Best LLM for data analysis — SQL, spreadsheets, charts
Data analysis is part language, part exactness. The best LLM for it is one that writes runnable SQL/Python, respects schemas, and does not invent column names. Crowd chat Elo only loosely tracks that.
Prefer models with strong quality index as a prior, then test on a real schema. Long context helps when you paste CSV samples; tool use helps when the model must call a warehouse. Compare context and price so you are not stuffing 80MB CSVs into a flagship.
Highest quality index right now
Live OpenRouter pricing and Arena quality, cached about an hour. Not a static blog table.
| Model | Provider | Blend $ / 1M | Quality | Context |
|---|---|---|---|---|
| Qwen3.8 Max (0902) | Qwen | 4.00 | 95.1 | 1,000,000 |
| Claude Opus 5 | Anthropic | 15.00 | 93.4 | 1,000,000 |
| Claude Fable 5 | Anthropic | 30.00 | 91.1 | 1,000,000 |
| GLM 5.3 Flash | Z.ai | 0.16 | 89.7 | 1,048,576 |
| Qwen3.8 27B | Qwen | 1.71 | 89.0 | 1,000,000 |
Schema honesty
The failure mode that matters is hallucinated fields. Give the model a schema dump and ask three questions you know. If it invents a column, it is not your analyst, no matter how high its Elo. Reasoning SKUs sometimes reduce this; they also increase latency.
CSV-in-prompt vs warehouse tools
Pasting tables burns input tokens and hits context limits. For recurring analysis, a small model plus a SQL tool is cheaper than a 1M-context flagship. Use long-context models for one-off exploration of messy exports.
Python notebooks
If the output is code the user runs, you want a coding-capable model (see the coding guide). If the output is a narrative on already-computed numbers, a writing-oriented model is enough.
Privacy
Customer data in prompts is a procurement issue. Open-weight self-host or a VPC-hosted API may beat any public leaderboard winner. This site still helps you pick which weight to host by showing which rows the market prices as high quality.
Shortlist method
Leaderboard with quality 0.6 and context 0.4. Take three models. Run the same SQL-generation prompt in the arena. Keep the cheapest one that produces valid SQL on your schema twice in a row.
FAQ
Can LLMs replace analysts?
- They draft queries and explanations. They still invent numbers if you let them. Keep a compute layer that actually runs the query.
Is GPT or Claude better for SQL?
- Measure on your schema. Quality index is a weak SQL benchmark.
Do I need a huge context window?
- Only if you paste big tables. Tool-using agents can use tiny windows.
What about multimodal chart reading?
- See the multimodal and cheapest-vision guides; text Elo will not rank OCR.
Related guides
Also try: LLM leaderboard, compare tool, live arena.