Valentin Fourier is a developer, SEO consultant, and the editor behind GPUBeacon. He builds comparison products for markets that hide the real price, and he trains and serves models often enough to care which hour is actually in stock. He writes in English on purpose: GPU buyers search in English, the catalog is in English, and a review that reads like a machine translation is a waste of the reader’s time. The prose is a design doc, not a landing page. On-demand first, VRAM on the table, interconnect named, waitlists labeled. If a sentence could have been written by the vendor, he cuts it.
Why this site exists
I am a developer who ended up in SEO, and a person who fine-tunes models often enough to hate a pricing page. The GPU market is fragmented on purpose. Hyperscalers quote. Marketplaces hide host risk in a reliability score. Managed clouds call interruptible inventory on-demand.
GPUBeacon is the index I wanted: published on-demand hours, VRAM, GPU count, interconnect, stock. Spot is a flag. Commissions never move a row. I take a side in the copy because a comparison without a verdict is a brochure with extra steps.
English, on purpose
I am French. GPUBeacon is not. The people who rent H100s this week search in English, compare in English, and paste error logs in English. I write the reviews that way: proper English, short sentences, no Franglais, no ‘seamless ecosystem’ that means nothing.
If a line would embarrass you in a design doc, it does not ship. That is the standard. Not a translation. Not an AI polish pass over French notes. English as the working language of this market.
How I review a provider
First I name the business model, marketplace, managed neocloud, inference API, or hyperscaler. Then I look at what is actually in the catalog this week. Then I write who should rent here and who should leave. That order does not change because a vendor has a nicer landing page.
I do not publish star scores. I do not invent SLAs. I do not mix a spot H100 with an on-demand H100 and call it the same product. If I am wrong, email me. The catalog is the source of truth; the prose is my reading of it.
How I write a vs page
A vs page is a decision, not two reviews glued together. I name the pair in the H1, I put the result in the first screen, and I say whether I pick left, right, or split. Then I prove it: same catalog fields, when to rent each, the trap that usually cheats the comparison, and the listings.
I do not publish a star score. I do not mix a waitlist from-price with an in-stock hour. If you cannot leave the page knowing which SKU or which cloud to open, the page is not done.
LLMs, on purpose
Most of the people landing on these pages are not benchmarking FLOPs for a paper. They are fitting a 70B, serving a LoRA, or trying to keep a KV cache in HBM without paying Blackwell tax they will not use. I write to that job. VRAM first. Checkpointing second. Interconnect when the job leaves one GPU.
What he actually works on
- On-demand GPU comparison
- LLM fine-tunes and serving
- VRAM vs FLOPs trade-offs
- Technical SEO
- Marketplace vs managed clouds
- Catalog-first editorial
- GPU vs GPU and provider vs provider verdicts
- English for a technical audience