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RREF Calculator

Pick a matrix size, enter the entries, and the calculator returns the reduced row echelon form. For augmented matrices it reads the solution (unique, none, or infinite) from RREF.

Matrix size

The augmented sizes 2x3 and 3x4 treat the last column as the right-hand side of a linear system.

Matrix entries

Reduced row echelon form

Reading

x = 5, y = 3, z = -2

Unique solution from the rightmost column of RREF.

Row 11 0 0 5
Row 20 1 0 3
Row 30 0 1 -2

Gauss-Jordan elimination drives each pivot to 1 and zeros out the rest of its column. The resulting form is unique for any matrix.

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Examples

3x4 system: x + y + z = 6; 2y + 5z = -4; 2x + 5y - z = 27

x = 5, y = 3, z = -2

2x3 system: x + 2y = 5; 3x + 4y = 11

x = 1, y = 2

3x3 identity check

rank 3

Augmented with a zero row that doesn't match

no solution

How it works

Gauss-Jordan elimination picks the largest absolute pivot in the current column, scales the pivot row so the pivot is 1, then subtracts multiples of that row from every other row to clear the column. The process repeats column by column.

Scale · divide pivot row by its pivot value

Eliminate · row_k -= (row_k[c] / pivot) × row_pivot

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Frequently asked questions

Reduced row echelon form is the unique simplest form of a matrix produced by row operations. In RREF, every pivot is 1, every pivot column has zeros elsewhere, and the pivots step down and to the right.

Rank counts the number of pivot rows in RREF. For a coefficient matrix, rank equals the number of independent equations. For an augmented system, comparing the rank of the coefficient matrix to the rank of the augmented matrix tells you whether the system is consistent.

Use 2x3 (for two equations in x and y) or 3x4 (for three equations in x, y, z). Enter each equation as one row: the coefficients of the variables in the left columns, and the right-hand side in the last column. The calculator reads the solution from RREF.

No solution: a row in RREF reads 0 = nonzero, which is impossible. Infinite solutions: the system has at least one free variable (a column without a pivot), so any value for that variable extends to a valid solution.

Reduced row echelon form is uniquely determined by the original matrix. Two different RREFs would imply contradictory pivot positions. This is what makes RREF useful for answering questions about a matrix at a glance.

Row echelon form (REF) only requires zeros below the pivots and a staircase shape. RREF goes further: pivots are exactly 1, and pivot columns have zeros above the pivot as well. Every matrix has a unique RREF.