Openrouter Models

OpenRouter Models

Discover, search, and compare the 300+ AI models available on OpenRouter. Query live data including pricing, context lengths, per-provider latency and uptime, throughput, supported modalities, and supported parameters.

Prerequisites

The OPENROUTER_API_KEY environment variable is optional for most scripts. It is only required for get-endpoints.ts (provider performance data). Get a key at https://openrouter.ai/keys

First-Time Setup

cd <skill-path>/scripts && npm install

Decision Tree

Pick the right script based on what the user is asking:

Resolve Model

Resolve an informal or vague model name to an exact OpenRouter model ID using fuzzy matching:

cd <skill-path>/scripts && npx tsx resolve-model.ts "claude sonnet"
cd <skill-path>/scripts && npx tsx resolve-model.ts "gpt 4o mini"
cd <skill-path>/scripts && npx tsx resolve-model.ts "llama 3.1"

Results include a confidence level and score:

Two-step workflow: First resolve the informal name with resolve-model.ts, then feed the resolved id into other scripts (compare-models.ts, get-endpoints.ts, etc.).

List Models

cd <skill-path>/scripts && npx tsx list-models.ts

Filter by Category

Server-side category filtering:

cd <skill-path>/scripts && npx tsx list-models.ts --category programming

Categories: programming, roleplay, marketing, marketing/seo, technology, science, translation, legal, finance, health, trivia, academia

Sort Results

cd <skill-path>/scripts && npx tsx list-models.ts --sort newest      # Recently added first
cd <skill-path>/scripts && npx tsx list-models.ts --sort price       # Cheapest first
cd <skill-path>/scripts && npx tsx list-models.ts --sort context     # Largest context first
cd <skill-path>/scripts && npx tsx list-models.ts --sort throughput  # Most output tokens first

Models with upcoming expiration_date values trigger a stderr warning.

Search Models

cd <skill-path>/scripts && npx tsx search-models.ts "claude"
cd <skill-path>/scripts && npx tsx search-models.ts --modality image
cd <skill-path>/scripts && npx tsx search-models.ts "gpt" --modality text

Modalities: text, image, audio, file

Compare Models

Compare two or more models side-by-side with pricing in per-million-tokens format. Uses exact ID matching — openai/gpt-4o matches only that model, not variants like gpt-4o-mini.

cd <skill-path>/scripts && npx tsx compare-models.ts "anthropic/claude-sonnet-4" "openai/gpt-4o"
cd <skill-path>/scripts && npx tsx compare-models.ts "anthropic/claude-sonnet-4" "openai/gpt-4o" "google/gemini-2.5-pro" --sort price

Sort options: price (cheapest first), context (largest first), speed/throughput (most output tokens first)

Provider Performance (Endpoints)

Get per-provider latency, uptime, and throughput for any model:

cd <skill-path>/scripts && npx tsx get-endpoints.ts "anthropic/claude-sonnet-4"
cd <skill-path>/scripts && npx tsx get-endpoints.ts "anthropic/claude-sonnet-4" --sort throughput
cd <skill-path>/scripts && npx tsx get-endpoints.ts "openai/gpt-4o" --sort latency

Sort options: throughput (fastest tokens/sec first), latency (lowest p50 ms first), uptime (most reliable first), price (cheapest first)

Returns for each provider:

• Latency (p50/p75/p90/p99 in ms) — median to worst-case response times
• Throughput (p50/p75/p90/p99 tokens/sec) — generation speed
• Uptime — percentage over the last 30 minutes
• Status — operational or degraded
• Provider-specific pricing — some providers offer discounts
• Supported parameters — varies by provider (some don't support all features)

API Response Shapes

GET /api/v1/models returns { data: Model[] }. For full field reference, see the Models reference.

Query parameters (all optional):

Tips for working with the response:

• To check if a model supports a feature, use model.supported_parameters (e.g. .includes("tools")), or filter server-side with ?supported_parameters=tools.
• To check modalities, use model.architecture.input_modalities / model.architecture.output_modalities.
• Pricing values are per-token in USD as strings — multiply by 1,000,000 for per-million-token pricing.
• knowledge_cutoff and expiration_date are date strings or null.
• links.details points to the per-provider endpoints API for that model. GET /api/v1/models/{author}/{slug}/endpoints returns { data: { id, name, endpoints: Endpoint[] } }.
• Endpoint status: 0 = operational, non-zero = degraded.
• Endpoint latency_last_30m / throughput_last_30m: percentile objects with p50, p75, p90, p99.

Script Output Formats

The scripts below reformat the raw API data. When calling the API directly (e.g. via fetch), refer to the OpenAPI spec for field names.

list-models.ts / search-models.ts

A subset of the raw API fields — the scripts run formatModel() which drops canonical_slug, hugging_face_id, default_parameters, knowledge_cutoff, and links. If you need those fields, call the API directly.

compare-models.ts

{
  "id": "anthropic/claude-sonnet-4",
  "name": "Anthropic: Claude Sonnet 4",
  "context_length": 1000000,
  "max_completion_tokens": 64000,
  "per_request_limits": null,
  "pricing_per_million_tokens": {
    "prompt": "$3.00",
    "completion": "$15.00",
    "cached_input": "$0.30"
  },
  "modalities": { "input": ["text", "image"], "output": ["text"] },
  "supported_parameters": ["max_tokens", "temperature", "..."],
  "is_moderated": false
}

get-endpoints.ts

{
  "model_id": "anthropic/claude-sonnet-4",
  "model_name": "Anthropic: Claude Sonnet 4",
  "total_providers": 5,
  "endpoints": [
    {
      "provider": "Anthropic",
      "tag": "anthropic",
      "status": "operational",
      "uptime_30m": "100.00%",
      "latency_30m_ms": { "p50": 800, "p75": 1200, "p90": 2000, "p99": 5000 },
      "throughput_30m_tokens_per_sec": { "p50": 45, "p75": 55, "p90": 65, "p99": 90 },
      "context_length": 1000000,
      "max_completion_tokens": 64000,
      "pricing_per_million_tokens": { "prompt": "$3.00", "completion": "$15.00", "cached_input": "$0.30" },
      "supports_implicit_caching": true,
      "supported_parameters": ["max_tokens", "temperature", "tools", "..."]
    }
  ]
}

Key Fields

Presenting Results

• When a user mentions a model by informal name, use resolve-model.ts first, then feed the resolved id into other scripts
• Convert pricing to per-million-tokens format for readability
• When comparing, use a markdown table with models as columns
• For provider endpoints, highlight the fastest (lowest p50 latency) and most reliable (highest uptime) providers
• Call out notable supported parameters: tools, structured_outputs, reasoning, web_search_options
• Note cache pricing when available — it can cut input costs 90%+
• Flag models with expiration_date as deprecated
• When a model has multiple providers at different prices, mention the cheapest option