Benchmarking the RTX Spark
See the first results from the Microsoft Surface Laptop Ultra.AI
The first RTX Spark laptops are here, and with them, our first round of benchmarks for this new breed of laptop.
First announced at Computex, RTX Spark is NVIDIA's first complete laptop processor, with CPU, GPU, and memory on a single package. The first laptops launch October 16, and include the machine tested here, the Surface Laptop Ultra from Microsoft.
At the heart of RTX Spark is a bespoke System-on-Chip (SoC) co-developed with MediaTek. The flagship configuration, named the N1X, combines a 20-core NVIDIA Grace CPU (featuring a cluster of high-performance Arm Cortex-X925 and power-efficient A725 cores) with a Blackwell-generation RTX GPU packing 48 Streaming Multiprocessors and up to 6,144 CUDA cores. If that core count sounds familiar to PC builders, it should: it sits right in line with NVIDIA's desktop GeForce RTX 5070 class.
By supplying up to 128GB of shared LPDDR5X unified memory, the Grace CPU and Blackwell GPU share direct access to the same memory space. Armed with NVIDIA's 5th-generation Tensor Cores and native FP4 micro-scaling, an RTX Spark laptop can load and run massive 120-billion-parameter LLMs locally.
We ran our new Micro Center AI benchmarks on the Surface Laptop Ultra, and the initial results are below.
Unless noted, higher is better. A short prompt is about 90 tokens and a long prompt is about 9,000. The RTX Spark laptop ran NVIDIA's native ARM64 build of llama.cpp.
Generation speed
Output tokens per second once the model starts answering.
| Model / prompt | RTX Spark (Surface Laptop Ultra) |
|---|---|
| GLM 4.7 Flash | |
| General, short prompt | 55.6 |
| General, long prompt | 48.9 |
| Coding, short prompt | 55.4 |
| Coding, long prompt | 49.0 |
| Nemotron 3 Nano Omni 30B | |
| General, short prompt | 63.9 |
| General, long prompt | 62.6 |
| Coding, short prompt | 64.0 |
| Coding, long prompt | 63.0 |
| Qwen3.5 122B A10B | |
| General, short prompt | 35.2 |
| General, long prompt | 34.0 |
| Coding, short prompt | 35.3 |
| Coding, long prompt | 35.0 |
| Muse Glimmer 30B | |
| General, short prompt | 15.9 |
| General, long prompt | 15.6 |
| Coding, short prompt | 15.9 |
| Coding, long prompt | 15.6 |
| Qwen3.8 27B | |
| General, short prompt | 14.5 |
| General, long prompt | 14.1 |
| Coding, short prompt | 14.8 |
| Coding, long prompt | 14.3 |
Prompt processing speed
How quickly each system reads your prompt, in prompt tokens per second.
| Model / prompt | RTX Spark (Surface Laptop Ultra) |
|---|---|
| GLM 4.7 Flash | |
| General, short prompt | 452 |
| General, long prompt | 1,336 |
| Coding, short prompt | 457 |
| Coding, long prompt | 1,341 |
| Nemotron 3 Nano Omni 30B | |
| General, short prompt | 352 |
| General, long prompt | 1,865 |
| Coding, short prompt | 360 |
| Coding, long prompt | 1,835 |
| Qwen3.5 122B A10B | |
| General, short prompt | 168 |
| General, long prompt | 604 |
| Coding, short prompt | 183 |
| Coding, long prompt | 611 |
| Muse Glimmer 30B | |
| General, short prompt | 253 |
| General, long prompt | 782 |
| Coding, short prompt | 263 |
| Coding, long prompt | 786 |
| Qwen3.8 27B | |
| General, short prompt | 352 |
| General, long prompt | 665 |
| Coding, short prompt | 338 |
| Coding, long prompt | 669 |
Time to first token
How long you wait before the first word of the answer appears, in seconds. Lower is better.
| Model / prompt | RTX Spark (Surface Laptop Ultra) |
|---|---|
| GLM 4.7 Flash | |
| General, short prompt | 0.19 |
| General, long prompt | 6.79 |
| Coding, short prompt | 0.20 |
| Coding, long prompt | 6.43 |
| Nemotron 3 Nano Omni 30B | |
| General, short prompt | 0.29 |
| General, long prompt | 5.36 |
| Coding, short prompt | 0.30 |
| Coding, long prompt | 5.09 |
| Qwen3.5 122B A10B | |
| General, short prompt | 0.58 |
| General, long prompt | 16.38 |
| Coding, short prompt | 0.55 |
| Coding, long prompt | 15.48 |
| Muse Glimmer 30B | |
| General, short prompt | 0.55 |
| General, long prompt | 11.45 |
| Coding, short prompt | 0.54 |
| Coding, long prompt | 11.03 |
| Qwen3.8 27B | |
| General, short prompt | 0.40 |
| General, long prompt | 14.92 |
| Coding, short prompt | 0.43 |
| Coding, long prompt | 14.20 |
Efficiency and power
Output tokens per watt-hour of energy (higher is better) and average GPU power draw while generating, in watts (lower is better), across 40 requests per model (4 prompts x 10 runs).
