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Framework

Framework Laptop 16 (AMD Ryzen AI 300 Series)

Released Nov 20, 2025$1,499 launch priceLaptop

Framework's modular 16-inch laptop gets AMD Ryzen AI 300 Series mainboards (Ryzen AI 7 350 or Ryzen AI 9 HX 370 at launch) and an optional swappable NVIDIA GeForce RTX 5070 Graphics Module. Specs describe the Ryzen AI 7 350, RTX 5070, 16GB, 1TB build; pre-orders opened at $1,499 for the DIY Edition without the GPU module, which adds $650.

Pros

  • Swappable RTX 5070 Graphics Module (8GB GDDR7, 100W) that also fits existing Laptop 16 units; Framework claims 30-40% higher gaming frame rates than the Radeon RX 7700S module
  • Geekbench 6 scores of 2,878 single-core and 12,399 multi-core in review testing, with a single-core lead over the previous-generation Ryzen 7 7840HS Laptop 16
  • Matte 2560x1600 165Hz panel with G-Sync support when the RTX 5070 module is fitted
  • Six Expansion Card slots (four with display output), user-replaceable 85Wh battery, two SO-DIMM slots up to 96GB and two M.2 SSD slots
  • Optional 240W USB-C GaN adapter, plus Wi-Fi 7 and a second-generation 1080p webcam with hardware privacy switches

Cons

  • DIY Edition ships without RAM, storage, an OS or a power adapter; the RTX 5070 module adds $650 and the 240W adapter $109 to the $1,499 starting price
  • Screen peaked at 444 nits in review testing, below the 500-nit rating and 40 nits dimmer than the previous model
  • Measured runtime of about 8h20m with the RTX 5070 module fitted, down from 8h49m for the previous Radeon RX 7700S model
  • Keyboard module felt mushy and the seams around the spacers and touchpad looked cheap in review testing
46.5Inno Score

Below average

Computed from specs & benchmarks via our public methodology.

Performance46.6
Display44.8
Battery53.5
Portability40.2

Full specifications

Everything we track for the Framework Laptop 16 (AMD Ryzen AI 300 Series)

Display

Screen size
16 ″
Panel type
IPS LCD (matte anti-glare, VRR, G-Sync support with RTX 5070 module)
Resolution
2560x1600
Refresh rate
165 Hz
Peak brightness
500 nits

Performance

Graphics
NVIDIA GeForce RTX 5070 Laptop GPU (8GB GDDR7, 100W, swappable Graphics Module)
RAM
16 GB
RAM type
DDR5-5600 (SO-DIMM)
Storage
1,024 GB
Storage type
M.2 2280 NVMe SSD

Benchmarks

Geekbench 6 (single)
2,878Top 35%
Geekbench 6 (multi)
12,399Bottom 38%

Battery

Capacity
85 Wh
Web browsing endurance
8.3 h
Charging
240 W

Design

Weight
2.4 kg
Thickness
21 mm
Material
CNC aluminum top cover with thixomolded magnesium alloy bottom cover

Connectivity

Ports
6x swappable Expansion Cards (USB-C, USB-A, HDMI, DisplayPort, Ethernet, microSD/SD, 3.5mm audio options; four slots with display output and up to 240W charging, two with USB4), plus a USB-C port on the RTX 5070 module (display output, 240W charging)
Wi-Fi
Wi-Fi 7 (AMD RZ717)
Bluetooth
5.4
Webcam
1080p 30fps (2nd Gen, 9.2MP OmniVision OV08X sensor, 87° FOV), hardware privacy switch
Biometrics
Fingerprint reader (Windows Hello and Linux libfprint compatible)

Software

Operating system
Windows 11 Home (DIY Edition ships without an OS; Linux supported)

Quick answers

Is the Framework Laptop 16 (AMD Ryzen AI 300 Series) good in 2026?

The Framework Laptop 16 (AMD Ryzen AI 300 Series) earns an Inno Score of 46.5/100 (“Below average”) based on its specs and benchmark results. Framework's modular 16-inch laptop gets AMD Ryzen AI 300 Series mainboards (Ryzen AI 7 350 or Ryzen AI 9 HX 370 at launch) and an optional swappable NVIDIA GeForce RTX 5070 Graphics Module. Specs describe the Ryzen AI 7 350, RTX 5070, 16GB, 1TB build; pre-orders opened at $1,499 for the DIY Edition without the GPU module, which adds $650.

What are the key specs of the Framework Laptop 16 (AMD Ryzen AI 300 Series)?

Processor: AMD Ryzen AI 7 350 · RAM: 16 GB · Screen size: 16 ″ · Weight: 2.4 kg

What are the closest alternatives to the Framework Laptop 16 (AMD Ryzen AI 300 Series)?

Its closest rivals on InnoReviews are HP OmniBook X 14 (2026), Lenovo ThinkBook 14 Gen 8 (Intel), Lenovo ThinkPad E16 Gen 3 (Intel) — open the comparison pages for a spec-by-spec breakdown.

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