What is the best LLM for data analysis in 2026?
Interpreting data chains three moves: read a table correctly, apply the right statistic, and conclude without overreaching. The Data Analysis category of our independent benchmark tests exactly that chain.
The podium: top 3 models in data analysis
Undisputed category leader, OpenAI earns the spot with consistency across every subtask and a peak of tablereformat (100/100). Cost: $0.736/successful task, in the leader pack.
81,6 from OpenAI — 1,4 points behind the leader, strong on tablereformat (100/100), weaker on tablejoin (56/100). Cost: $0.436/successful task, in the leader pack.
80,5 from Anthropic — 2,4 points behind the leader, strong on tablereformat (94/100), weaker on tablejoin (56/100). Watch the price: $1.478/task, much more expensive than the leader for a lower score.
Full Data Analysis ranking — top 15
| # | Model | Org | Score | Cost/task |
|---|---|---|---|---|
| 1 | gpt-6-astra-max | OpenAI | 83,0 | $0.736 |
| 2 | gpt-5.5-xhigh | OpenAI | 81,6 | $0.436 |
| 3 | claude-fable-5-max-effort | Anthropic | 80,5 | $1.478 |
| 4 | claude-fable-5-1-max-effort | Anthropic | 80,3 | $1.212 |
| 5 | smaug-agentic | Other | 79,9 | $0.329 |
| 6 | gpt-5.6-sol-max | OpenAI | 79,8 | $0.507 |
| 7 | muse-spark-1.3-xhigh | Other | 79,6 | $0.219 |
| 8 | deepseek-v4-flash-vision-expopen | DeepSeek | 79,5 | $0.051 |
| 9 | deepseek-v4-flash-0731open | DeepSeek | 79,3 | $0.060 |
| 10 | gpt-5.4-xhigh | OpenAI | 79,3 | $0.387 |
| 11 | gpt-5.6-terra-max | OpenAI | 79,3 | $0.344 |
| 12 | deepseek-v4.1-flash-maxopen | DeepSeek | 79,3 | $0.029 |
| 13 | deepseek-v4-pro-0813open | DeepSeek | 79,2 | $0.044 |
| 14 | smaug-flash | Other | 79,1 | $0.014 |
| 15 | smaug-mini | Other | 78,8 | $0.099 |
Scores out of 100, release 2026-06-25. Cost = dollars per successful task (lower is better). 57 models ranked in this category. See the full benchmark →
💚 Best value: ox-alpha-max (Other)
At $0.0000 per successful task, ox-alpha-max reaches 75,8 score — 91% of the leader’s performance for 1% of its price. Free on this benchmark.
How we measure this category
Tasks combine tabular reading, basic statistics and inference from in-context data. Grading is automatic. The category often reveals a common flaw: strong abstract reasoners that fail simple operations once information is buried in a table.
tablejoin
tablereformat
BI, research, reporting: if your prompts contain data, this category matters more than the overall score.
How to read this ranking
This ranking covers 57 models evaluated on the same release, and the gap between first and last reaches 29,7 points — enough to separate professional workloads from casual use. The category median sits at 74,6: any model below that bar must compensate with price or specialization. We also see OpenAI dominating the top of the table (10 models in the top 11), a sign that this skill rewards precise architecture choices more than simply scaling the model. Finally, a category score is never an average of everything: a model that excels here can still be average elsewhere — the other six rankings exist for that.
What changed since the previous release
The current leader (gpt-6-astra-max, OpenAI) is a new entry in the ranking: it was not evaluated on release 2026-01-08. That signals a category in flux.
Our recommendation
Bottom line: for raw performance, gpt-6-astra-max (OpenAI) leads the category at 83,0/100 — a 3,1-point gap over 5th place (smaug-agentic), an edge that shows up in real deliverable quality on long tasks. On a tight budget, deepseek-v4-flash-vision-exp ($0.051) is the best score under $0.10/task (79,5/100). Finally, 16 of 57 models are open-weight: if data confidentiality is non-negotiable, self-hosting is a realistic path in this category. Always compare two axes — score and cost per successful task — that is where the choice is made.
Frequently asked questions
What is the best LLM for data analysis in 2026?
On our benchmark (release 2026-06-25), it is gpt-6-astra-max (OpenAI) with a score of 83,0/100, ahead of gpt-5.5-xhigh (81,6)..
What is a free or budget option for data analysis?
At $0.0000 per successful task, ox-alpha-max (Other) still scores 75,8 — the best performance per dollar in the category.
Is the gap between first and tenth noticeable in practice?
It is 3,7 points between gpt-6-astra-max (83,0) and 10th-place gpt-5.4-xhigh (79,3). On a single task the difference often goes unnoticed; across thousands of calls or long chains, those points become different success rates — and a different budget.
How is this ranking produced?
iatrust publishes independent benchmark scores with refreshed questions to avoid training-data contamination, and automatic grading. We add no subjective judgment to the scores; verdicts are computed from subtasks and measured costs. The page regenerates automatically on each new release.
Compare the 57 models across 23 tasks
Full ranking, expandable subtasks, cost per task, release history.