Data · best for
Best AI model for CSV / Spreadsheet Cleanup (2026)
Normalizing messy tabular data with consistent fields. Ranked from 346 live models on the OpenRouter catalog, weighted for structured output, context window, low cost.
| # | Model | Score | In / 1M | Out / 1M | Context | |
|---|---|---|---|---|---|---|
| 1 | Auto Routeropenrouter/auto | 200134 | $-1000000.00 | $-1000000.00 | 2,000,000 | Try → |
| 2 | Pareto Code Routeropenrouter/pareto-code | 200114 | $-1000000.00 | $-1000000.00 | 200,000 | Try → |
| 3 | Body Builder (beta)openrouter/bodybuilder | 200111 | $-1000000.00 | $-1000000.00 | 128,000 | Try → |
| 4 | Qwen: Qwen3.5-Flashqwen/qwen3.5-flash-02-23 | 134 | $0.07 | $0.26 | 1,000,000 | Try → |
| 5 | OpenAI: GPT-5 Nanoopenai/gpt-5-nano | 134 | $0.05 | $0.40 | 400,000 | Try → |
| 6 | Google: Gemini 2.0 Flash Litegoogle/gemini-2.0-flash-lite-001 | 134 | $0.07 | $0.30 | 1,048,576 | Try → |
| 7 | OpenAI: GPT-5.4 Nanoopenai/gpt-5.4-nano | 133 | $0.20 | $1.25 | 400,000 | Try → |
| 8 | xAI: Grok 4.1 Fastx-ai/grok-4.1-fast | 133 | $0.20 | $0.50 | 2,000,000 | Try → |
| 9 | Google: Gemini 2.5 Flash Lite Preview 09-2025google/gemini-2.5-flash-lite-preview-09-2025 | 133 | $0.10 | $0.40 | 1,048,576 | Try → |
| 10 | xAI: Grok 4 Fastx-ai/grok-4-fast | 133 | $0.20 | $0.50 | 2,000,000 | Try → |
| 11 | Google: Gemini 2.5 Flash Litegoogle/gemini-2.5-flash-lite | 133 | $0.10 | $0.40 | 1,048,576 | Try → |
| 12 | OpenAI: GPT-4.1 Nanoopenai/gpt-4.1-nano | 133 | $0.10 | $0.40 | 1,047,576 | Try → |
| 13 | Google: Gemini 2.0 Flashgoogle/gemini-2.0-flash-001 | 133 | $0.10 | $0.40 | 1,048,576 | Try → |
| 14 | Qwen: Qwen3.6 Plusqwen/qwen3.6-plus | 133 | $0.33 | $1.95 | 1,000,000 | Try → |
| 15 | Google: Gemini 3.1 Flash Lite Previewgoogle/gemini-3.1-flash-lite-preview | 133 | $0.25 | $1.50 | 1,048,576 | Try → |
How we ranked these
For CSV / Spreadsheet Cleanup, we weight models on structured output, context window, low cost. Higher means better. Scores combine OpenRouter's model metadata (context length, modality support, tool calling, structured output, reasoning capability) with public pricing. See full methodology →
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