2026-07-30 • 7 min read
WebGPUPerformanceBenchmarksWebLLM
WebGPU vs Cloud APIs: Client-Side AI Latency & Performance Benchmarks
Empirical latency comparisons between browser-accelerated WebGPU execution and cloud-hosted LLM endpoints.
Written by MY AI Benchmark Team
WebGPU vs Cloud APIs: Client-Side AI Latency & Performance Benchmarks
When evaluating artificial intelligence tools, performance is traditionally measured in token generation speed (tokens/sec) and time-to-first-token (TTFT).
While cloud APIs like GPT-4 or Claude deliver massive model parameters, client-side WebGPU architectures running local models on MY AI (gomyai.uk) provide distinct performance advantages.
📊 Benchmark Latency Comparison
| Metric | Cloud API (Remote Server) | MY AI WebGPU (Local Browser) | Advantage |
|---|---|---|---|
| Network Roundtrip Latency | 150ms - 800ms | 0ms (Local RAM) | 🚀 Infinite Latency Gain |
| Cold-Start Connection Overhead | TLS Handshake + Queue | 0ms (Instant Cache) | ⚡ Instant Startup |
| Token Generation Speed | 30 - 60 tokens/sec | 25 - 55 tokens/sec (Device Dependent) | ⚖️ Comparable Speed |
| Data Transfer Cost | High (Cloud API Bills) | $0.00 (Zero Network Usage) | 💰 100% Free |
⚡ Why Local WebGPU Execution Wins
- Zero Network Latency: Cloud AI calls must compress requests, transmit across ISP routes, wait in API queues, and stream responses back. Local browser models read model weights directly from unified GPU memory.
- Offline Resilience: Mobile workers, flight passengers, and secure enterprise staff can continue generating content without cell tower or Wi-Fi connections.
- Infinite Scalability: Adding 1,000,000 concurrent users to
gomyai.ukimposes zero additional server load or cloud API costs.