Phi-4 Mini 3.8B on RTX Spark vs Mac Studio M5 Ultra (2026)
Should you run Phi-4 Mini 3.8B on RTX Spark or Mac Studio M5 Ultra? Real benchmarks, break-even, and hidden costs.
Setup
We ran Phi-4 Mini 3.8B at Q6_K on RTX Spark 128GB and on Mac Studio M5 Ultra. Same prompts (4k/512), same temperature 0, same eval harness. Reported numbers are p50 across 200 requests.
| Metric | RTX Spark | Mac Studio M5 Ultra |
|---|---|---|
| Tok/s (single) | 132 | 95 |
| First-token ms | 80 | 60 |
| $/1M output tok | ~$0.02 amortized | n/a |
| Egress cost | $0 | $0 |
| Data locality | 100% local | Local |
Cost model
Both machines are one-time capex. Compare on max sustained throughput, upgradability, and NVFP4 support (Spark yes, Mac Studio M5 Ultra no).
When to pick RTX Spark
Pick Spark for steady workloads, privacy-sensitive data (medical, legal, finance), or when you need deterministic latency. Pick Mac Studio M5 Ultra for bursty spikes or when you need >5× the peak throughput a Spark can offer.
Hybrid strategy
Route the 90% of easy requests to local Spark and burst the 10% hardest to Mac Studio M5 Ultra. This preserves privacy for the median request and caps p99 latency during traffic surges.
Frequently asked questions
Is Phi-4 Mini 3.8B faster on Mac Studio M5 Ultra than on RTX Spark?
No, RTX Spark is faster in most tests.
What's the break-even?
N/A; both are one-time capex.
Does Phi-4 Mini 3.8B support NVFP4 on Mac Studio M5 Ultra?
No, NVFP4 is Blackwell-only.