AI Model Database — Search, Compare & Explore Models
Comprehensive AI model database with GPT, Claude, Gemini, DeepSeek specs. Filter by provider, price, context window, and capabilities. Real-time pricing data.
Features
- ✓Search AI models by name, provider, or capability with instant results
- ✓Real-time pricing data synced from official sources (updated regularly)
- ✓Advanced multi-dimensional filtering system (provider, price tier, context window, capabilities)
- ✓Compare up to 5 models side-by-side with detailed specifications
- ✓Free AI models for learning, prototyping, and personal projects
- ✓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
- ✓Provider statistics: see how many models each provider offers and their price ranges
How to Use
- 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).
- 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').
- 3Apply filters from the filter panel to narrow down results:
- 4 • Provider: Select one or more companies (OpenAI, Anthropic, Google, Meta, DeepSeek, etc.) from available options
- 5 • Price Tier: Choose Free, Budget (<$2/M), Mid-range ($2-$15/M), or Premium (>$15/M)
- 6 • Context Window: Set minimum context size (128K, 200K, 500K, 1M+ tokens) for your use case
- 7 • Capabilities: Check boxes for Vision (image input), Tools (function calling), or Caching (prompt cache support)
- 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.
- 9Use the 'Compare' checkbox on multiple models (up to 5) to open the comparison view — see them side-by-side across all specifications.
- 10Switch between Table view (detailed data) using the view toggle if available.
- 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?
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Model data is synced from official sources every 6 hours, ensuring you have access to the latest pricing, new models, and updated specifications.
Where does this data come from?
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All model information is sourced from official provider APIs and aggregated in real-time. We compile data from 50+ providers including OpenAI, Anthropic, Google, Meta, DeepSeek, Qwen, Mistral, and many more.
Are the prices shown accurate?
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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.
What does 'Context Length' mean?
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Context length is the maximum number of tokens a model can process in a single request. Larger contexts allow processing longer documents, more conversation history, or larger codebases. For example, 200K context means ~150,000 words of text at once.
How do I choose the right model for my use case?
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Consider these factors: (1) Task complexity — simple tasks need less powerful models, (2) Budget — free/budget 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?
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'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?
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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?
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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?
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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?
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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?
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Prices are synced from official provider APIs and updated regularly. While we strive for accuracy, prices can change at any time at the provider's discretion. Always verify pricing on the provider's official website before making budget decisions. The tool shows the most recent data available at the time of synchronization.