/v1/ai/models
Models available for inference, with cost in cents per query and each model's published intelligence index (Artificial Analysis, reconciled against OpenRouter's benchmarks API)
Request
https://api.xrpl.to/v1/ai/modelscurl 'https://api.xrpl.to/v1/ai/models'
Response
https://api.xrpl.to/v1/ai/models{ "models": [ { "id": "z-ai/glm-5.3-flash", "provider": "openrouter", "cost_cents": 5, "intelligence_index": 41.9, "coding_index": 71.5, "agentic_index": 51.2, "reasoning": true, "context_window": 1310720 }, { "id": "z-ai/glm-5.3", "provider": "openrouter", "cost_cents": 15, "intelligence_index": 44.9, "coding_index": 74.8, "agentic_index": 53.4, "reasoning": true, "context_window": 1310720 }, { "id": "qwen/qwen3.8-max-0902", "provider": "openrouter", "cost_cents": 25, "intelligence_index": 53.4, "coding_index": 68.9, "agentic_index": 49.9, "reasoning": true, "context_window": 1000000 }, { "id": "moonshotai/kimi-k2.6", "provider": "openrouter", "cost_cents": 15, "intelligence_index": 27.5, "coding_index": 61.8, "agentic_index": 22.1, "reasoning": true, "context_window": 262144 }, { "id": "moonshotai/kimi-k3", "provider": "openrouter", "cost_cents": 25, "intelligence_index": 43.8, "coding_index": 76.2, "agentic_index": 50.6, "reasoning": true, "context_window": 1048576 } ], "packs": [ { "id": "mini", "name": "Mini", "usd": 2.5, "cents": 250 }, { "id": "starter", "name": "Starter", "usd": 5, "cents": 500 }, { "id": "standard", "name": "Standard", "usd": 20, "cents": 2000 }, { "id": "pro", "name": "Pro", "usd": 50, "cents": 5000 } ] }
Long arrays and strings are shortened in the example; Send request for the full answer.
What it does
Models available for inference, with cost in cents per query and each model's published intelligence index (Artificial Analysis, reconciled against OpenRouter's benchmarks API)