Openrouter Model Availability

---
name: openrouter-model-availability
description: 'Monitor OpenRouter model availability and implement health checks. Use
  when building systems that depend on specific models being online. Triggers: ''openrouter
  model status'', ''is model available'', ''openrouter health check'', ''model availability''.

  '
allowed-tools: Read, Write, Edit, Grep, Bash(python3:*), Bash(curl:*), Bash(jq:*)
version: 1.20.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- openrouter
- monitoring
- availability
compatibility: Designed for Claude Code
---
# OpenRouter Model Availability

## Overview

OpenRouter's `/api/v1/models` endpoint is the source of truth for model availability. Models can be temporarily unavailable, have degraded performance, or be permanently removed. This skill covers querying model status, building health probes, tracking availability over time, and automating failover.

## Prerequisites

- An OpenRouter API key exported as `OPENROUTER_API_KEY` for live probes (the catalog query itself needs no auth) — see the `openrouter-install-auth` skill for setup
- `curl` and `jq` for the catalog status queries and the cron monitoring script
- Python 3.8+ with the OpenAI SDK and `requests` (`pip install openai requests`) for the health-check service
- A small credit balance — each `max_tokens: 1` probe costs roughly $0.0001

## Instructions

1. Confirm your models exist in the catalog with `curl -s https://openrouter.ai/api/v1/models | jq ...` per Query Model Status — pull `context_length` and per-million pricing without spending any tokens.
2. For a zero-cost existence check inside code, use `check_model_exists()` from Catalog-Based Availability Check; on a miss it calls `find_similar()` to suggest same-provider replacements.
3. Probe live health with `probe_model()` from Health Check Service — a `max_tokens: 1` request that returns a `HealthStatus` with `available`, `latency_ms`, and `checked_at`.
4. Sweep your critical set with `check_critical_models()`, which logs `OK`/`FAIL` plus latency per model.
5. Automate via the Availability Monitoring Script as a `*/5 * * * *` cron job appending timestamped status lines to `/var/log/openrouter-health.log`.
6. Tune alerting per Error Handling — require 2-3 consecutive failures before marking a model down to avoid false positives.

## Query Model Status

```bash
# Check if specific models exist and their status
curl -s https://openrouter.ai/api/v1/models | jq '[.data[] | select(
  .id == "anthropic/claude-3.5-sonnet" or
  .id == "openai/gpt-4o" or
  .id == "openai/gpt-4o-mini"
) | {
  id,
  context_length,
  prompt_per_M: ((.pricing.prompt | tonumber) * 1000000),
  completion_per_M: ((.pricing.completion | tonumber) * 1000000)
}]'

# List all available models (just IDs)
curl -s https://openrouter.ai/api/v1/models | jq '[.data[].id] | sort'

# Count models by provider
curl -s https://openrouter.ai/api/v1/models | jq '[.data[].id | split("/")[0]] | group_by(.) | map({provider: .[0], count: length}) | sort_by(-.count)'
```

## Health Check Service

```python
import os, time, logging
from datetime import datetime, timezone
from dataclasses import dataclass
import requests
from openai import OpenAI, APIError, APITimeoutError

log = logging.getLogger("openrouter.health")

@dataclass
class HealthStatus:
    model: str
    available: bool
    latency_ms: float
    checked_at: str
    error: str = ""

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key=os.environ["OPENROUTER_API_KEY"],
    timeout=15.0,
    default_headers={"HTTP-Referer": "https://my-app.com", "X-Title": "health-check"},
)

def probe_model(model_id: str) -> HealthStatus:
    """Send a minimal request to test model availability."""
    start = time.monotonic()
    try:
        response = client.chat.completions.create(
            model=model_id,
            messages=[{"role": "user", "content": "hi"}],
            max_tokens=1,  # Minimal cost
        )
        latency = (time.monotonic() - start) * 1000
        return HealthStatus(
            model=model_id, available=True, latency_ms=round(latency, 1),
            checked_at=datetime.now(timezone.utc).isoformat(),
        )
    except (APIError, APITimeoutError) as e:
        latency = (time.monotonic() - start) * 1000
        return HealthStatus(
            model=model_id, available=False, latency_ms=round(latency, 1),
            checked_at=datetime.now(timezone.utc).isoformat(),
            error=str(e),
        )

def check_critical_models() -> list[HealthStatus]:
    """Probe all critical models."""
    CRITICAL_MODELS = [
        "anthropic/claude-3.5-sonnet",
        "openai/gpt-4o",
        "openai/gpt-4o-mini",
        "google/gemini-2.0-flash-001",
    ]
    results = []
    for model in CRITICAL_MODELS:
        status = probe_model(model)
        log.info(f"{'OK' if status.available else 'FAIL'} {model} ({status.latency_ms}ms)")
        results.append(status)
    return results
```

