Agent skill · research science · replicate
compare-models
Compare Replicate models by cost, speed, quality, and capabilities.
Why this skill is useful
Provides specific methodologies for evaluating and comparing AI models based on cost, speed, quality, and capabilities that the AI wouldn't reliably generate on its own.
What it needs
Requires replicate account access. About 1k tokens when loaded. Last updated 2026-06-04. 53 stars on the source repository.
What this skill does
Docs Reference: <https://replicate.com/docs/llms.txt> OpenAPI schema: <https://api.replicate.com/openapi.json> MCP server: <https://mcp.replicate.com> Per-model docs: https://replicate.com/{owner}/{model}/llms.txt Set Accept: text/markdown when requesting docs pages for Markdown responses. Workflow 1. Search or browse collections to build a shortlist of candidate models. 2. Fetch each model's schema to compare inputs, outputs, and capabilities. 3. Check pricing from model metadata or the Replicate website. 4. Run a small batch of test predictions to compare output quality. 5. Pick the model that best fits your constraints (cost, latency, quality). What to compare Speed: Check metrics.predicttime on completed predictions for actual inference time. Official models are always warm. Community models can cold-boot. Cost: Official models have predictable per-run pricing. Community models charge by compute time (GPU-seconds). Run a few predictions and check the metrics field for actual cost. Quality: Run the same prompts through each model and compare outputs. Quality is subjective. Match it to your use case, not a leaderboard. Capabilities: Compare input schemas for supported features (reference images, masks, aspect ratios, streaming, multi-image input). Check output formats. Key tradeoffs Lowest cost: smaller/distilled models. Accept slower inference and lower quality. Lowest latency: official models or schnell/turbo variants. Accept higher cost per run. Highest quality: pro/max/quality variants. Accept slower inference and higher cost. Most control: models with ControlNet, masks, or reference images. Accept more complex input setup. Official vs community models Official models: always warm, stable APIs, predictable pricing, maintained by Replicate. Community models: may cold-boot, require version pinning, maintained by the author. If a community model meets your needs and an official model doesn't, consider creating a deployment for consistent uptime. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills replicate/compare-models