NVIDIA RTX 4090 vs NVIDIA RTX 4060 Ti 16GB
Side-by-side local AI comparison: VRAM, memory bandwidth, model compatibility, and estimated tokens per second across 107 open-weight models.
Quick verdict
NVIDIA RTX 4090 wins for local AI inference. It has 8 GB more VRAM and 250.0% more memory bandwidth, runs 57 models natively (vs 48), and exclusively fits 9 models the other cannot.
Specs comparison
| Spec | NVIDIA RTX 4090 | NVIDIA RTX 4060 Ti 16GB |
|---|---|---|
| VRAM | 24 GB | 16 GB |
| Memory type | GDDR6X | GDDR6 |
| Bandwidth | 1008 GB/s(+250%) | 288 GB/s |
| Architecture | Ada Lovelace | Ada Lovelace |
| Backend | CUDA | CUDA |
| Tier | Consumer | Consumer |
| Released | 2022 | 2023 |
| Models (native) | 57 | 48 |
Estimated tokens per second
Computed from memory bandwidth and model active-parameter weight. Assumes model fits natively in VRAM.
| Model | NVIDIA RTX 4090 | NVIDIA RTX 4060 Ti 16GB | Delta |
|---|---|---|---|
| Llama 3.3 70B Instruct(70B) | N/A | N/A | N/A |
| Qwen 3.6 27B(27B) | 38.3 t/s(Q5_K_M) | 17.5 t/s(Q3_K_M) | +199%at Q3_K_M |
| Llama 3.1 8B Instruct(8B) | 47.2 t/s(BF16) | 25.2 t/s(Q8_0) | +212%at Q8_0 |
| Qwen 2.5 7B Instruct(7.6B) | 51.7 t/s(BF16) | 28.2 t/s(Q8_0) | +213%at Q8_0 |
Delta is NVIDIA RTX 4090 relative to NVIDIA RTX 4060 Ti 16GB, compared at the highest quantization that fits natively on both cards.
Only NVIDIA RTX 4090 can run(9)
Only NVIDIA RTX 4060 Ti 16GB can run(0)
No exclusive models: NVIDIA RTX 4090 can run everything NVIDIA RTX 4060 Ti 16GB can.
Both run natively(48)
These models fit in VRAM on both GPUs. Bandwidth determines which runs them faster.
- Qwen 3.5 35B-A3B (MoE)196.2 t/svs118.3 t/s
- Qwen 3.6 35B-A3B (MoE)196.2 t/svs118.3 t/s
- Ornith 1.5 35B-A3B (MoE)196.2 t/svs118.3 t/s
- Gemma 4 31B37.9 t/svs18 t/s
- Qwen3 30B-A3B (MoE)144.9 t/svs86 t/s
- Muse Glimmer 30B39 t/svs17.7 t/s
- Gemma 2 27B Instruct40.1 t/svs17.9 t/s
- Gemma 3 27B Instruct43.4 t/svs20.2 t/s
- Qwen 3.6 27B38.3 t/svs17.5 t/s
- UI-Mate 27B38.3 t/svs17.5 t/s
- Bonsai 27B79.6 t/svs29.1 t/s
- Bonsai 2 27B90.1 t/svs34.2 t/s
- Qwen 3.8 27B38.3 t/svs17.5 t/s
- Gemma 4 26B (MoE)168.5 t/svs89.6 t/s
- Mistral Small 3.1 24B Instruct43.1 t/svs18.8 t/s
- Mistral Small 22B38.4 t/svs18.9 t/s
- +32 more on both
Which should you choose?
Choose NVIDIA RTX 4090 if:
- • You need to run larger models (>16 GB VRAM)
- • Faster token generation is the priority
Choose NVIDIA RTX 4060 Ti 16GB if:
- • You want the newer architecture and longer driver support lifecycle
Frequently asked questions
- Which is better for local AI, the NVIDIA RTX 4090 or NVIDIA RTX 4060 Ti 16GB?
- For local AI inference, the NVIDIA RTX 4090 has the edge. It offers 24 GB VRAM (vs 16 GB) and 1008 GB/s bandwidth (vs 288 GB/s), letting it run 57 models natively in VRAM vs 48 for its rival.
- How much VRAM does the NVIDIA RTX 4090 have vs the NVIDIA RTX 4060 Ti 16GB?
- The NVIDIA RTX 4090 has 24 GB of GDDR6X at 1008 GB/s. The NVIDIA RTX 4060 Ti 16GB has 16 GB of GDDR6 at 288 GB/s. The NVIDIA RTX 4090 has 8 GB more VRAM, allowing it to run 9 models the NVIDIA RTX 4060 Ti 16GB cannot fit natively.
- Can the NVIDIA RTX 4090 run Llama 3.3 70B?
- The NVIDIA RTX 4090 can run Llama 3.3 70B with CPU offload at Q3_K_M, but at reduced speed.
- 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.
- What is the difference between the NVIDIA RTX 4090 and NVIDIA RTX 4060 Ti 16GB for AI?
- The key difference for AI inference is VRAM and memory bandwidth. The NVIDIA RTX 4090 has 24 GB VRAM at 1008 GB/s (CUDA backend). The NVIDIA RTX 4060 Ti 16GB has 16 GB VRAM at 288 GB/s (CUDA backend). VRAM determines which models fit; bandwidth determines tokens per second. The NVIDIA RTX 4090 runs 57 models natively vs 48 for the NVIDIA RTX 4060 Ti 16GB.