Is deepseek-v3.2-max good at Data & Analytics?
deepseek-v3.2-max ranks #44 of 69 for Data & Analytics — excellent. The top pick for this task is claude-opus-4.8-low.
deepseek-v3.2-max on each Data & Analytics sub-task
| Spot the Misleading Stat | 100.0/100 | #24 |
| SQL Reasoning | 99.8/100 | #45 |
| Metric Calculation | 95.5/100 | #41 |
| Honest Communication | 76.0/100 | #67 |
Real examples, graded
WeakSessions vs visitors denominator (Cedar & Sage) 64/100
“The model correctly calculates the session conversion rate as 2% and shows the formula. However, it fails the core conceptual test of the prompt: recognizing that 'conversion rate' is ambiguous when both sessions and unique visitors are provided. It ignores the visitor conversion rate (2.86%) and does not discuss why the denominator basis matters.”
WeakCorrelation vs causation (Northwind) 99/100
“The model perfectly answers the prompt. It correctly identifies that the report's conclusion is flawed because it treats correlation as causation. It provides excellent examples of confounding variables and correctly states that a controlled comparison is needed to prove a causal relationship.”
Frequently asked
Is deepseek-v3.2-max good at Data & Analytics?
deepseek-v3.2-max ranks #44 of 69 models we tested for Data & Analytics, scoring excellent.
What is deepseek-v3.2-max's strongest Data & Analytics skill?
Its best sub-task here is Spot the Misleading Stat.
This page is Spring Prompt, running
We just did this for every model. Do it for your prompt.
The rankings above come from running real tasks through real models and scoring every output. Spring Prompt is that same engine — pointed at your prompt, your test cases, and your definition of good.
- Generate test cases from your prompt — no eval set required to start.
- Compare models side by side with quality, cost and latency in one matrix.
- Optimise the winner until the scores say it's ready to ship.
Prompt × model results
12 test cases · 3 evals