Skill

or-compare-models

Use when the user wants to compare two or more OpenRouter models head-to-head. Triggers on phrases like "compare <model-a> and <model-b> on OpenRouter", "head-to-head OR comparison", "which is better — <model-a> or <model-b>", "side-by-side OpenRouter models", "diff these OR models".

npx claudepluginhub danielrosehill/claude-open-router-model-research-plugin

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How this skill is triggered — by the user, by Claude, or both

Slash command

/open-router-model-research:or-compare-models

User invocable

Model invocable

Inline context

Default effort

Context Preview

The summary Claude sees in its skill listing — used to decide when to auto-load this skill

Build a structured side-by-side comparison of two or more OpenRouter models so the user can choose between them.

SKILL.md

68 lines · ~688 tokens

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Last CommitApr 16, 2026

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Head-to-Head OpenRouter Model Comparison

Build a structured side-by-side comparison of two or more OpenRouter models so the user can choose between them.

When to use

The user has named 2+ specific OpenRouter models (or asked to compare picks from a previous recommendation) and wants a structured comparison.

Workflow

Step 1: Identify the models

If the user named the models, take their IDs as-is. If they referenced them indirectly ("compare the two cheapest tool-calling models"), first run the relevant filter (via or-find-tool-models) and pick the targets.

If a model ID is ambiguous or not found in the catalog, ask for clarification before proceeding.

Step 2: Fetch catalog data

curl -s https://openrouter.ai/api/v1/models -H "Accept: application/json"

Extract each target model's record.

Step 3: Build the comparison table

Render a markdown table with one column per model and one row per dimension. Recommended rows:

Dimension	Model A	Model B
Provider
Context length
Max output tokens
Input modalities
Output modalities
Prompt $/1M tokens
Completion $/1M tokens
Image $/each (if vision)
Tool use support	yes/no	yes/no
Structured outputs	yes/no	yes/no
Tokenizer
Created (date)
Top provider context
Per-request limits

Step 4: Add a written summary

Below the table, write a 3–5 sentence summary highlighting:

Where the models meaningfully differ (price ratio, context ratio, capability gaps)
What each is better suited for, based on the differences
A clear "if X matters most, pick A; if Y matters most, pick B" verdict

Step 5: Offer to deepen the analysis

End with: "Want me to research either of these models beyond the OR catalog (model card, benchmarks, license)?" — route to or-evaluate-model if yes.

Notes

Don't bring in benchmark scores or qualitative judgments from memory. Stick to catalog facts in the table. Save subjective comparisons for the summary, and clearly mark them as your interpretation.
If comparing more than 3 models, the table gets unwieldy — suggest grouping into pairs or running a recommendation flow instead.
If two models are nearly identical (same family, e.g. gpt-4o vs gpt-4o-2024-08-06), say so explicitly and explain what differs (typically date / pricing tier).