RTX 4060 Ti vs RTX 2000 Ada for local AI
Both fit the same models we track, up to gpt-oss 20B. The RTX 4060 Ti generates about 29% faster on any model both can run, because it has 288 GB/s of memory bandwidth to the RTX 2000 Ada's 224 GB/s.
Memory and bandwidth
Memory decides which models fit. Bandwidth decides how fast they generate, because every token reads the model's active weights once.
| RTX 4060 Ti | RTX 2000 Ada | |
|---|---|---|
| Memory | 8 or 16 GB VRAM | 16 GB VRAM |
| Bandwidth | 288 GB/s | 224 GB/s |
| Biggest model that fits | gpt-oss 20B | gpt-oss 20B |
| Best everyday pick | gpt-oss 20B, ~50 tok/s | gpt-oss 20B, ~39 tok/s |
Every model, side by side
Estimated generation speed at the largest memory size each was sold in (16 GB and 16 GB).
| Model | RTX 4060 Ti | RTX 2000 Ada |
|---|---|---|
| Qwen3 4B About 4 GB | ~63 tok/s Runs great | ~49 tok/s Runs great |
| Qwen3 8B About 7 GB | ~30 tok/s Runs great | ~24 tok/s Usable |
| Gemma 3 12B About 10 GB | ~20 tok/s Usable | ~15 tok/s Usable |
| Qwen3 14B About 11 GB | ~17 tok/s Usable | ~13 tok/s Usable |
| gpt-oss 20B About 16 GB | ~50 tok/s Runs great | ~39 tok/s Runs great |
| Gemma 3 27B About 19 GB | Needs 19 GB | Needs 19 GB |
| Qwen3 30B-A3B About 21 GB | Needs 21 GB | Needs 21 GB |
| Qwen3 32B About 22 GB | Needs 22 GB | Needs 22 GB |
| Llama 3.3 70B About 45 GB | Needs 45 GB | Needs 45 GB |
| gpt-oss 120B About 67 GB | Needs 67 GB | Needs 67 GB |
| Qwen3 235B-A22B About 144 GB | Needs 144 GB | Needs 144 GB |
| DeepSeek R1 671B About 406 GB | Needs 406 GB | Needs 406 GB |
The RTX 4060 Ti, for speed. They fit the same models. Price matters as much as either number: check used prices on the builds page, where every parts list has a measured or estimated speed.
Both columns use the same formula: memory bandwidth divided by the weights read per token, calibrated on our own rack, with Ollama's default 4-bit sizes. Real results are usually within about a third. Measured either one? Send us the number.