Models covered
This tool compares Claude 3.5 Sonnet & Haiku (Anthropic), GPT-4o & GPT-4o mini (OpenAI),
Gemini 1.5 Pro & 2.0 Flash (Google), Llama 3.1 70B (Meta), Mistral Large, and Phi-3 Mini
(Microsoft).
Scoring methodology
Recommendations are scored based on task-model fit, budget tier, context window match,
speed requirement, and deployment preference. Results are deterministic — no AI is used
to generate them.
Prices may vary
Pricing shown is approximate based on public provider pages as of early 2026. Always
check the official pricing pages before committing to a model in production — prices
and capabilities change frequently.
Why a questionnaire instead of a benchmark table?
Benchmark tables answer the wrong question. They tell you which model tops MMLU, not which one fits a
support chatbot with a $200 monthly budget. This tool works the other way around: you describe the job,
it ranks the candidates. Five questions cover the things that actually decide the choice — what the model
does all day (code generation, chat, document analysis, vision, function calling, streaming, long documents,
or embeddings), how much you'll spend, how much context you need, how fast responses have to come back,
and whether the model can live in a cloud API or has to run on your own hardware.
Where this saves real time
A team building an internal document Q&A bot lands on a different answer than a solo dev shipping a
coding assistant, and both land on a different answer than a company that can't send data to a third-party
API at all. The on-premise question alone eliminates most of the field — if your compliance team says data
stays in-house, the ranking narrows to models like Llama 3.1 70B and Phi-3 Mini that you can self-host.
The picker makes those eliminations explicit instead of leaving them buried in ten pricing pages.
Frequently asked questions
Does this tool call an AI to make recommendations?
No. The scoring is a fixed rule set that runs in your browser. Same answers in, same three models out, every time. That's deliberate — a recommendation you can't reproduce isn't one you can defend to your team.
Are my answers sent anywhere?
No. Everything runs client-side. Nothing about your use case, budget, or deployment constraints leaves the page.
Why isn't the newest model from provider X listed?
The tool covers nine models across five providers (see "Models covered" above). New models ship constantly, so treat the result as a shortlist to verify, not a final decision.
Should I trust the pricing numbers?
Use them for relative comparison, not billing math. They're approximations from public pricing pages as of early 2026, and providers change prices without warning.
// huntermussel
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