16GB
VRAM
GDDR6 memory
AIVory · GPU Marketplace
Live spot pricingNVIDIA RTX 2000 Ada — Ada tensor cores in a 70-watt whisper.
The entry-level Ada Lovelace professional card draws just 70 watts while packing 16 GB of GDDR6 and full Ada tensor cores with FP8 support. At $0.28/hr on spot, the RTX 2000 Ada is built for always-on edge inference and compact deployments where power draw and physical size matter more than raw throughput.
At a glance
RTX 2000 Ada specifications.
Key hardware specs that determine what workloads this GPU handles.
288 GB/s
Memory Bandwidth
peak throughput
70W
TDP
thermal design power
Ada Lovelace
Architecture
NVIDIA GPU architecture
Spot pricing
RTX 2000 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 2000 Ada.
Tested model-GPU pairings with notes on why each is a good fit.
Phi-3 Mini 3.8B
3.8B in FP16 at 7.6 GB leaves 8.4 GB free. The RTX 2000 Ada's Ada tensor cores run Phi-3 Mini at efficient FP8 precision for maximum throughput per watt.
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Llama 3.2 3B
3B in FP16 at 6 GB runs with 10 GB headroom. Low-power serving for always-on assistant applications where the RTX 2000 Ada's 70W TDP keeps operational costs minimal.
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Gemma 2 2B
2B in FP16 at just 4 GB. Multiple instances can run simultaneously on the 16 GB VRAM, or use the remaining 12 GB for embedding models alongside the chat model.
View model pricing →
Use cases
What the RTX 2000 Ada is built for.
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Edge inference in power-constrained environments
The RTX 2000 Ada's 70W TDP is the lowest of any Ada Lovelace GPU — matching the T4 and L4 in power efficiency while offering Ada's improved tensor cores and FP8 support. Deploy 3B-7B models at retail kiosks, branch offices, IoT gateways, or any location where power budgets and cooling capacity are limited.
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Multi-model serving in compact form factors
The small-form-factor PCIe design fits in half-height, half-length (HHHL) slots that other GPUs can't physically enter. Run multiple small models (embeddings + chat + classification) on a single RTX 2000 Ada in a compact 1U server, with 16 GB split across lightweight models for multi-purpose AI endpoints.
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Professional driver certification for regulated edge deployments
Edge AI in healthcare (bedside diagnostics), retail (POS analytics), and industrial (quality inspection) often requires ISV-certified hardware. The RTX 2000 Ada carries NVIDIA professional certifications in a form factor that fits edge appliances — something consumer cards and data center GPUs can't match.
FAQ
Common questions.
RTX 2000 Ada vs T4 — both 16 GB at ~70W, which is better?
The RTX 2000 Ada (Ada Lovelace, $0.28/hr) has newer tensor cores with FP8 support and roughly 2x the inference throughput of the T4 (Turing, $0.18/hr). The T4 is cheaper and has wider cloud availability. For pure cost, the T4 wins. For performance-per-watt and FP8 capabilities, the RTX 2000 Ada is the better card at a $0.10/hr premium.
Can the RTX 2000 Ada handle 7B models?
In FP16, 7B needs ~14 GB — technically fits on the 16 GB card but leaves only 2 GB for KV cache, which limits concurrency to 1-2 simultaneous users. In INT8, 7B needs ~7 GB with 9 GB free — practical for moderate traffic. In FP8 (Ada-native), throughput improves further. For 7B production serving, INT8 or FP8 quantization is recommended on this card.
Why is the RTX 2000 Ada more expensive than the RTX A4000?
The RTX A4000 (Ampere, $0.17/hr) is a previous-generation card being offloaded at depreciated prices. The RTX 2000 Ada (Ada Lovelace, $0.28/hr) is current-gen with higher tensor throughput and FP8 support. The price reflects the generation gap — newer architecture commands a premium, even at the entry-level tier. If you don't need FP8 or Ada-specific features, the A4000 is the better value.
What's the bandwidth limitation in practice?
At 288 GB/s, the RTX 2000 Ada has the lowest bandwidth of any 16 GB GPU. Token generation speed is directly limited by bandwidth — expect roughly 60% of the T4's tokens/second on the same model, despite having faster tensor cores. The RTX 2000 Ada is bandwidth-limited, not compute-limited. It excels at high-batch, low-latency workloads where tensor utilization stays high, not at single-user interactive chat.
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