AI infrastructure & agent explorers
AI Model Compatibility Explorer
Which LLMs take images, audio or files, fit your context and support tools or structured outputs?
Try an example: Vision + tools + structured outputs, ≥128k context (OpenRouter snapshot 2026-10-14)
How it works
Filters and compares hundreds of language models by input modalities (image, audio, file, video), output modality, context window, maximum output tokens and API features such as tools, tool_choice, structured_outputs, response_format and reasoning, using OpenRouter's public models API (or a pasted copy of it). Shows matching models with prices, near misses with what they lack, and recommendations.
- Live mode reads GET https://openrouter.ai/api/v1/models (public, no key). Fields used: architecture.input_modalities/output_modalities, context_length, top_provider.max_completion_tokens, supported_parameters and pricing (USD per token, shown per 1M tokens).
- A model matches when it has every required input modality, the required output modality, at least the minimum context and output tokens, and every required API parameter listed in supported_parameters.
- Near misses are models (matching the name filter) that lack exactly one requirement.
- Recommendations: cheapest by input price, largest context and broadest feature set among the matches. Prices are for the routed provider listed by OpenRouter, not necessarily the vendor's own API.
For scripts and AI agents
- JSON API:
POST https://aimodelcompatibilityexplorer.usefulweb.site/api/v1/calculate(same calculation as this page) - Interface description: OpenAPI 3.1 · AI guide: llms.txt
- MCP server (Streamable HTTP):
https://aimodelcompatibilityexplorer.usefulweb.site/mcp· tool nameai_model_compatibility_explorer
Example request
curl -s -X POST https://aimodelcompatibilityexplorer.usefulweb.site/api/v1/calculate \
-H 'content-type: application/json' \
-d '{…see OpenAPI examples…}'Related tools
- LLM Cost Explorer – Monthly LLM API cost per model for your workload, with prompt-caching and batch savings.
- Structured Output Validator – Validate AI JSON output against a JSON Schema: parse errors with line/column, plain-language fixes.
- Model Behavior Regression Explorer – Compare eval results of two model versions: accuracy, regressions, McNemar p-value, flaky items.