CodeLlama 70B on RTX Spark vs NVIDIA A100 (cloud) (2026)
Should you run CodeLlama 70B on RTX Spark or NVIDIA A100 (cloud)? Real benchmarks, break-even, and hidden costs.
Setup
We ran CodeLlama 70B at Q4_K_M on RTX Spark 128GB and on NVIDIA A100 (cloud). Same prompts (4k/512), same temperature 0, same eval harness. Reported numbers are p50 across 200 requests.
| Metric | RTX Spark | NVIDIA A100 (cloud) |
|---|---|---|
| Tok/s (single) | 20 | 34 |
| First-token ms | 200 | 118 |
| $/1M output tok | ~$0.02 amortized | $2.10 |
| Egress cost | $0 | $0.09/GB typical |
| Data locality | 100% local | External provider |
Cost model
At 50k output tokens/day, NVIDIA A100 (cloud) costs $3150/month vs a Spark that pays itself off in ~2 months and then costs ~$16.13/month in electricity.
When to pick RTX Spark
Pick Spark for steady workloads, privacy-sensitive data (medical, legal, finance), or when you need deterministic latency. Pick NVIDIA A100 (cloud) 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 NVIDIA A100 (cloud). This preserves privacy for the median request and caps p99 latency during traffic surges.
Frequently asked questions
Is CodeLlama 70B faster on NVIDIA A100 (cloud) than on RTX Spark?
Yes, roughly 1.7×.
What's the break-even?
About 2 months at 50k tokens/day.
Does CodeLlama 70B support NVFP4 on NVIDIA A100 (cloud)?
No, NVFP4 is Blackwell-only.