NVIDIA RTX A6000
E797606
The NVIDIA RTX A6000 is a high-end professional graphics card designed for demanding workloads like AI, data science, and advanced 3D content creation.
All labels observed (3)
| Label | Occurrences |
|---|---|
| NVIDIA RTX A6000 canonical | 2 |
| NVIDIA RTX 6000 Ada Generation | 1 |
| NVIDIA RTX A6000 professional GPU | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T9323340 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NVIDIA RTX A6000 Context triple: [NVIDIA Ampere architecture, notableGPU, NVIDIA RTX A6000]
-
A.
NVIDIA A100
The NVIDIA A100 is a high-performance data center GPU designed for AI, high-performance computing, and data analytics workloads, featuring advanced Tensor Core acceleration.
-
B.
NVIDIA A40
The NVIDIA A40 is a high-performance data center GPU designed for professional visualization, AI inference, and compute workloads, built on NVIDIA’s Ampere generation.
-
C.
NVIDIA Quadro
NVIDIA Quadro is a line of professional-grade graphics cards designed for demanding visualization, CAD, and content creation workloads in workstations and enterprise environments.
-
D.
NVIDIA A30
The NVIDIA A30 is a data center GPU designed for accelerated computing workloads such as AI inference, training, and high-performance computing, offering a balance of performance and efficiency for enterprise deployments.
-
E.
NVIDIA DGX
NVIDIA DGX is a line of high-performance, AI-optimized computing systems designed for training and deploying large-scale machine learning and deep learning models.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: NVIDIA RTX A6000 Target entity description: The NVIDIA RTX A6000 is a high-end professional graphics card designed for demanding workloads like AI, data science, and advanced 3D content creation.
-
A.
NVIDIA A100
The NVIDIA A100 is a high-performance data center GPU designed for AI, high-performance computing, and data analytics workloads, featuring advanced Tensor Core acceleration.
-
B.
NVIDIA A40
The NVIDIA A40 is a high-performance data center GPU designed for professional visualization, AI inference, and compute workloads, built on NVIDIA’s Ampere generation.
-
C.
NVIDIA Quadro
NVIDIA Quadro is a line of professional-grade graphics cards designed for demanding visualization, CAD, and content creation workloads in workstations and enterprise environments.
-
D.
NVIDIA A30
The NVIDIA A30 is a data center GPU designed for accelerated computing workloads such as AI inference, training, and high-performance computing, offering a balance of performance and efficiency for enterprise deployments.
-
E.
NVIDIA DGX
NVIDIA DGX is a line of high-performance, AI-optimized computing systems designed for training and deploying large-scale machine learning and deep learning models.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
professional graphics card
ⓘ
workstation GPU ⓘ |
| architecture | Ampere ⓘ |
| coolingType | active cooling ⓘ |
| cudaCores | 10752 ⓘ |
| displayConnectors | 4x DisplayPort 1.4a ⓘ |
| formFactor | dual-slot ⓘ |
| gpuModel | GA102 ⓘ |
| interface | PCI Express 4.0 x16 ⓘ |
| manufacturer |
NVIDIA
ⓘ
linked to:
NVIDIA Corporation
|
| maxNVLinkGPUs | 2 ⓘ |
| maxPowerConsumption | 300 W ⓘ |
| memoryBandwidth | 768 GB/s ⓘ |
| memoryBusWidth | 384-bit ⓘ |
| memoryCapacity | 48 GB ⓘ |
| memoryType | GDDR6 ECC ⓘ |
| nvlinkBridgeWidth | 112.5 GB/s per direction ⓘ |
| powerConnectors | 1x 8-pin PCIe ⓘ |
| productLine |
NVIDIA RTX (professional)
ⓘ
linked to:
RTX
|
| rayTracingCores | 2nd generation ⓘ |
| releasePeriod | around Q4 2020 ⓘ |
| supports8KDisplay | true ⓘ |
| supportsAPIs |
CUDA
ⓘ
linked to:
NVIDIA CUDA
DirectX 12 Ultimate ⓘ NVIDIA OptiX ⓘ OpenCL ⓘ OpenGL ⓘ Vulkan ⓘ |
| supportsDLSS | true ⓘ |
| supportsECCMemory | true ⓘ |
| supportsHDR | true ⓘ |
| supportsMIG | false ⓘ |
| supportsMultiMonitor | true ⓘ |
| supportsNvidiaOmniverse | true ⓘ |
| supportsNvidiaRTXTechnology | true ⓘ |
| supportsNvidiavGPU | true ⓘ |
| supportsNVLink | true ⓘ |
| supportsQuadBufferedStereo | true ⓘ |
| supportsRayTracing | true ⓘ |
| supportsVirtualization | true ⓘ |
| targetMarket | workstations ⓘ |
| targetUsers |
AI researchers
ⓘ
data scientists ⓘ professional content creators ⓘ |
| tensorCores | 3rd generation ⓘ |
| useCase |
3D rendering and visualization
ⓘ
AI training and inference ⓘ VR and AR content creation ⓘ data science and analytics ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: NVIDIA RTX A6000 Description of subject: The NVIDIA RTX A6000 is a high-end professional graphics card designed for demanding workloads like AI, data science, and advanced 3D content creation.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: NVIDIA RTX A6000
linked to: NVIDIA RTX A6000