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 107 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 62 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) | 62 | 62 |
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) | 20.9 t/s(Q3_K_M) | 17.1 t/s(Q3_K_M) | +22% |
| Qwen 3.6 27B(27B) | 26 t/s(Q8_0) | 21.2 t/s(Q8_0) | +23% |
| Llama 3.1 8B Instruct(8B) | 45.2 t/s(BF16) | 36.8 t/s(BF16) | +23% |
| Qwen 2.5 7B Instruct(7.6B) | 49.4 t/s(BF16) | 40.2 t/s(BF16) | +23% |
Delta is NVIDIA RTX 6000 Ada relative to NVIDIA RTX A6000, compared at the highest quantization that fits natively on both cards.
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(62)
These models fit in VRAM on both GPUs. Bandwidth determines which runs them faster.
- Qwen 2.5 72B Instruct20.4 t/svs16.7 t/s
- Llama 3.3 70B Instruct20.9 t/svs17.1 t/s
- DeepSeek R1 Distill Llama 70B20.9 t/svs17.1 t/s
- Llama 3.1 70B Instruct20.9 t/svs17.1 t/s
- Mixtral 8x7B Instruct v0.160.9 t/svs50.3 t/s
- Flint 40B (MoE)147.7 t/svs134.1 t/s
- Command-R 35B20.4 t/svs16.4 t/s
- Qwen 3.5 35B-A3B (MoE)137.9 t/svs121.3 t/s
- Qwen 3.6 35B-A3B (MoE)137.9 t/svs121.3 t/s
- Ornith 1.5 35B-A3B (MoE)137.9 t/svs121.3 t/s
- Yi 1.5 34B Chat20.3 t/svs16.5 t/s
- Qwen3 32B21.4 t/svs17.4 t/s
- Qwen 2.5 32B Instruct21.2 t/svs17.2 t/s
- Qwen 2.5 Coder 32B Instruct21.2 t/svs17.2 t/s
- DeepSeek R1 Distill Qwen 32B21.2 t/svs17.2 t/s
- Nemotron 3 Nano 30B123.5 t/svs110.4 t/s
- +46 more on both
Which should you choose?
- • Faster token generation is the priority
- • You want the newer architecture and longer driver support lifecycle
- • Price or availability decides it: NVIDIA RTX A6000 has no VRAM, bandwidth or backend advantage over NVIDIA RTX 6000 Ada
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 62 models natively in VRAM vs 62 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 20.9 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 17.1 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 62 models natively vs 62 for the NVIDIA RTX A6000.