing for bursty workloads, with prepaid credits.
Automated Provisioning: Payment triggers a magic-link sign-in and an auto-provisioner that has a live microVM running in about three minutes with no human in the loop.
Custom Subdomain and Sidecars: Pro tiers add a custom subdomain, alongside separate microVM services for multi-agent communication and long-term agent memory.

Always-On Coding Agents: Keeping a Claude Code or Codex agent working on a backlog overnight without leaving a laptop running.
Secure Key Handling: Running agents for a team that cannot let model API keys leave its own infrastructure boundary.
Parallel Agent Fleets: Dispatching one brief to fifty isolated workers to compare approaches or parallelize a large refactor.
Bursty Batch Work: Using per-second Spot or On-Demand VMs for agents that only run a few hours a day, paying only for active runtime.
Self-Hosting Alternative: Replacing hand-rolled VPS setups for open-source agent harnesses like Hermes, OpenClaw or OpenCode.
Long-Running Agent Memory: Pairing an agent VM with a dedicated memory microVM so knowledge persists between sessions.