Compare tools
Pick 2–5 published tools. Values come from our evidence-checked profiles — an em-dash means unknown, never “no”. Ranking rows reflect the current published methodology for the comparison context.
Cloudflare AI Gateway vs LiteLLM
Context: LLM Gateways & Model Routing Platforms · 25 rows
| Attribute | Cloudflare AI GatewayCloudflare | LiteLLMBerriAI |
|---|---|---|
| Identity · Taxonomy | ||
| Documentation | https://developers.cloudflare.com/ai-gateway/ | https://docs.litellm.ai/docs/ |
| Tags | llm-gateway, proxy, caching, rate-limiting, analytics | llm-gateway, proxy, open-source, routing |
| Platform · Deployment | ||
| Delivery model | SaaS | self-hosted |
| Pricing · Licensing | ||
| Free plan | true | true |
| Free trial | — | true |
| License model | — | open-source |
| Pricing model | free, subscription, usage | free, custom |
| Source repository | — | https://github.com/BerriAI/litellm |
| SPDX license IDs | — | MIT |
| Trial length | — | 30 |
| Features · Product · Fit | ||
| Core capabilities | Provider proxying for AI applications, Response caching, Rate limiting, Request retry and model fallback, Analytics for requests, tokens, and cost, Logging of requests and errors | Unified OpenAI-compatible API to 140+ LLM providers, Virtual keys with per-key, team, and org budgets, Auto routing, load balancing, and caching, Guardrails including PII masking and prompt injection protection, Usage analytics, spend tracking, and chargeback, Unified access for LLMs, agents, and MCP servers |
| Api · Integrations · Ecosystem | ||
| API available | true | true |
| CLI | — | true |
| Enterprise SSO | — | OIDC |
| Support · Docs · Services | ||
| Support channels | — | community, enterprise support |
| Audience · Use · Case | ||
| Best for | Teams that want AI gateway controls such as caching, rate limits, analytics, and fallbacks across model providers, especially those already using Cloudflare. | Platform and engineering teams that want to self-host one OpenAI-compatible gateway in front of many LLM providers, with budgets, routing, and guardrails. |
| Company-size fit | individual, SMB, mid-market, enterprise | mid-market, enterprise |
| Primary use cases | Cost tracking for LLM usage, Rate limiting AI traffic, Caching model responses, Provider failover | Central LLM gateway for AI applications, Spend tracking and chargeback across teams, Model routing and load balancing |
| Skill level | intermediate | advanced |
| Lifecycle · Versioning | ||
| Changelog/release notes | — | https://docs.litellm.ai/release_notes |
| Current version | — | v1.100.0 |
| Maintenance status | active | active |
| Vendor · Maintainer | ||
| Founded year | 2009 | — |
| Headquarters country | United States | — |
| Vendor type | commercial | commercial |
“—” means unknown (we never treat missing evidence as a negative). Cells reflect each value's current evidence state; superseded or stale values are excluded. Ranking rows are editorial assessments under the cited methodology version — see the LLM Gateways & Model Routing Platforms category for definitions.