Framework · Laptop
Framework 16 (Radeon RX 7700S)
Repairable, sustainable laptop with dGPU for local inference
- 32 GBsystem RAM
- 32Bfits in memory (Q4, 8k)
- 14Bpractical (estimate)
- 40 Wmax draw
- ~€1,900indicative price
What can it run?
Pick a job or a model size. The bar compares what it needs with this machine's usable memory.
- Model weights
- Context cache
- Runtime + extras (Whisper, embeddings)
How we calculate this
Weights = parameters × bits per weight / 8 (Q4_K_M ≈ 4.85; Q8_0 ≈ 8.5). Cache = context tokens × the reference model's per-token size (layers × KV heads × head size × 2 × 2 bytes). Plus 1.5 GB of runtime. Usable memory = total minus what the system keeps (3–6 GB on shared memory, 0.5 GB on a GPU). Comfortable = fits in 85%. It is a ±20% estimate: measure it on your machine before you decide. How to pick the GGUF file
When does it beat the cloud?
Set your usage. We compare the purchase plus electricity with what you would pay a cloud API.
| Month | Own hardware | Cloud |
|---|
- Own hardware (purchase + electricity)
- Cloud API
Assumptions: €0.25/kWh (Spain average, editable), USD 1 = €0.92, 3 input tokens per output token, and the machine at maximum draw for every hour it is on (worst case). API prices verified 2026-09-09. Your time and maintenance are not included. Note: the cloud side is a frontier model and here you would run a smaller open one; this compares cost, not quality.
Learn with this machine
- GDPR and AI in 2026: Local Deployment Is the Clean AnswerEUR 7.1 billion in GDPR fines since 2018 and 443 breach notifications a day (DLA Piper, 2026). Why local AI removes the cross-border transfer risk.
- Local AI ROI: What the Cloud-Exit Case Studies Really ShowDell's commissioned ROI model and 37signals' own cloud-exit figures, read carefully: what they prove, what they don't, and how to run the numbers for your SME.
- Local AI: what it is, what you need and when it pays offWhat running AI on your own hardware means, the three pieces you need, where it falls short today and when it costs less than a cloud API.
- GGUF Quantization: Pick the Right File for Your MachineHow to read a GGUF file name, choose between Q4_K_M, Q5 and Q8 for the memory you have, and measure speed, memory and quality yourself with three commands.
Skip it if…
- you want speed: here the model runs on the CPU from system RAM, not on the GPU.
Specs and where the numbers come from
| CPU | AMD Ryzen 9 7940HS |
|---|---|
| GPU | Radeon RX 7700S 8GB |
| NPU | Ryzen AI |
| Memory | 32 GB (system RAM); usable by the model ≈ 28 GB |
| Speed | 15 tok/s with 14B Q4 vendor or community estimate, not measured by us |
| Price | ~€1,900 indicative, checked 2026-09-19; check the live price in the shop |
We only call something "measured" when it ran on our machines. Editorial policy