You would expect the 8B parameter model to crush the 3.8B model on API throughput. And it does — but maybe not by as much as you would think. LLaMA 3 8B manages 36.2 requests per second versus Phi-3 Mini‘s 21.0. That is a significant lead, but Phi-3 is no slouch. The interesting story is what Phi-3 offers in return: half the VRAM and notably higher response quality.
API Load Test
RTX 3090, vLLM, INT4, continuous batching, 1-50 concurrent connections. Live benchmark data.
| Model (INT4) | Requests/sec | p50 Latency (ms) | p99 Latency (ms) | VRAM Used |
|---|---|---|---|---|
| LLaMA 3 8B | 36.2 | 70 | 339 | 6.5 GB |
| Phi-3 Mini | 21.0 | 92 | 404 | 3.2 GB |
LLaMA wins on every latency and throughput metric. Its p50 of 70 ms and p99 of 339 ms are both better than Phi-3’s 92 ms and 404 ms. The throughput gap (72% more requests per second) is substantial for high-traffic APIs.
But consider this: Phi-3’s p99 of 404 ms is still well under most real-world SLA requirements (typically 500 ms-1s). For APIs with moderate traffic, Phi-3 delivers perfectly acceptable latency while scoring higher on output quality benchmarks.
Architecture and Specs
| Specification | LLaMA 3 8B | Phi-3 Mini |
|---|---|---|
| Parameters | 8B | 3.8B |
| Architecture | Dense Transformer | Dense Transformer |
| Context Length | 8K | 128K |
| VRAM (FP16) | 16 GB | 7.6 GB |
| VRAM (INT4) | 6.5 GB | 3.2 GB |
| Licence | Meta Community | MIT |
Phi-3’s 128K context window does allocate more KV cache per request, which partly explains the throughput gap despite the smaller model size. For short-prompt API calls, you could restrict the max context length in vLLM to reclaim that headroom. See the LLaMA VRAM guide and Phi-3 VRAM guide.
Cost at Scale
| Cost Factor | LLaMA 3 8B | Phi-3 Mini |
|---|---|---|
| GPU Required (INT4) | RTX 3090 (24 GB) | RTX 3090 (24 GB) |
| VRAM Used | 6.5 GB | 3.2 GB |
| Est. Monthly Server Cost | £151 | £142 |
| Throughput Advantage | 3% faster | 3% cheaper/tok |
LLaMA’s throughput advantage makes it cheaper per request at high volume. Phi-3 could offset this by running on a cheaper GPU card. Calculate your breakeven at the cost calculator. More at the comparisons hub.
The Trade-Off
LLaMA 3 8B for volume. If your API handles hundreds of requests per second and throughput is the binding constraint, LLaMA delivers 72% more capacity per GPU. That directly reduces your hardware bill at scale. Hardware guidance at best GPU for inference.
Phi-3 Mini for quality at moderate traffic. If your API serves fewer than 20 requests per second and response quality matters more than peak throughput — think premium-tier endpoints, internal tools, or quality-gated production APIs — Phi-3’s superior output justifies the lower throughput. MIT licensing also simplifies commercial deployment. Setup at the self-host guide.
See also: LLaMA 3 vs Phi-3 for Chatbots | LLaMA 3 vs DeepSeek for API Serving
Serve Your Model
Run LLaMA 3 8B or Phi-3 Mini on dedicated GPU servers. No rate limits, full root access.
Browse GPU Servers
