48GB
VRAM
GDDR6 memory
AIVory · GPU Marketplace
Live spot pricingNVIDIA RTX 6000 Ada — professional-grade 48 GB with ECC and display.
The top of NVIDIA's professional Ada lineup. 48 GB of ECC-protected GDDR6 with 960 GB/s bandwidth, full Ada Lovelace tensor cores, and certified drivers for enterprise workstations. At $0.74/hr on spot, the RTX 6000 Ada combines workstation reliability with inference performance that rivals the L40S — plus display output and graphics capabilities the data center cards lack.
At a glance
RTX 6000 Ada specifications.
Key hardware specs that determine what workloads this GPU handles.
960 GB/s
Memory Bandwidth
peak throughput
300W
TDP
thermal design power
Ada Lovelace
Architecture
NVIDIA GPU architecture
Spot pricing
RTX 6000 Ada: live hourly rates.
Every provider offering this GPU on the spot market, sorted cheapest first.
Prices in USD per GPU-hour · spot instances · sorted cheapest first
Recommended models
AI models that run well on RTX 6000 Ada.
Tested model-GPU pairings with notes on why each is a good fit.
Qwen 2.5 72B
72B parameters in INT4 (GPTQ/AWQ) need ~36 GB, fitting on the RTX 6000 Ada with 12 GB for KV cache. ECC memory ensures output correctness under sustained load.
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Gemma 4 31B
31B parameters in FP16 need ~62 GB — run in INT8 at ~31 GB with 17 GB headroom. The 960 GB/s bandwidth outpaces every other 48 GB card for token generation.
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Mistral Small 24B
Fits in full FP16 on the RTX 6000 Ada with 24 GB free for batched serving. The Ada tensor cores deliver the highest throughput of any professional-class GPU at this VRAM tier.
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Use cases
What the RTX 6000 Ada is built for.
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Enterprise inference with certified driver stability
The RTX 6000 Ada runs on NVIDIA's ISV-certified professional drivers, which are validated against enterprise applications and carry longer support lifecycles than consumer GeForce drivers. For regulated industries that require driver certification (healthcare, defense, financial), the RTX 6000 Ada is the only 48 GB Ada card that qualifies.
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Combined AI inference and 3D visualization pipelines
Product design teams running neural rendering, AI-assisted CAD, or real-time simulation with ML inference benefit from a single GPU that handles both workloads. The RTX 6000 Ada's display output, ray tracing cores, and tensor cores operate simultaneously — unlike data center cards like the L40S that lack display connectivity.
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Highest-bandwidth 48 GB inference for latency-sensitive serving
At 960 GB/s, the RTX 6000 Ada has the fastest memory bandwidth of any 48 GB GPU — 11% faster than the L40/L40S (864 GB/s) and 38% faster than the A6000 (768 GB/s). For workloads where per-token latency matters more than cost-per-token, the RTX 6000 Ada generates tokens faster than any alternative at this VRAM tier.
FAQ
Common questions.
RTX 6000 Ada vs L40S — which 48 GB Ada card should I use?
They share the Ada Lovelace architecture and 48 GB VRAM. The RTX 6000 Ada has higher bandwidth (960 vs 864 GB/s), ECC memory, and display output. The L40S has hardware-optimized transformer scheduling and costs less ($0.57 vs $0.74/hr). For pure LLM inference throughput, the L40S's transformer engine optimizations give it an edge despite lower bandwidth. For mixed workloads, ECC, or when you need display output, the RTX 6000 Ada wins.
Is the RTX 6000 Ada the successor to the A6000?
Yes. The RTX 6000 Ada replaces the RTX A6000 in NVIDIA's professional lineup. Key upgrades: Ada Lovelace vs Ampere architecture (~50% higher tensor throughput), 960 vs 768 GB/s bandwidth, and FP8 support. The A6000 is cheaper ($0.33/hr), but the RTX 6000 Ada delivers significantly more performance per GPU-hour.
Does the ECC memory reduce available VRAM?
No. The RTX 6000 Ada's 48 GB specification is the usable capacity after ECC overhead. NVIDIA uses inline ECC that's transparent to the user — you get the full 48 GB of usable VRAM. ECC adds a small latency overhead (~2-3%) for error checking, but this is negligible for inference workloads.
Can I use the RTX 6000 Ada for training?
Yes, and better than most 48 GB GPUs. The 960 GB/s bandwidth helps with gradient communication, and ECC prevents training instabilities from bit errors. Fine-tuning 30B models in BF16 fits within the 48 GB envelope. Full pre-training should still target A100/H100 for HBM bandwidth, but the RTX 6000 Ada is a strong fine-tuning card.
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