AI Tools
Match quality tier, open-weight preference, and price sensitivity to models in the /ai-models catalog — with links to profiles and comparisons.
Start questionsExplained methodology
Each tool and guide makes the decision criteria and fit logic visible.
Clear disclosure
Commercial relationships are disclosed so readers can judge with context.
Ongoing updates
Important guides and tools are reviewed as products and categories change.
Answer 4 short prompts to get a logic-based recommendation plus strong alternatives.
Current status
Question 1 of 4
State is saved locally, so refreshing keeps your progress intact.
Model APIs
Frontier models cost more per token. Routine volume work rarely needs the top tier.
Restoring your saved answers...
Available result profiles
Optional reference for the decision profiles this tool can return — answer the questions above first.
Your answers favor maximum capability for hard reasoning, coding, and agentic work — cost is secondary to getting the task done.
Best for: Hard multi-step reasoning, Agentic engineering workflows, Tasks where a failed run costs more than extra tokens
Watch out: Frontier input rates are often 10–25× budget tiers. Confirm the task truly needs frontier quality before defaulting to the flagship.
Shortlist examples: GPT-5.6 Sol, Claude Opus 5, Gemini 3.1 Pro
Your answers favor one capable middle tier for mixed coding, writing, and analysis — without always paying frontier rates.
Best for: Mixed engineering and knowledge work, Teams picking one default model, Production features that are not always frontier-hard
Watch out: Middle tiers still vary 5–10× in price. Open the comparison pages before standardising a team on one model.
Shortlist examples: GPT-5.6 Terra, Claude Sonnet 5, Grok 4.5
Your answers favor predictable per-token cost for classification, summarisation, and chat at scale.
Best for: High-volume chat and classification, Summarisation pipelines, Cost-sensitive prototypes at scale
Watch out: Budget models fail loudly on hard reasoning. Keep a frontier tier for escalation paths rather than forcing one cheap model everywhere.
Shortlist examples: GPT-5.6 Luna, Gemini 3.7 Flash, DeepSeek V4 Flash
This tool currently compares Frontier Reasoning, Balanced Daily Driver, Budget and High Volume decision paths.
Fit before features
Each recommendation starts with the buyer's situation, operating constraints, and decision risk before comparing feature lists.
Trade-offs are visible
Every result should explain who should choose it, who should skip it, and what would make a runner-up smarter.
Shortlists stay practical
The site favors shortlist clarity, setup reality, renewal risk, and owner capacity over inflated all-in-one claims.
Scoring inputs
The scoring model uses the question flow, weighted result profiles, shortlist trade-offs, and supporting editorial pages rather than a single generic ranking.
Limits to check
Pricing, availability, trial terms, and support commitments can change. Confirm current vendor terms before buying.
Logic review cadence: Reviewed when tool logic, category assumptions, or major vendor positioning changes.
Use these paths to decide whether your answers should favor speed, depth, control, or practical ownership.
Simple fit
Choose the option that solves the current problem with the least unnecessary complexity.
Growth fit
Prioritize headroom when the decision will support a larger team, budget, or workload soon.
Control fit
Favor stronger governance when compliance, ownership, or support risk matters more than speed.
The two finalists of each result profile in this tool, side by side.
This tool weighs catalog signals from lib/ai-models.ts:
Recommendations link to model profile pages where pricing and context are verified. Compare head-to-head in the AI library before standardising a team default.
No. It routes you to catalog profiles and comparisons where benchmarks are sourced and dated. The flow scores tier and price fit only.
Answer the open-weight question honestly — the open picks link to profiles and the open-weight hub. Use the local model fit finder for hardware to self-host.
Comparison
OpenAI’s August 2026 ChatGPT refresh changed the free tier more than the API. Here is how Free/Go vs Plus/Pro actually differ — and what still bills separately.
Read the side-by-side comparison to see where the trade-offs split and which type of buyer each option actually fits.
Comparison
Plus/Pro Chat got an August Sol refresh. Work and Codex did not automatically inherit it. Treat them as separate buying decisions.
Read the side-by-side comparison to see where the trade-offs split and which type of buyer each option actually fits.
Comparison
A workstation GPU and an hourly inference pod are both valid — but they fail in opposite directions when you guess instead of measuring concurrency, idle time, and ops overhead.
Read the side-by-side comparison to see where the trade-offs split and which type of buyer each option actually fits.
Buying guide
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Buying guide
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