Get the best Machine Learning and AI Laptop with a 32-core i9-14900HX CPU, 16 GB RTX 4090, 96 GB of fast RAM, and 12 GB of NVMe storage. Use the GPU-accelerated Focus Deep Learning Suite to start developing AI pipelines in minutes.
Run GPU-accelerated AI in minutes with the Focus Deep Learning Suite. It guides you to install Anaconda and then add and test TensorFlow, PyTorch, and Jupyter Notebook as needed. Develop pipelines with industry-standard PyCharm from the included JetBrains Toolbox.
The RTX 4090 M shows an astounding 90% performance increase over the last-gen RTX 3080 Ti M on AI Bench. Even the RTX 4080 M is 53% faster. The TSMC “4N” lithography and evolutionary features make the 40-series GPUs substantially more efficient than the 30-series.
RESULTS [1,2,3] | RTX 4090 M | RTX 4080 M | RTX 4070 M | RTX 3080 Ti M | RTX 4060 M | RTX 3070 Ti M | RTX 3060 M |
---|---|---|---|---|---|---|---|
Inference | 26,263 | 21,077 | 13,343 | 14,245 | 11,843 | 13,153 | 10,265 |
Training | 31,791 | 25,201 | 15,872 | 16,034 | 14,164 | 14,782 | 11,806 |
AI Score | 58,054 | 46,277 | 29,215 | 30,279 | 26,007 | 27,935 | 22,071 |
Video RAM | 16 GB | 12 GB | 8 GB | 16 GB | 8 GB | 8 GB | 6 GB |
[1] See official comparison chart
[2] All 40-series from Kubuntu Focus M2 GEN 5
[3] All 30-series from Kubuntu Focus M2 GEN 4
We continuously validate, curate, and pin the Deep Learning Suite, graphics drivers, CUDA, cuDNN, TensorRT, and OptiX to always provide excellent performance, reliability, and compatibility across ML and GPU workloads. Get all these improvements through normal software updates.
Of course, the M2 can do far more than just AI, ML, and data science! Develop Apache Spark big data projects. Render Blender Optix scenes. Coordinate Kubernetes clusters. Build every asset of a web app simultaneously. Experience complex games and simulations with incredible frame rates. Focus on your work while our team delivers powerful optimizations, tools, and updates developed and tested for your hardware[2].
[1] Versus CPU-only ML pipelines.
[2] Focus retains copies of models and validates updates on them for a minimum of 3 years after last sale date. Canonical, Ubuntu, and Kubuntu define LTS OS support periods, and Focus provides optimizations, tools, and docs for a given OS during this time.
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