| Model | Tokens per watt-hour | Avg. power (W, lower is better) |
|---|---|---|
| GLM 4.7 Flash | 2,992 | 47 |
| Nemotron 3 Nano Omni 30B | 3,894 | 44 |
| Qwen3.5 122B A10B | 1,665 | 48 |
| Muse Glimmer 30B | 1,117 | 43 |
| Qwen3.8 27B | 1,010 | 43 |
Gaming: Cyberpunk 2077
We also ran Cyberpunk 2077's built-in benchmark on the Surface Laptop Ultra at 1080p, 1440p, and its full 3270 x 2180 resolution. Native means DLSS and frame generation are off. DLSS Balanced uses the Transformer model with frame generation off, and DLSS + 4x FG adds multi-frame generation. RT Low turns on local shadow ray tracing only; RT Ultra adds reflections, sun and local shadows, and Ultra lighting. Path tracing is off.
| Setting / mode | 1080p | 1440p | Full res (3270 x 2180) |
|---|---|---|---|
| Low / Native | 91.32 | 81.60 | 53.90 |
| Low / DLSS Balanced | 95.75 | 90.89 | 69.69 |
| Low / DLSS + 4x FG | 305.65 | 196.60 | 145.52 |
| Ultra / Native | 71.90 | 48.58 | 25.43 |
| Ultra / DLSS Balanced | 82.14 | 65.34 | 39.53 |
| Ultra / DLSS + 4x FG | 224.10 | 151.20 | 105.40 |
| RT Low / Native | 68.44 | 44.21 | 23.76 |
| RT Low / DLSS Balanced | 82.96 | 61.58 | 37.42 |
| RT Low / DLSS + 4x FG | 215.95 | 147.26 | 100.62 |
| RT Ultra / Native | 32.27 | 21.48 | 13.61 |
| RT Ultra / DLSS Balanced | 52.44 | 37.60 | 24.45 |
| RT Ultra / DLSS + 4x FG | 155.86 | 109.96 | 76.47 |
Frame-generation results include generated frames. Each result is a single pass of the roughly 64-second built-in benchmark, tested on October 11, 2026, with game version 2.31 and driver 617.42.
RTX Spark laptops are coming to Micro Center, with systems hitting shelves starting October 16. Brands to look for include Asus, Dell, HP, Lenovo, Microsoft, and MSI. Stay tuned and we'll bring you more benchmark testing and hands-on reviews, plus all the RTX Spark shopping advice you'll need, and if you want to see these machines in person, keep an eye on your local Micro Center.
More from MC News
- Run AI Locally: The Best LLMs for 8GB, 16GB, 32GB Memory and Beyond
- How to Use Local AI With Your Own Files: A Beginner's Guide to RAG
- Reading vs. Answering: The Two Hardware Bottlenecks Behind Local AI Performance
- How to Use a Local LLM in Visual Studio Code
- Hands-On with the AMD Ryzen AI Halo
- Quantization Explained: Why the Same LLM Gives Better Results on High-End Hardware
- Why Context Length, Not AI Model Size, Is Your Biggest VRAM Problem
- How to Use LM Studio to turn your PC into an AI Server
- Why VRAM and Memory Bandwidth are Key for Powering Local AI
- Keyboard 101: Intro to Computer Keyboards
- Fix It Yourself: Talking to iFixit on Why Repairable Tech Matters
- The Local LLM Your Laptop's Been Waiting For
- Gemma vs Qwen: Which Local AI is Best?
Micro Center Editor-in-Chief Dan Ackerman is a veteran technology journalist with over 20 years of experience testing and reviewing the latest consumer tech. He previously served as Editor-in-Chief of Gizmodo and Editorial Director at CNET and is the author of the New York Times-reviewed book The Tetris Effect, a critically acclaimed Cold War history of the world's most influential video game. Reach him at dackerman at microcenter.com.
Comment on This Post
See More Blog Categories
Recent Posts
Watch: MSI Prestige N16 Flip AI+ Review: RTX Spark Built for Creators
We take a closer look at the MSI Prestige N16 Flip AI+, a 2-in-1 with NVIDIA RTX Spark, 128GB of unified memory, and a 4K Tandem OLED touchscreen.
Continue Reading About Watch: MSI Prestige N16 Flip AI+ Review: RTX Spark Built for Creators
