NVIDIA RTX 4060 Ti 16GB vs NVIDIA RTX 3090
Side-by-side local AI comparison — VRAM, memory bandwidth, model compatibility, and estimated tokens per second across 70 open-weight models.
Quick verdict
NVIDIA RTX 3090 wins for local AI inference. It has 8 GB more VRAM and 225% more memory bandwidth, runs 42 models natively (vs 41), and exclusively fits 1 models the other cannot.
Specs comparison
| Spec | NVIDIA RTX 4060 Ti 16GB | NVIDIA RTX 3090 |
|---|---|---|
| VRAM | 16 GB | 24 GB |
| Memory type | GDDR6 | GDDR6X |
| Bandwidth | 288 GB/s | 936 GB/s(+225%) |
| Architecture | Ada Lovelace | Ampere |
| Backend | CUDA | CUDA |
| Tier | Consumer | Consumer |
| Released | 2023 | 2020 |
| Models (native) | 41 | 42 |
Estimated tokens per second
Computed from memory bandwidth and model active-parameter weight. Assumes model fits natively in VRAM.
| Model | NVIDIA RTX 4060 Ti 16GB | NVIDIA RTX 3090 | Delta |
|---|---|---|---|
| Llama 3.3 70B Instruct(70B) | — | — | — |
| Qwen 3.6 27B(27B) | 26.7 t/s(Q3_K_M) | 55.5 t/s(Q5_K_M) | -52% |
| Llama 3.1 8B Instruct(8B) | 36 t/s(Q8) | 58.5 t/s(FP16) | -38% |
| Qwen 2.5 7B Instruct(7.6B) | 37.9 t/s(Q8) | 61.6 t/s(FP16) | -38% |
Delta is NVIDIA RTX 4060 Ti 16GB relative to NVIDIA RTX 3090.
Only NVIDIA RTX 4060 Ti 16GB can run(0)
No exclusive models — NVIDIA RTX 3090 can run everything NVIDIA RTX 4060 Ti 16GB can.
Only NVIDIA RTX 3090 can run(1)
Both run natively(41)
These models fit in VRAM on both GPUs. Bandwidth determines which runs them faster.
- Qwen 3.5 35B-A3B (MoE)352 t/svs686.4 t/s
- Qwen 3.6 35B27.4 t/svs53.5 t/s
- Yi 1.5 34B Chat27.9 t/svs54.4 t/s
- Qwen3 32B29.3 t/svs57.1 t/s
- Qwen 2.5 32B Instruct29.5 t/svs57.6 t/s
- Qwen 2.5 Coder 32B Instruct29.5 t/svs57.6 t/s
- DeepSeek R1 Distill Qwen 32B29.5 t/svs57.6 t/s
- Nemotron 3 Nano 30B264 t/svs686.4 t/s
- Gemma 4 31B31 t/svs60.4 t/s
- Qwen3 30B-A3B (MoE)264 t/svs549.1 t/s
- Gemma 2 27B Instruct35.3 t/svs55.1 t/s
- Gemma 3 27B Instruct26.7 t/svs55.5 t/s
- Qwen 3.6 27B26.7 t/svs55.5 t/s
- Gemma 4 26B (MoE)208.4 t/svs433.5 t/s
- Mistral Small 3.1 24B Instruct24 t/svs52 t/s
- Mistral Small 22B25.9 t/svs56.2 t/s
- +25 more on both
Which should you choose?
Choose NVIDIA RTX 4060 Ti 16GB if:
- • You want the newer architecture and longer driver support lifecycle
Choose NVIDIA RTX 3090 if:
- • You need to run larger models (>16 GB VRAM)
- • Faster token generation is the priority
Frequently asked questions
- Which is better for local AI, the NVIDIA RTX 4060 Ti 16GB or NVIDIA RTX 3090?
- For local AI inference, the NVIDIA RTX 3090 has the edge. It offers 24 GB VRAM (vs 16 GB) and 936 GB/s bandwidth (vs 288 GB/s), letting it run 42 models natively in VRAM vs 41 for its rival.
- How much VRAM does the NVIDIA RTX 4060 Ti 16GB have vs the NVIDIA RTX 3090?
- The NVIDIA RTX 4060 Ti 16GB has 16 GB of GDDR6 at 288 GB/s. The NVIDIA RTX 3090 has 24 GB of GDDR6X at 936 GB/s. The NVIDIA RTX 3090 has 8 GB more VRAM, allowing it to run 1 models the NVIDIA RTX 4060 Ti 16GB cannot fit natively.
- Can the NVIDIA RTX 4060 Ti 16GB run Llama 3.3 70B?
- The NVIDIA RTX 4060 Ti 16GB can run Llama 3.3 70B with CPU offload at Q3_K_M, but at reduced speed.
- Can the NVIDIA RTX 3090 run Llama 3.3 70B?
- The NVIDIA RTX 3090 can run Llama 3.3 70B with CPU offload at Q4_K_M, but at reduced speed.
- What is the difference between the NVIDIA RTX 4060 Ti 16GB and NVIDIA RTX 3090 for AI?
- The key difference for AI inference is VRAM and memory bandwidth. The NVIDIA RTX 4060 Ti 16GB has 16 GB VRAM at 288 GB/s (CUDA backend). The NVIDIA RTX 3090 has 24 GB VRAM at 936 GB/s (CUDA backend). VRAM determines which models fit; bandwidth determines tokens per second. The NVIDIA RTX 4060 Ti 16GB runs 41 models natively vs 42 for the NVIDIA RTX 3090.