GRE® → GMAT® Score Converter
Enter your GRE® Verbal and Quant scores to see the equivalent GMAT® Focus Edition total. Based on ETS and GMAC concordance data.
How this works:This converter chains ETS's GRE→GMAT Classic comparison tool with GMAC's Classic→Focus concordance tables. The result is an estimate — no official GRE→GMAT Focus conversion exists. Use it for setting target scores, not for admissions decisions.
Have a GMAT® Focus score instead? See its GRE® equivalent
How This Converter Works
Is this conversion official?
No. ETS (the GRE maker) has not released a direct GRE→GMAT Focus comparison tool. GMAC (the GMAT maker) has stated that no such table can exist due to differences between the tests. This converter chains two separate concordance tables — ETS's original GRE→GMAT Classic tool (now archived) and GMAC's Classic→Focus concordance — to produce an estimate. Treat it as ±10-15 points.
Why does my GRE total map to a specific GMAT score?
The converter uses your GRE Verbal + Quant total to look up the corresponding GMAT Focus total at the same percentile. Two different GRE combinations that add up to the same total (e.g., 162V/160Q and 160V/162Q) will map to the same GMAT estimate. In reality, the section-level breakdown matters — schools may weight Quant more heavily for certain programs.
Should I take the GRE or the GMAT?
Nearly all top MBA programs accept both. If you already have a GRE score, this converter helps you understand where you'd land on the GMAT Focus scale — useful if you're considering retaking or switching tests. The GRE can be advantageous if you're also applying to non-MBA graduate programs, or if your Verbal skills are significantly stronger than your Quant. Take a free practice test for each to compare your starting percentiles.
What about section-level conversions?
ETS originally provided Verbal-to-Verbal and Quant-to-Quant conversion tables, but those mapped to the old GMAT 0-60 section scale, not the current 60-90 Focus Edition scale. We chose to offer only the total-score conversion to avoid compounding estimation errors across multiple chained tables.