

NVIDIA A10G wins 7 of 11 benchmarks, averaging 66.5% faster.
Both cards were measured first-party on our bench, same suite, same test rig.
The gap is widest in Z-Image Turbo, where NVIDIA A10G leads by 156% (1.35 vs 3.45 images/min); the closest fight is Qwen3 4B (35% apart); VRAM decides part of this one: NVIDIA GeForce RTX 4060 Ti 16GB runs 137 of our 12 AI workloads while the other card runs 6, models that don't fit score zero.
| Benchmark | NVIDIA GeForce RTX 4060 Ti 16GB | NVIDIA A10G | Difference |
|---|---|---|---|
| Qwen3 4B tok/s | 96.29 | 129.87 | -26% |
| Llama 3.1 8B tok/s | 57.09 | 86.62 | -34% |
| Qwen2.5-Coder 14B tok/s | 31.12 | 47.07 | -34% |
| Qwen3 32B tok/s | 0 | 22.04 | n/a |
| Llama 3.3 70B tok/s | 0 | 0 | n/a |
| Stable Diffusion XL images/min | 4.58 | 6.38 | -28% |
| Z-Image Turbo images/min | 1.35 | 3.45 | -61% |
| FLUX.1 dev images/min | 0 | 0 | n/a |
| FLUX.1 Kontext dev images/min | 0 | 0 | n/a |
| Qwen-Image-Edit images/min | 0 | 0 | n/a |
| Wan 2.2 5B (720p) frames/s | 0 | 0.18 | n/a |
How long each card takes to finish a complete pipeline, not just one model. NVIDIA GeForce RTX 4060 Ti 16GB is faster on 0 of 1; NVIDIA A10G on 1.
| Workflow | NVIDIA GeForce RTX 4060 Ti 16GB | NVIDIA A10G | Difference |
|---|---|---|---|
| Full codebase review | 32.1 min | 21.3 min | NVIDIA A10G 1.51x faster |
| NVIDIA GeForce RTX 4060 Ti 16GB | NVIDIA A10G | |
|---|---|---|
| VRAM | 16GB | 24GB |
| Architecture | Ada Lovelace | Ampere |
| Memory bandwidth | 288 GB/s | 600 GB/s |
| Boost clock | 2,535 MHz | 1,710 MHz |
| TDP | 165 W | 150 W |
| Launch MSRP | $499 | $2,800 |
| Release | 2023-07-18 | 2021-11-01 |
NVIDIA GeForce RTX 4060 Ti 16GB full review · NVIDIA A10G full review · All AI & Machine Learning rankings