G.SKILL Ripjaws DDR4 SO-DIMM Series DDR4 RAM 16GB (2x8GB) 3200MT/s CL22-22-22-52 1.20V Unbuffered Non-ECC Notebook/Laptop Memory SO-DIMM (F4-3200C22D-16GRS)
Bottom line: The G.SKILL Ripjaws DDR4 SO-DIMM Series DDR4 RAM 16GB: Matched 2x8GB pair fills two SO-DIMM slots for dual-channel operation; main trade-off: CL22-22-22-52 timings are loose compared with lower-latency DDR4 kits.
As an Amazon Associate, SpecPicks earns from qualifying purchases. Full disclosure →
Pros & Cons
Pros
- ✓ Matched 2x8GB pair fills two SO-DIMM slots for dual-channel operation
- ✓ Rated for DDR4-3200, the top JEDEC DDR4 speed many current laptops support
- ✓ Standard 1.20V operation within normal notebook power limits
- ✓ JEDEC default profile boots at stock BIOS settings, no tuning needed
- ✓ Validated laptop list available via G.SKILL QVL and RAM Configurator tool
Cons
- ✗ CL22-22-22-52 timings are loose compared with lower-latency DDR4 kits
- ✗ 8GB per module caps the kit at 16GB in a two-slot laptop
- ✗ Must stay a matched pair; mixing with other kits risks instability
- ✗ Non-ECC unbuffered, so not suitable for ECC workstations or servers
Manufacturer description
The G.SKILL Ripjaws DDR4 SO-DIMM kit (F4-3200C22D-16GRS) gives your laptop 16GB of memory as two matched 8GB modules. That lets a notebook with two SO-DIMM slots run in dual-channel mode. Each 260-pin module is rated for DDR4-3200 at CL22-22-22-52 and 1.20V, the standard DDR4 voltage, so it works within the power limits of most notebooks. The kit includes a JEDEC default profile and boots at the JEDEC default SPD speed with default BIOS settings on compatible hardware. In most laptops that means no BIOS changes and no overclocking menus. If you are moving up from 8GB, the extra capacity…
SpecPicks Verdict
SpecPicks scored G.SKILL Ripjaws DDR4 SO-DIMM Series DDR4 RAM 16GB (2x8GB) 3200MT/s… using a rating × review-volume × price-fit model applied to published specs and reviews across the memory & ram category. G.SKILL's memory & ram lineup sits within the broader category mid-tier; price and specs are the deciding factors over brand loyalty here. Judge it on the specification table and the price rather than on sentiment: check the figures that decide your use case, then put it side-by-side with two or three close alternatives in the Compare tool before clicking through.
Common buyer scenarios for memory & ram of this kind: matching it to an existing build, replacing a failing part, or upgrading from a previous-generation equivalent. Check the spec table below against your current setup — particularly socket / form-factor / power-rating fields — and confirm compatibility on the retailer's listing before purchase. Prices and stock are set by the retailer and may have moved since this page was last updated.
Frequently Asked Questions
Will this G.SKILL Ripjaws kit fit my laptop?
It is a 260-pin DDR4 SO-DIMM kit for laptops and notebooks. To confirm your exact model, use the G.SKILL memory QVL or the RAM Configurator tool on the G.SKILL website.
Do I need to change BIOS settings to use DDR4-3200?
No, in most cases. The kit includes a JEDEC default profile and boots at the JEDEC default SPD speed with default BIOS settings on compatible hardware.
Can I add this kit to the RAM already in my laptop?
G.SKILL advises against it. The two 8GB modules are sold as a matched set, and mixing memory kits can cause stability problems or system failure. Replace your existing modules with this pair instead.
What are the full specs of the F4-3200C22D-16GRS?
16GB total as 2x8GB modules, DDR4-3200, CL22-22-22-52 timings, 1.20V, non-ECC, unbuffered, 260-pin SO-DIMM form factor.
Is this ECC memory for a workstation or server?
No. This is non-ECC unbuffered memory for consumer laptops and notebooks. Systems that require ECC or registered memory need a different kit.
Key Features
- G.SKILL Ripjaws DDR4 SO-DIMM Series DDR4 SO-DIMM Memory Kit, Model: F4-3200C22D-16GRS
- 16GB total capacity kit containing 2x8GB modules, rated for up to DDR4-3200 CL22-22-22-52 at 1.20V
- Non-ECC, DDR4 SO-DIMM, 260-pin, for Laptop/Notebook
- Includes JEDEC default profile
- Do not mix memory kits. Memory kits are sold in matched kits that are designed to run together as a set. Mixing memory kits will result in stability issues or system failure.
- Refer to G.SKILL memory QVL or RAM Configurator tool on the G.SKILL website for more details on validated motherboard and hardware.
