NVIDIA RTX 6000 Ada vs NVIDIA RTX A6000
Side-by-side local AI comparison: VRAM, memory bandwidth, model compatibility, and estimated tokens per second across 97 open-weight models.
Quick verdict
NVIDIA RTX 6000 Ada is faster for local AI inference, but only on memory bandwidth (25.0% more). Both GPUs have 48 GB VRAM and run the exact same 57 models natively — neither fits anything the other can't.
Specs comparison
| Spec | NVIDIA RTX 6000 Ada | NVIDIA RTX A6000 |
|---|---|---|
| VRAM | 48 GB | 48 GB |
| Memory type | GDDR6 | GDDR6 |
| Bandwidth | 960 GB/s(+25%) | 768 GB/s |
| Architecture | Ada Lovelace | Ampere |
| Backend | CUDA | CUDA |
| Tier | Workstation | Workstation |
| Released | 2022 | 2020 |
| Models (native) | 57 | 57 |
Estimated tokens per second
Computed from memory bandwidth and model active-parameter weight. Assumes model fits natively in VRAM.
| Model | NVIDIA RTX 6000 Ada | NVIDIA RTX A6000 | Delta |
|---|---|---|---|
| Llama 3.3 70B Instruct(70B) | 17.2 t/s(Q3_K_M) | 13.7 t/s(Q3_K_M) | +26% |
| Qwen 3.6 27B(27B) | 21.3 t/s(Q8_0) | 17.1 t/s(Q8_0) | +25% |
| Llama 3.1 8B Instruct(8B) | 36.5 t/s(BF16) | 29.2 t/s(BF16) | +25% |
| Qwen 2.5 7B Instruct(7.6B) | 39.8 t/s(BF16) | 31.9 t/s(BF16) | +25% |
Delta is NVIDIA RTX 6000 Ada relative to NVIDIA RTX A6000.
Only NVIDIA RTX 6000 Ada can run(0)
No exclusive models: NVIDIA RTX A6000 can run everything NVIDIA RTX 6000 Ada can.
Only NVIDIA RTX A6000 can run(0)
No exclusive models: NVIDIA RTX 6000 Ada can run everything NVIDIA RTX A6000 can.
Both run natively(57)
These models fit in VRAM on both GPUs. Bandwidth determines which runs them faster.
- Qwen 2.5 72B Instruct16.7 t/svs13.4 t/s
- Llama 3.3 70B Instruct17.2 t/svs13.7 t/s
- DeepSeek R1 Distill Llama 70B17.2 t/svs13.7 t/s
- Llama 3.1 70B Instruct17.2 t/svs13.7 t/s
- Mixtral 8x7B Instruct v0.117.2 t/svs13.7 t/s
- Command-R 35B15.8 t/svs12.6 t/s
- Qwen 3.5 35B-A3B (MoE)57.8 t/svs46.2 t/s
- Qwen 3.6 35B15.9 t/svs12.7 t/s
- Ornith 1.5 35B-A3B (MoE)57.8 t/svs46.2 t/s
- Yi 1.5 34B Chat16.2 t/svs12.9 t/s
- Qwen3 32B17.2 t/svs13.8 t/s
- Qwen 2.5 32B Instruct17 t/svs13.6 t/s
- Qwen 2.5 Coder 32B Instruct17 t/svs13.6 t/s
- DeepSeek R1 Distill Qwen 32B17 t/svs13.6 t/s
- Nemotron 3 Nano 30B56.4 t/svs45.1 t/s
- Gemma 4 31B18.3 t/svs14.6 t/s
- +41 more on both
Which should you choose?
- • Faster token generation is the priority
- • You want the newer architecture and longer driver support lifecycle
Frequently asked questions
- Which is better for local AI, the NVIDIA RTX 6000 Ada or NVIDIA RTX A6000?
- For local AI inference, the NVIDIA RTX 6000 Ada has the edge. It offers 48 GB VRAM (vs 48 GB) and 960 GB/s bandwidth (vs 768 GB/s), letting it run 57 models natively in VRAM vs 57 for its rival.
- How much VRAM does the NVIDIA RTX 6000 Ada have vs the NVIDIA RTX A6000?
- The NVIDIA RTX 6000 Ada has 48 GB of GDDR6 at 960 GB/s. The NVIDIA RTX A6000 has 48 GB of GDDR6 at 768 GB/s. Both GPUs have the same VRAM amount; bandwidth determines which generates tokens faster.
- Can the NVIDIA RTX 6000 Ada run Llama 3.3 70B?
- Yes. The NVIDIA RTX 6000 Ada runs Llama 3.3 70B natively at Q3_K_M quantization at approximately 17.2 tokens per second.
- Can the NVIDIA RTX A6000 run Llama 3.3 70B?
- Yes. The NVIDIA RTX A6000 runs Llama 3.3 70B natively at Q3_K_M quantization at approximately 13.7 tokens per second.
- What is the difference between the NVIDIA RTX 6000 Ada and NVIDIA RTX A6000 for AI?
- The key difference for AI inference is VRAM and memory bandwidth. The NVIDIA RTX 6000 Ada has 48 GB VRAM at 960 GB/s (CUDA backend). The NVIDIA RTX A6000 has 48 GB VRAM at 768 GB/s (CUDA backend). VRAM determines which models fit; bandwidth determines tokens per second. The NVIDIA RTX 6000 Ada runs 57 models natively vs 57 for the NVIDIA RTX A6000.