Build explore and query the OpenRouter model catalog programmatically. Use when selecting models or checking availability. Trigger with phrases like 'openrouter models', 'list openrouter models', 'openrouter model catalog', 'available models openrouter'.
npxskills add jeremylongshore/claude-code-plugins-plus-skills--skill openrouter-model-catalogLoading…
Query the GET /api/v1/models endpoint to browse 400+ models, filter by capabilities, compare pricing, and check provider endpoints. No API key required for the models endpoint.
curl and jq for the command-line catalog queries — GET /api/v1/models itself requires no authOPENROUTER_API_KEY only for the Special Routers completion example — see the openrouter-install-auth skill for setuprequests for filtering, plus the OpenAI SDK for the openrouter/auto example (pip install requests openai)curl -s https://openrouter.ai/api/v1/models | jq '.data | length'; add ?supported_parameters=tools to filter to tool-calling models.pricing.prompt/pricing.completion are per token (multiply by 1M for readable rates), plus context_length, top_provider.max_completion_tokens, and architecture.modality.GET /api/v1/models/{id}/endpoints per List Providers for a Model.:free, :nitro, :floor, :extended, :thinking), or delegate selection entirely to openrouter/auto per Special Routers./api/v1/models — prices change frequently.# Full catalog (no auth required)
curl -s https://openrouter.ai/api/v1/models | jq '.data | length'
# → 400+
# Filter to text output models only
curl -s "https://openrouter.ai/api/v1/models?supported_parameters=tools" | jq '.data | length'
{
"id": "anthropic/claude-3.5-sonnet",
"name": "Claude 3.5 Sonnet",
"description": "Anthropic's most intelligent model...",
"context_length": 200000,
"pricing": {
"prompt": "0.000003",
"completion": "0.000015",
"image": "0.0048",
"request": "0"
},
"top_provider": {
"context_length": 200000,
"max_completion_tokens": 8192,
"is_moderated": false
},
"per_request_limits": null,
"architecture": {
"modality": "text+image->text",
"tokenizer": "Claude",
"instruct_type": null
}
}
Key fields:
pricing.prompt / pricing.completion -- cost per token (not per million; multiply by 1M for readable rates)context_length -- max input tokenstop_provider.max_completion_tokens -- max output tokensarchitecture.modality -- text->text, text+image->text, etc.import requests
models = requests.get("https://openrouter.ai/api/v1/models").json()["data"]
# Find all free models
free_models = [m for m in models if m["pricing"]["prompt"] == "0"]
print(f"Free models: {len(free_models)}")
# Models with tool calling support
# (query with supported_parameters)
tool_models = requests.get(
"https://openrouter.ai/api/v1/models?supported_parameters=tools"
).json()["data"]
print(f"Tool-calling models: {len(tool_models)}")
# Sort by prompt price (cheapest first, excluding free)
paid = [m for m in models if float(m["pricing"]["prompt"]) > 0]
paid.sort(key=lambda m: float(m["pricing"]["prompt"]))
for m in paid[:10]:
cost_per_m = float(m["pricing"]["prompt"]) * 1_000_000
print(f" ${cost_per_m:.2f}/M tokens — {m['id']} ({m['context_length']//1000}K ctx)")
# Filter by context length (128K+)
large_ctx = [m for m in models if m["context_length"] >= 128_000]
print(f"128K+ context models: {len(large_ctx)}")
# See all providers and their pricing for a specific model
curl -s "https://openrouter.ai/api/v1/models/anthropic/claude-3.5-sonnet/endpoints" | jq '.data[] | {
provider: .provider_name,
price_prompt: .pricing.prompt,
price_completion: .pricing.completion,
context_length: .context_length,
quantization: .quantization
}'
Append a suffix to any model ID for variant behavior:
| Suffix | Effect | Example |
|---|---|---|
:free | Free tier (where available) | google/gemma-2-9b-it:free |
:nitro | Sort providers by throughput (faster) | anthropic/claude-3.5-sonnet:nitro |
:floor | Sort providers by price (cheapest) | openai/gpt-4o:floor |
:extended | Extended context window | anthropic/claude-3.5-sonnet:extended |
:thinking | Enable extended reasoning | anthropic/claude-3.5-sonnet:thinking |
| Model ID | Behavior |
|---|---|
openrouter/auto | Auto-selects best model for your prompt (powered by NotDiamond) |
openrouter/free | Routes to free models only |
# Let OpenRouter pick the best model
response = client.chat.completions.create(
model="openrouter/auto",
messages=[{"role": "user", "content": "Write a SQL query to find duplicate emails"}],
max_tokens=200,
)
print(f"Auto-selected: {response.model}") # Shows which model was chosen
| Model ID | Context | Cost (prompt/completion per 1M) |
|---|---|---|
google/gemma-2-9b-it:free | 8K | Free |
meta-llama/llama-3.1-8b-instruct | 128K | ~$0.06 / $0.06 |
anthropic/claude-3-haiku | 200K | $0.25 / $1.25 |
openai/gpt-4o-mini | 128K | $0.15 / $0.60 |
anthropic/claude-3.5-sonnet | 200K | $3.00 / $15.00 |
openai/gpt-4o | 128K | $2.50 / $10.00 |
openai/o1 | 200K | $15.00 / $60.00 |
Prices change frequently. Always verify via /api/v1/models.
id, context_length, pricing, top_provider, and architecture fields$0.06/M tokens — meta-llama/llama-3.1-8b-instruct (128K ctx)provider_name, prompt/completion pricing, context_length, quantizationopenrouter/auto requests, response.model reveals which model the router actually selectedFetch the catalog once, then slice it three ways with the filters from Python: Query and Filter:
models = requests.get("https://openrouter.ai/api/v1/models").json()["data"]
free = [m for m in models if m["pricing"]["prompt"] == "0"]
large = [m for m in models if m["context_length"] >= 128_000]
print(f"Total: {len(models)}, free: {len(free)}, 128K+: {len(large)}")
# Total: 267, free: 12, 128K+: 45 (counts drift as the catalog changes)
The same pass sorted by prompt price surfaces the cheapest paid options — meta-llama/llama-3-8b-instruct: $0.05/1M prompt tokens leads the list in the worked run. More worked examples: references/examples.md.
| Issue | Cause | Fix |
|---|---|---|
| Model ID not found at request time | Model renamed, removed, or typo | Re-query /api/v1/models; use exact ID from catalog |
| Stale pricing | Cached catalog data outdated | Refresh catalog hourly; pricing updates dynamically |
| Empty results with filter | No models match the filter criteria | Broaden the filter; check parameter spelling |
/api/v1/models for deprecation notices and new model additionssupported_parameters query filter to ensure models support features you need (tools, JSON mode, etc.)
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.