Full Specifications
| Brand | G.SKILL |
|---|---|
| Voltage | 1.2 Volts |
| RAM Size | 16 GB |
| Model Name | Ripjaws DDR4 SO-DIMM |
| Unit Count | 1.0 Count |
| Form Factor | SO-DIMM |
| Memory Speed | 3200 MT/s |
| Model Number | F4-3200C22D-16GRS |
| Built-In Media | Camera body |
| Number of Pins | 260 |
| Mfr Part Number | F4-3200C22D-16GRS |
| Memory Generation | DDR4 |
| Compatible Devices | Laptop |
| Data Transfer Rate | 3200 MHz |
| Memory Form Factor | SODIMM |
| Additional Features | Plug & Play |
| Computer Memory Size | 16 GB |
| Warranty Description | Limited Lifetime Manufacturer |
| RAM Memory Technology | DDR4 |
| Column Address Strobe Latency | 22 |
Hardware benchmark data
Ready to buy?
G.SKILL Ripjaws DDR4 SO-DIMM Series DDR4 RAM 16GB (2x8GB) 3200MT/s CL22-22-22-52 1.20V Unbuffered Non-ECC Notebook/Laptop Memory SO-DIMM (F4-3200C22D-16GRS) is listed on Amazon. Price, availability, shipping and returns are set by Amazon and its sellers — check the listing for current terms. SpecPicks earns a small commission on qualifying purchases — thank you for supporting independent review work.
Related Memory & RAM
More guides & deep dives from the SpecPicks archive
Browse all articles & guides →- How to Build a Windows 98 Retro PC in 2026
- Best Budget Gaming PC Build 2026 — ~$1,000 Parts List
- The Complete Voodoo5 5500 AGP Driver Guide (2026 Edition)
- RTX 4070 Super vs RX 7800 XT — Which to Buy in 2026
- Best Retro Handhelds in 2026 — From $35 to $500
- Emulation Hardware in 2026: FPGA, Software, and Cart-Reader Ecosystems
- Best 1440p Gaming GPUs in 2026
More reviews from the SpecPicks archive
Browse all reviews →- Kimi-Dev-72B Local Coding Benchmarks: VRAM Required, Tok/s, and How It Stacks Against DeepSeek V4 and…
- NVK Open-Source Vulkan Driver Gains Experimental DLSS on Linux
- Crucial BX500 vs Samsung 870 EVO for Budget & Retro Builds
- Intel Arc AI Training in 2026: What Workloads Actually Work
- The $500M Claude Bill: What Local LLM Inference Actually Costs
- Building a Local LLM Workstation on a Raspberry Pi 5 + Ryzen 7 5800X Hybrid
- Samsung SSD Brand Guide 2026: Every Drive Worth Buying
- Raspberry Pi 4 8GB vs Pi Zero W: Which Fits Your First Project?
- Running local LLMs on the Ryzen 5 5600G iGPU (no dedicated GPU) in 2026
- Ollama on a 12GB RTX 3060: Best Models and tok/s in 2026
- NVIDIA Cosmos 3 vs Ideogram 4.0: Which Open Image Model to Run on 12GB
- 007 First Light on Steam Deck: Performance & Best Settings
- Apple Intelligence Ships in China on Alibaba's Qwen: What It Means
- G4-Meromero 31B: Running the Uncensored Gemma 4 Finetune on a 12GB RTX 3060
- The $5M Sega Bet That Saved Nvidia — and Still Shapes GPU Launches
- CompactFlash Boot Drive for a Win98 / XP Retro PC (2026 Guide)
- Pi Pico Puts Bluetooth Keyboards on the I2C Bus
- 16% of Freelance Jobs Are Now AI-Doable: The Local Agent Rig That Runs Them
- Best AM4 CPU to Pair With an RTX 3060 12GB in 2026
- vLLM on a Single RTX 3060 12GB: Batched Serving Numbers and When It's Worth It (2026)
- Tesla P40 vs RTX 3090: Used 24GB GPUs for Local LLMs in 2026
- 768GB Intel Optane DIMM Rigs: Can Cheap Persistent Memory Really Run a 1T-Parameter LLM?
- Best SATA SSD for the PS4 Pro in 2026 (Cheap Speed Upgrade)
- Raspberry Pi LLM Projects: What Actually Runs in 2026
Earliest SpecPicks reviews
Browse full archive →- Best GPU for Llama 3.1 8B (2026)
- Best GPU for Qwen 3 14B (2026)
- Best GPU for Qwen 3 32B (2026)
- Best GPU for Llama 3.1 70B (2026)
- Best GPU for DeepSeek-R1 32B (2026)
- Best GPU for Llama 3.1 405B (2026)
- How to run Llama 3.1 8B on NVIDIA GeForce RTX 5090
- How to run Qwen 3 14B on NVIDIA GeForce RTX 5090
- How to run Qwen 3 32B on NVIDIA GeForce RTX 5090
- How to run Llama 3.1 70B on NVIDIA GeForce RTX 5090
- How to run DeepSeek-R1 32B on NVIDIA GeForce RTX 5090
- How to run Llama 3.1 8B on NVIDIA GeForce RTX 4090