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UFOZoo

AI Model Database: Search, Compare & Explore Models

AI model database online: search and compare AI models by provider, context length, and price tier, with filtering, specs, and use-case suggestions.

Updated 2026-09-14

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Features

  • Search AI models by name, provider, or capability with instant results
  • Up-to-date pricing data compiled from official model cards (snapshot dated 2026-09-11)
  • Advanced multi-dimensional filtering system (provider, price tier, context window, capabilities)
  • Compare up to 5 models side-by-side with detailed specifications
  • Filter by leading providers: OpenAI, Anthropic, Google, Meta, DeepSeek, Qwen, Mistral, and more
  • Price tier categorization: Free, Budget (<$2/M), Mid ($2-$15/M), Premium (>$15/M)
  • Context window filtering: from 128K to 1M+ tokens for long document processing
  • Capability filters: Vision (multimodal), Tools (function calling), Prompt Caching support
  • Detailed model specifications: architecture, tokenizer, input/output modalities
  • Pricing breakdown with cache discounts (cached input at 90% off standard price)
  • Sortable table view with columns for name, provider, pricing, context length, and capabilities
  • Model cards showing key metrics: input/output price per 1M tokens, context window size

How to Use

  1. 1Open the AI Model Database tool: you'll see all available models listed in a searchable table with key information (name, provider, pricing, context length).
  2. 2Use the search bar at the top to find specific models by name (e.g., 'GPT', 'Claude', 'DeepSeek'), provider ('OpenAI', 'Anthropic'), or capability ('vision', 'free', 'coding').
  3. 3Apply filters from the filter panel to narrow down results:
  4. 4 • Provider: Select one or more companies (OpenAI, Anthropic, Google, Meta, DeepSeek, etc.) from available options
  5. 5 • Price Tier: Choose Free, Budget (<$2/M), Mid-range ($2-$15/M), or Premium (>$15/M)
  6. 6 • Context Window: Set minimum context size (128K, 200K, 500K, 1M+ tokens) for your use case
  7. 7 • Capabilities: Check boxes for Vision (image input), Tools (function calling), or Caching (prompt cache support)
  8. 8Click on any model row to expand and see full details including description, complete pricing breakdown (input/output/cached costs), architecture info, and capability list.
  9. 9Use the 'Compare' checkbox on multiple models (up to 5) to open the comparison view; see them side-by-side across all specifications.
  10. 10Switch between Table view (detailed data) using the view toggle if available.
  11. 11For quick access to popular models, use the provider badges or price tier tags to jump to filtered lists.

Frequently Asked Questions

How often is the model data updated?

Model data is compiled from official model cards and pricing pages; the current snapshot was taken on 2026-09-11. This is a static database: it refreshes when the site is rebuilt with a new snapshot, not on a fixed sync schedule.

Where does this data come from?

All model information is compiled from official provider model cards and pricing pages (OpenAI, Anthropic, Google, Meta, DeepSeek, Qwen, Mistral, and many more). The snapshot was taken on 2026-09-11, so treat the listed prices as a point-in-time record and confirm current rates on the provider's site.

Are the prices shown accurate?

Yes! Prices are displayed exactly as provided by model providers; these are current market rates with no markup. Note that actual costs may vary slightly depending on usage patterns and caching efficiency.

How do I choose the right model for my use case?

Consider these factors: (1) Task complexity: simple tasks need less powerful models, (2) Budget: low-cost models for testing, premium for production, (3) Latency: smaller models are faster, (4) Special needs: vision for images, tools for function calling, large context for long documents.

What's the difference between Input and Output pricing?

'Input' refers to tokens you send TO the model (your prompt, messages, documents). 'Output' refers to tokens the model generates IN RESPONSE (its replies, code, text). Output is typically 3-5x more expensive than input.

Why do some models show 'Cached' pricing?

Prompt Caching allows reusing previously processed content at much lower cost (typically 90% off). If your application sends similar prompts repeatedly (fixed system prompt, few-shot examples, knowledge base), caching can dramatically reduce costs.

Which providers offer free models?

Free models are available from providers including OpenAI (gpt-oss-120b-free), Meta (Llama series), Qwen (free versions), Google (some Gemini Flash variants), and several open-source model hosts.

How do I filter models by specific capabilities?

Use the Capabilities filter panel. Check 'Vision' for models that can process images, 'Tools' for function calling support, and 'Caching' for prompt caching discounts. You can combine multiple filters; for example, find vision-capable models under $15/M with at least 128K context for a document analysis project.

What does 'Context Length' mean in practice?

Context length is the maximum tokens a model can process in one request. 128K context fits roughly 96,000 words (about a novel). 200K fits ~150,000 words. 1M+ fits entire codebases or very long documents. Larger context costs more per token but handles more data without needing to split requests.

How are model prices updated and how reliable are they?

Prices are compiled from official provider model cards, and the current snapshot is dated 2026-09-11. Prices can change at any time at the provider's discretion, so always verify current pricing on the provider's official website before making budget decisions; the tool shows the most recent snapshot we have.

Why do model prices change so often?

AI providers reprice frequently; API price cuts and new tiers have been common as the market matures, sometimes several times a year per provider. This database is a static snapshot (currently dated 2026-09-11), so the listed price can be days or weeks behind a provider's latest announcement. For billing-critical decisions, confirm the current price on the provider's pricing page; the database is best used for relative cost comparisons between models.

Why is my model missing from the database?

The database is a static snapshot (currently dated 2026-09-11), so a model released after that date will not appear until the snapshot is refreshed. Some models are also listed under different names than you remember; search a partial name like 'GPT' or 'Claude' to find the exact ID. Models that are not exposed through public APIs (invite-only or enterprise-contract models) are not included at all.

Why can't I find voice models or vector databases in this tool?

This database tracks text and chat LLM API pricing for the OpenAI/Anthropic/Google/DeepSeek/Qwen class of models. Voice and TTS models, embedding/vector databases, and image generation models are separate product categories with different pricing units (per minute, per vector, per image), so they are deliberately out of scope here. For those, check the provider's own catalog or a category-specific directory.