## Catalog-Based Availability Check

```python
def check_model_exists(model_id: str) -> dict:
    """Check if a model exists in the catalog (no API call cost)."""
    resp = requests.get("https://openrouter.ai/api/v1/models")
    models = {m["id"]: m for m in resp.json()["data"]}

    if model_id in models:
        m = models[model_id]
        return {
            "exists": True,
            "context_length": m["context_length"],
            "pricing": m["pricing"],
        }
    return {"exists": False, "suggestion": find_similar(model_id, models)}

def find_similar(model_id: str, models: dict) -> list[str]:
    """Find models with similar names (for migration when model is removed)."""
    prefix = model_id.split("/")[0]
    return [m for m in models if m.startswith(prefix)][:5]
```

## Availability Monitoring Script

```bash
#!/bin/bash
# Run as cron job: */5 * * * * /path/to/check_models.sh

MODELS=("anthropic/claude-3.5-sonnet" "openai/gpt-4o" "openai/gpt-4o-mini")
LOG_FILE="/var/log/openrouter-health.log"

for MODEL in "${MODELS[@]}"; do
  START=$(date +%s%N)
  HTTP_CODE=$(curl -s -o /dev/null -w "%{http_code}" \
    https://openrouter.ai/api/v1/chat/completions \
    -H "Authorization: Bearer $OPENROUTER_API_KEY" \
    -H "Content-Type: application/json" \
    -d "{\"model\":\"$MODEL\",\"messages\":[{\"role\":\"user\",\"content\":\"ping\"}],\"max_tokens\":1}" \
    --max-time 15)
  END=$(date +%s%N)
  LATENCY=$(( (END - START) / 1000000 ))

  STATUS="OK"
  [ "$HTTP_CODE" != "200" ] && STATUS="FAIL"

  echo "$(date -u +%Y-%m-%dT%H:%M:%SZ) $STATUS $MODEL $HTTP_CODE ${LATENCY}ms" >> "$LOG_FILE"
done
```

## Output

- `HealthStatus` records per probed model: `available`, `latency_ms`, an ISO-8601 `checked_at` timestamp, and the error string when a model is down
- Catalog check dicts: `{"exists": True, "context_length": ..., "pricing": ...}` on a hit, or `{"exists": False, "suggestion": [...]}` listing similar model IDs on a miss
- Append-only log lines from the cron script, e.g. `2026-07-02T14:05:01Z OK anthropic/claude-3.5-sonnet 200 842ms`, one per critical model every 5 minutes

## Examples

Check that a critical model is still in the catalog before spending tokens on a probe:

```bash
curl -s https://openrouter.ai/api/v1/models | jq '[.data[] | select(
  .id == "anthropic/claude-3.5-sonnet") | {id, context_length}]'
# [{"id": "anthropic/claude-3.5-sonnet", "context_length": 200000}]
```

Then run the Python health sweep — `run_health_checks()` in `references/examples.md` prints `[OK] anthropic/claude-3.5-sonnet: 842.3ms` per model, a `3/3 models healthy` summary, and the mapped fallback (e.g. `openai/gpt-4-turbo`) for any failure. More worked examples: `references/examples.md`.

## Error Handling

| Error | Cause | Fix |
|-------|-------|-----|
| Model not in catalog | Model renamed or removed | Use `find_similar()` to find replacement |
| Health check timeout (>15s) | Model overloaded or cold-starting | Distinguish slow vs down; increase timeout for probes |
| False positive down | Transient network issue | Require 2-3 consecutive failures before alerting |
| 402 on health check | Credits exhausted | Health checks cost ~$0.0001 each; ensure adequate credits |

## Enterprise Considerations

- Health probes cost tokens ($0.0001 or less per probe with `max_tokens: 1`) -- budget for monitoring
- Require 2-3 consecutive failures before marking a model as down to avoid false positives
- Cache the models list and refresh every 5 minutes -- don't hit `/api/v1/models` on every request
- Subscribe to OpenRouter announcements for model deprecations and new additions
- Maintain a model alias map so your code uses logical names (e.g., "primary-chat") that you can remap
- Alert when critical models disappear from the catalog, not just when they fail probes

## References

- Examples | Errors
- [Models API](https://openrouter.ai/docs/api/api-reference/models/get-models) | [Status](https://status.openrouter.ai)