Find Your Perfect AI Model
8 questions. 60 seconds. Top 3 picks ranked by your exact workload. No signup, no email, no nonsense — just the AI models that match what you actually need.
Why a quiz beats a comparison table
Comparison tables are great when you already know what you're looking for. The problem is that for most teams, the question isn't "is GPT-5 cheaper than Claude Sonnet?" — it's "which of these 134 models should I even be evaluating?" That's a decision tree, not a spreadsheet, which is why we built this quiz.
Use case first
The single biggest determinant of which model fits is what you want it to do. The quiz starts there and filters aggressively before considering anything else.
Constraints next
Latency, cost ceiling and compliance are hard constraints — miss them and the model is unusable regardless of quality. The quiz applies these before secondary signals like context length and tool-use.
Ranking last
Only after filtering do we rank the survivors by quality tier and pricing fit. You get three real candidates instead of a 234-row table you'd never actually read.
How the scoring works
Behind the quiz sits a deterministic scoring matrix — no LLM, no black box. Each of the eight answers contributes a numeric weight toward every model in the catalogue:
- Use case (60 pts): the dominant signal. A model tagged for coding gets the full +60 when you select 'Coding'; one that only fits 'general' gets +15; one that doesn't fit at all is filtered out with a punitive -100 so it can't show up by accident.
- Latency (+25 / -30): sub-400ms first-token latency earns a strong boost if you marked latency critical. Missing the ceiling triggers a 30-point penalty so a 4-second reasoner can't sneak into a real-time recommendation.
- Quality (+30 / -25): tier-3 frontier models win the bonus when you ask for SOTA. The 'open-source OK' option additionally rewards models with open weights.
- Budget (+30 / sliding): sub-$1-per-million tokens earns the full bonus on a tight budget. Overshoot is a soft penalty that scales with how far over the ceiling the model sits.
- Modality (+25 / -40): multimodal support is a hard requirement when marked critical — text-only models drop out entirely.
- Context length (+25 / -20): the 2M-token king (Gemini 2.5 Pro) and the 10M-token Llama Scout earn extra weight when you say your inputs are very long.
- Tool-use (+20 / -30): essential for agent workflows. Models without first-class function-calling are filtered out when you mark tool-use required.
- Compliance (+25 / -35): EU hosting is a hard constraint for many DACH/EU teams. Models without an in-region option drop out, period.
Final score = sum of all eight weights. Models with non-positive scores are excluded; the top three are returned. Tie-breaking is deterministic on score, then on the order of the catalogue — running the quiz with the same answers always returns the same three picks.
The 30 models in the quiz
We picked the 30 most production-relevant AI models across every major category. The full catalogue of 130+ models is browsable at /models; the quiz subset is what we'd actually recommend to a customer in 2026:
Frontier text & multimodal
- Claude Opus 4.5
- Claude Sonnet 4.5
- GPT-5
- Gemini 2.5 Pro
- Grok 4
- o1 (Reasoning)
Fast & cheap workhorses
- Claude Haiku 4.5
- GPT-5 Mini
- GPT-5 Nano
- Gemini 2.5 Flash
- Gemini 2.5 Flash-Lite
- Grok Code Fast 1
Open-weight champions
- DeepSeek V3.2
- DeepSeek R1
- Llama 4 Maverick
- Llama 4 Scout
- Qwen 3 Coder
- Mistral Small 3.2
European / EU-hostable
- Mistral Large 2.1
- Mistral Small 3.2
- Flux 1.1 Pro Ultra
- DeepSeek V3.2
Image / video / audio
- Imagen 4 Ultra
- Flux 1.1 Pro Ultra
- SDXL Lightning
- Veo 3
- Sora 2
- ElevenLabs v3
- Whisper Large v3 Turbo
Embeddings & robotics
- Voyage 3 Large
- Text Embedding 3 Large
- π0 (Physical Intelligence)
- OpenVLA 7B
Frequently asked questions
How does the AI Model Quiz pick my top 3 models?
We score every model in our catalogue against your eight answers. Use case is the dominant signal — picking 'Coding' over 'Image generation' immediately filters to the right category. Latency, output quality tier, cost per million tokens, multimodal support, context window length, tool-use availability and EU hosting then act as tie-breakers. Models that fail a hard requirement (wrong category, blown latency budget, no EU region) are removed before the final ranking, then the three highest-scoring survivors are surfaced.
Which AI models are included in the quiz?
Around 30 production-relevant models: Claude Opus 4.5, Sonnet 4.5 and Haiku 4.5; GPT-5, GPT-5 Mini, GPT-5 Nano and o1; Gemini 2.5 Pro, Flash and Flash-Lite; Grok 4 and Grok Code Fast; DeepSeek V3.2 and R1; Mistral Large 2.1 and Small 3.2; Llama 4 Maverick and Scout; Qwen 3 Coder; Imagen 4 Ultra, Flux 1.1 Pro Ultra, SDXL Lightning; Veo 3 and Sora 2; ElevenLabs v3 and Whisper Large v3 Turbo; Voyage 3 Large and OpenAI text-embedding-3-large; plus π0 and OpenVLA for robotics. The full ranking table is available at /rankings.
Is there a single 'best' AI model in 2026?
No, and anyone telling you otherwise is selling something. The 'best' model depends on your latency budget (a 3-second reasoner is useless for IDE completion), your cost ceiling (frontier models cost 30-50x open-weights for marginal quality gains on most workloads) and your compliance posture (EU customer data restricts you to providers with in-region hosting). The quiz exists because the 'best' question only has a meaningful answer once you've specified those constraints.
Can I share my quiz result?
Yes — your answers are encoded into the page URL automatically (look for the `?q=...` parameter). Anyone who opens that link sees the exact same three recommendations without having to retake the quiz. There's also a 'Copy share link' button on the result screen.
Do I need to sign up to use the quiz?
No. The quiz runs entirely client-side — no account, no email, no tracking pixel. Once you have a recommendation you can click straight through to the model's spec sheet on Railwail, and only sign up if you decide to use the unified API.
How accurate is the recommendation?
The matrix is hand-curated by our team and updated whenever a major model launches, prices change, or benchmark scores shift. That said, the quiz is a starting point — it gets you to the right 2-3 candidates from a pool of 130+. The final decision should always involve a head-to-head test on your actual prompts. Use the comparison matrix at /compare or the cost calculator at /tools/llm-cost-calculator to drill deeper.
Why does the quiz penalise some models for missing latency?
Latency is a hard constraint for interactive workloads. If you select 'Critical (sub-200ms)' a chain-of-thought reasoner with an 8-second response time isn't just suboptimal — it's actively unusable. We apply a heavy negative score so those models drop out of the ranking entirely rather than landing at #3 with a misleading bullet list of their strengths.
What if no model matches my requirements?
Then your constraints are over-specified. The most common conflict is 'state-of-the-art quality + sub-$1 per 1M tokens + EU hosting' — that's a triangle where you can pick any two. The quiz tells you straight if there's no match; the fix is to relax one constraint, usually budget or hosting region, and re-run.
One API for every model in the quiz
After the quiz picks your three, swap any one in with a single line of code. Railwail is OpenAI-compatible and routes to all 130+ models — switch without rewriting your SDK or retry logic.