NVIDIA RTX Spark N1 (64GB Unified)
64 GB Unified · 200 GB/s
From
TBA
Pricing not announced
Unified Memory
64 GB
Bandwidth
200 GB/s
TDP
80W
Models
0
Tier
Full
The NVIDIA RTX Spark N1 (64GB Unified) with 64 GB unified memory. Performance data is being compiled.
Source: OwnRig methodology
64 GB
200 GB/s
Unified
80W
4096
16
700 TOPS
Surface Laptop Ultra, HP OmniBook X 14, Lenovo Yoga Pro 9n
Builder Capability: Full AI Builder
Supports concurrent coding + reasoning + embeddings. Can run 70B models at quantized precision.
Inference Backends
The software stacks that matter most for real-world inference on this device.
CUDA
betaArm Windows CUDA stack is pre-release; verify llama.cpp and GGUF runtimes on shipping hardware.
TensorRT-LLM
betaPrimary NVIDIA path for local agents; no OwnRig tok/s benchmarks on RTX Spark yet.
Windows ML
experimentalRequired for Windows-native models such as Aion 1.0 Plan when GA; not validated for arbitrary GGUF workloads.
Frequently Asked Questions
- What AI models can NVIDIA RTX Spark N1 (64GB Unified) run?
- The NVIDIA RTX Spark N1 (64GB Unified) can run 0 AI models. See the full compatibility table above for speeds and quality ratings.
- Is NVIDIA RTX Spark N1 (64GB Unified) good for AI coding?
- Yes. With 64 GB, the NVIDIA RTX Spark N1 (64GB Unified) supports the Full AI Builder tier: concurrent coding + reasoning + embeddings.
- How much memory does NVIDIA RTX Spark N1 (64GB Unified) have?
- The NVIDIA RTX Spark N1 (64GB Unified) has 64 GB of unified memory with 200 GB/s bandwidth.
- Can NVIDIA RTX Spark N1 (64GB Unified) run 70B models?
- 70B models typically require 24-48 GB of inference memory. The NVIDIA RTX Spark N1 (64GB Unified)'s 64 GB may not be sufficient. Consider a higher-tier device.
- Is NVIDIA RTX Spark N1 (64GB Unified) worth it for AI?
- Pricing for NVIDIA RTX Spark N1 (64GB Unified) has not been announced. It offers 64 GB unified memory, but OwnRig should treat recommendations as provisional until pricing and benchmarks are available.
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