RTX 6000 Ada
Flagship Ada professional GPU. 48GB GDDR6 with NVLink — two cards give 96GB unified. Excellent for 70B+ model inference.
RTX 6000 Ada Overview
The RTX 6000 Ada is NVIDIA’s flagship Ada Lovelace professional card, combining 48GB of ECC GDDR6 with 182.2 TFLOPS of FP16/BF16 tensor performance in a 300W workstation-friendly design. It offers a professional reliability and driver profile that consumer AD102 cards do not.
Its 960 GB/s memory bandwidth is healthy for GDDR6 and the 48GB capacity accommodates substantially larger workloads than 24GB cards. NVLink provides a path for paired-card configurations, but bandwidth remains well below HBM data-center platforms, so multi-GPU language-model workloads should be assessed for communication overhead rather than assumed to scale linearly.
This GPU is a strong fit for high-VRAM fine-tuning, professional visualization plus AI, and workstation-scale LLM inference. It is less attractive than HBM hardware for bandwidth-bound large-model serving and lacks the dedicated FP8 positioning of Hopper data-center products.
Memory
Compute Performance
Hardware
Relative Performance
Relative to highest-spec GPU in database
Limitations
Live Cloud PricingOn-demand hourly rates
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Use Case Guidance
LLM Model Size Guidance
Estimates only. Actual capacity depends on context length, KV cache, and framework overhead.
Related Guides
LLM APIs Running on This GPU Class
Providers that serve frontier LLM inference on Ada Lovelace-class hardware.
Related GPUs
Frequently Asked Questions
How much VRAM does the RTX 6000 Ada have?
The RTX 6000 Ada has 48GB of GDDR6 memory with 960 GB/s bandwidth. This enables running models up to approximately 96B parameters at INT4 precision, 48B at INT8, or 24B at FP16.
What is the FP16 performance of the RTX 6000 Ada?
The RTX 6000 Ada delivers 182.2 TFLOPS of FP16 performance and 182.2 TFLOPS BF16. INT8 throughput is 364 TOPS. For transformer inference, memory bandwidth (960 GB/s) is often the binding constraint rather than raw TFLOPS.
What is the RTX 6000 Ada best used for?
The RTX 6000 Ada is best suited for: Large model inference, Multi-GPU professional workloads, High-VRAM fine-tuning. Flagship Ada professional GPU. 48GB GDDR6 with NVLink — two cards give 96GB unified. Excellent for 70B+ model inference.
What interconnect does the RTX 6000 Ada use?
The RTX 6000 Ada uses NVLink 4.0 / PCIe 4.0 with 112 GB/s NVLink bandwidth for multi-GPU configurations. NVLink enables near-linear tensor-parallel scaling across multiple cards for models that exceed single-card VRAM.
What LLM model sizes can the RTX 6000 Ada run?
With 48GB of GDDR6, the RTX 6000 Ada can run models up to approximately 24B parameters at FP16 (2 bytes/param), 48B at INT8 (1 byte/param), or 96B at INT4/GGUF (0.5 bytes/param). These are estimates — actual capacity depends on context length, KV cache size, and framework overhead. Longer context windows require more KV cache memory, reducing the effective model size that fits.
How does the RTX 6000 Ada compare to the A100 for LLM inference?
The RTX 6000 Ada has 182.2 TFLOPS FP16 vs the A100 80GB's 312 TFLOPS, and 960 GB/s memory bandwidth vs the A100's 2,039 GB/s. For memory-bound autoregressive LLM inference, bandwidth is the primary determinant of tokens-per-second. The A100's higher bandwidth gives it a throughput advantage for large model inference, despite the RTX 6000 Ada's lower cost.
What is the power consumption of the RTX 6000 Ada?
The RTX 6000 Ada has a TDP (Thermal Design Power) of 300W. This is the maximum sustained power draw under full load. For data center deployments, total rack power consumption is typically 1.2–1.5× the GPU TDP when accounting for CPU, memory, networking, and cooling overhead. At 300W, the RTX 6000 Ada is in the mid-range tier — compatible with standard data center power infrastructure.
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