Alyph · Model comparison
Ask ChatGPT, Claude, and Gemini the same question. At once.
One prompt, one context, sent to multiple frontier models at the same time. You read the answers side by side and decide — no tabs, no re-pasting, no drift.
The short answer
Parallel model execution means sending the identical prompt with identical context to multiple frontier models simultaneously, so outputs are compared on merit rather than on setup differences. In Alyph, each model answers in its own isolated branch.
A client wants 20% off for a 12-month retainer. Take it?
Take it, with a 90-day out clause for both sides.
Counter at 10%. Discounts teach clients what to expect.
Only if the year is prepaid in cash.
What you get
- 300+ models: OpenAI, Anthropic, Google, DeepSeek, and more
- Identical context to every model — compare models, not prompts
- Answers render side by side on one canvas
- Continue the winning branch, prune the rest
- A three-model bake-off of a typical question costs cents
- One wallet, one set of spending limits
Why ask more than one model?
No single model is best at everything, and the ranking changes with every release. More importantly, a confidently wrong answer looks exactly like a correct one. When two models agree and a third disagrees, you’ve found the exact spot that deserves your attention — that disagreement is the cheapest review you will ever get.
The fair bake-off
- Fix the context. Every model gets the same files and constraints — the shared root above the branch point.
- Fix the prompt. The identical question, sent to all three at once. No paraphrasing drift between tabs.
- Judge by criteria, not vibes. Edge cases, stated assumptions, fit, signal.
- Continue the winner. Keep working in that branch; prune the rest.
The economics
Three provider subscriptions run about $60 a month — and still force the manual tab-switching workflow. In Alyph, a bake-off bills like any other request: provider token rates plus a 15% infrastructure margin, from one wallet. Three answers to a typical business question cost cents. See pricing →
Questions, answered
Which models can I compare?
Over 300 models from OpenAI, Anthropic, Google, DeepSeek, and more — all on the same canvas, all from one wallet. A practical trio is one frontier model from each major lab: their training differs enough that disagreements are genuinely informative.
Is asking three models at once expensive?
You pay token costs per model, so a bake-off costs roughly 3x a single query — typically cents for a business question. For high-stakes decisions like pricing or architecture, that’s far cheaper than acting on the wrong answer once.
Do the model branches see each other?
No. Each model answers in its own branch, inheriting only the shared context above the branch point. No model sees another’s answer unless you put it there — which is exactly what makes the comparison fair.
How do I know which answer is best?
Judge by criteria, not vibes: who caught the edge case, who stated their assumptions, whose answer fits how you actually work. When models disagree, the disagreement itself is the signal to dig deeper. The full method →
Try model comparison on the canvas
Free to start, with $5 of welcome credit. No subscription — cancel nothing, ever.