⚡ TTFT • TPS Streaming • Cerebras vs Groq vs Anthropic • Voice & Chat SLA
LLM Latency & Throughput Benchmark Estimator
Estimate Time To First Token (TTFT), continuous streaming throughput (TPS), and end-to-end turnaround latency to ensure real-time AI agents and voice pipelines meet your SLA.
⚙️ Workload Parameters
Input Prompt Tokens 1,500
100 (Single query) 8,000 (RAG context) 32,000 (Codebase AST)
Expected Output Tokens 800
50 (Short classification) 800 (Detailed response) 4,000 (Long document)
Estimated Latency Breakdown
Anthropic Claude 3.5 Sonnet
🟢 Interactive Voice Ready (<800ms)
Time to First Token (TTFT)
245 ms
Prompt prefill + RTT
Streaming Throughput
75 tok/s
Generation speed
Total Turnaround
10.9 s
Full completion time
Streaming Timeline Distribution Human reading speed: ~5 tok/s
Network RTT TTFT Prefill Token Generation
Live Architecture Benchmark Matrix
| Engine | Hardware | TTFT (1.5k ctx) | TPS Output | Best Use Case |
|---|---|---|---|---|
| Cerebras CS-3 | Wafer-Scale Engine | 110 ms | 2,100 tok/s | Real-time voice bots & bulk RAG re-ranking |
| Groq LPU | SRAM Tensor Core | 140 ms | 320 tok/s | Ultra-fast conversational agents |
| Claude 3.5 Sonnet | AWS Trainium2 / H100 | 245 ms | 75 tok/s | Complex coding & multi-file agents |
| DeepSeek-R1 (Official) | Cluster H800 / MoE | 1,850 ms | 28 tok/s | Deep mathematical & architectural reasoning |