Benchmark data from real deployments — then test a live model yourself. The chat below runs Llama 3.3 70B via Groq. Same model family we deploy locally, so you know what you're getting.
All benchmarks measured on production hardware with llama.cpp / Ollama, 2048 token context, greedy sampling. Numbers are generation throughput — tokens per second after the first token lands.
* Cloud API throughput varies with provider load, geographic region, and tier. More critically — TTFT for cloud APIs averages 600–1200ms due to network round-trip. Local TTFT is 60–120ms regardless of load. Numbers sourced from community benchmarks; your results may vary.
Throughput (tok/s) is only half the story. Time To First Token (TTFT) determines how responsive your application feels — and this is where local wins most dramatically.
| TTFT (avg) | THROUGHPUT | RATE LIMITS | CONSISTENCY | DATA LEAVES NETWORK | |
|---|---|---|---|---|---|
| Local · RTX 4090 | 84ms | 47 tok/s | NONE | DETERMINISTIC | NEVER |
| Local · RTX 3090 | 110ms | 38 tok/s | NONE | DETERMINISTIC | NEVER |
| GPT-4o API | ~800ms | ~30 tok/s | TPM / RPM CAPS | VARIABLE | ALWAYS |
| Claude Sonnet API | ~700ms | ~35 tok/s | TPM / RPM CAPS | VARIABLE | ALWAYS |
This is Llama 3.3 70B — the same open-weight model we deploy on local hardware. Running here via Groq's LPU infrastructure so you can test it without needing your own GPU. Ask it anything about local AI deployment.
You've seen the numbers and tested the model. We'll get Llama 3.3 70B — or whatever fits your use case — running on your own infrastructure. No more API bills.