Modular vs Cloudflare AI Gateway
Detailed side-by-side comparison to help you choose the right tool
Modular
🔴DeveloperAI Infrastructure
Unified AI inference platform from Chris Lattner's team — MAX engine, Mojo language, and a kernel-to-cloud stack.
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$0Cloudflare AI Gateway
🔴DeveloperAI Infrastructure
AI traffic control plane for routing, caching, observing, and governing model workloads. This review explains verified features, pricing evidence, operational limits, and a practical evaluation plan.
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Starting Price
FreeFeature Comparison
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Modular - Pros & Cons
Pros
- ✓Genuinely cross-vendor — same workflow on NVIDIA, AMD and Apple silicon
- ✓Compiler-level optimisation produces measurable cost-per-token wins on open models
- ✓Mojo gives Python-readable code that competes with hand-tuned CUDA C++
- ✓Built by the LLVM/Clang/Swift team — pedigree is real, not marketing
Cons
- ✗Mojo is still pre-1.0 with breaking changes between minor versions
- ✗Smaller open-source ecosystem than vLLM or NVIDIA Triton today
- ✗Distributed multi-node serving is less battle-tested than incumbents
- ✗No MCP support — not relevant if you only need raw serving, but worth noting
Cloudflare AI Gateway - Pros & Cons
Pros
- ✓Centralizes routing, logs, limits, and fallback policy across providers
- ✓Caching can reduce repeated inference cost and response latency
- ✓Rules can change from the dashboard or API without application redeployment
Cons
- ✗Gateway-specific public pricing was not available at the fetched pricing path
- ✗Adds another latency and availability dependency to every model request
- ✗Caching and prompt logs require careful tenant isolation, redaction, and retention controls
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