---
title: "Model catalog API: capabilities and prices at runtime"
description: "Discover available models and their capabilities at runtime via /api/models/catalog."
source: https://lazu.ai/docs/models/catalog
updated: 2026-10-02
---

# Model catalog

Lazu publishes the full set of models a given API key can access. Read this
catalog at runtime instead of hardcoding model names — new models get added,
old ones get deprecated, and which models a key can reach depends on the
key's scope.

## GET `/api/models/catalog`

```bash
curl https://api.lazu.ai/api/models/catalog \
  -H "Authorization: Bearer $LAZU_API_KEY"
```

Response (abridged):

```json
{
  "object": "list",
  "data": [
    {
      "id": "gpt-6-luna",
      "object": "model",
      "name": "gpt-6-luna",
      "provider": "openai",
      "owned_by": "openai",
      "modality": {
        "input": ["text", "image"],
        "output": ["text"]
      },
      "capabilities": {
        "supports_function_calling": true,
        "supports_parallel_function_calling": true,
        "supports_vision": true,
        "supports_reasoning": false,
        "supports_response_schema": true,
        "supports_prompt_caching": true
      },
      "supported_endpoint_types": ["openai", "openai-response"],
      "supported_endpoints": [
        { "type": "openai", "path": "/v1/chat/completions", "method": "POST" },
        { "type": "openai-response", "path": "/v1/responses", "method": "POST" }
      ],
      "default_endpoint_type": "openai",
      "context_length": 128000,
      "max_output_tokens": 16384,
      "pricing": {
        "currency": "USD",
        "billing_type": "per_token",
        "input": 0.15,
        "output": 0.6,
        "cache_read": 0.075,
        "pricing_version": 3
      },
      "usage_capabilities": {
        "reported_dimensions": [
          "input",
          "output",
          "cache_read",
          "cache_write",
          "cache_write_5m",
          "cache_write_1h"
        ],
        "billable_dimensions": [
          "input",
          "output",
          "cache_read",
          "cache_write_5m"
        ],
        "response_fields": {
          "openai_compatible": [
            "usage.prompt_tokens_details.cached_tokens",
            "usage.prompt_tokens_details.cache_write_tokens",
            "usage.prompt_tokens_details.cache_write_5m_tokens"
          ],
          "request_detail": [
            "usage.dimensions",
            "billing.line_items"
          ]
        }
      },
      "supported_parameters": [
        "tools",
        "tool_choice",
        "response_format",
        "cache_control"
      ],
      "parameters": {
        "model": { "type": "string", "required": true },
        "messages": { "type": "array", "required": true },
        "temperature": { "type": "float", "default": 1, "range": [0, 2] },
        "max_tokens": { "type": "integer", "default": 1024 },
        "stream": { "type": "boolean", "default": false }
      },
      "example": {
        "curl": "curl https://api.lazu.ai/v1/chat/completions ..."
      }
    },
    "..."
  ]
}
```

## Picking a model

| You want             | Filter on                                         | Common endpoint                           |
| -------------------- | ------------------------------------------------- | ----------------------------------------- |
| Text chat            | `modality.output` includes `text`                 | `/v1/chat/completions`                    |
| Multimodal (vision)  | `modality.input` includes `image`                 | `/v1/chat/completions` or `/v1/responses` |
| Reasoning (o-series) | `capabilities.supports_reasoning === true`        | `/v1/responses` (recommended)             |
| Embeddings           | `supported_endpoint_types` includes `embeddings`  | `/v1/embeddings`                          |
| Tool / function call | `capabilities.supports_function_calling === true` | `/v1/chat/completions`                    |

Use `default_endpoint_type` unless your client SDK specifically needs a
native provider endpoint (Anthropic's `/v1/messages`, Gemini's
`/v1beta/models/…:generateContent`, etc.).

## Usage and cache metadata

Each model includes `usage_capabilities` so production clients can discover
which usage dimensions may appear before sending traffic. This matters for
prompt caching because providers do not use one shared field set.

| Dimension        | Meaning                                                                                                                                                                                          |
| ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `cache_read`     | Cached input tokens read from an existing cache entry. In OpenAI-compatible responses this appears as `usage.prompt_tokens_details.cached_tokens` or `usage.input_tokens_details.cached_tokens`. |
| `cache_write`    | Cache creation/write tokens when the provider reports a total but not a TTL bucket.                                                                                                              |
| `cache_write_5m` | Cache creation/write tokens for a 5-minute TTL bucket.                                                                                                                                           |
| `cache_write_1h` | Cache creation/write tokens for a 1-hour TTL bucket.                                                                                                                                             |
| `cache_miss`     | Cache misses reported separately by the provider, for example DeepSeek `prompt_cache_miss_tokens`.                                                                                               |

Provider notes:

- OpenAI-compatible cache reads use `cached_tokens`; OpenAI chat responses do
  not expose a separate cache-write token count.
- Anthropic reports cache reads and cache creation, including 5-minute and
  1-hour buckets when available.
- Gemini reports cached content reads through `cachedContentTokenCount`.
- Qwen/DashScope may report `cached_tokens` and cache creation fields,
  including Anthropic-compatible cache field names on some routes.
- DeepSeek reports `prompt_cache_hit_tokens` and
  `prompt_cache_miss_tokens`; Lazu normalizes hits to `cache_read` and misses
  to `cache_miss`.

Use `reported_dimensions` to decide which fields may appear, and
`billable_dimensions` to decide which dimensions can affect price for the
current catalog price context.

## Listing via `/v1/models`

If your SDK uses OpenAI-style `models.list()`, Lazu also serves a flatter
OpenAI-compatible response at `/v1/models`:

```bash
curl https://api.lazu.ai/v1/models \
  -H "Authorization: Bearer $LAZU_API_KEY"
```

See [Models list](https://lazu.ai/docs/endpoints/models) for the exact schema.

## Pricing detail

Each catalog entry has a `pricing` object for the current API key's effective
catalog price. See [Pricing & lanes](https://lazu.ai/docs/models/pricing) for how routing lane
preferences affect the price returned for a key.