Hint: such matrices with even determinant have determinant zero in $\Bbb F_2$, whereas the ones with odd determinants have determinant 1 in $\Bbb F_2$ and hence are invertible. The question amounts to asking what the size of $GL(4,\Bbb F_2)$ is.
Assume that $A\in M_{nk,nk}$. Then let $(P_n)$ be the sequences of matrices defined as follows: $P_1=J_n,P_2={J_n}^2-I,P_q=J_nP_{q-1}-P_{q-2}$.
Then $\det(A)=\det(P_k)$.
EDIT. The eigenvalues of $J_n$ are the $(1+2\cos(\pi \dfrac{p}{n+1})),p=1\cdots n$; thus, if $Q$ is any polynomial, then we can calculate approximations of the eigenvalues of $Q(J_n)$, and then, an approximation of $\det(A)$. When we have enough significant digits, we deduce the true result -because this one is an integer-. Finally, we do not need to calculate any product of matrices. That follows calculates -using Maple- $\det(A)$ when $n=k=100$ (duration of the calculation: $1$"). First step. You choose Digits:=30. You see that the result has $1076$ digits. Second step. You choose Digits:=1150 and that works (see the sequence of zeros (or eventually of $9$) that appears at the end of the development of the obtained decimal number).
restart; with(LinearAlgebra):
k := 100; n := 100; d := time(); B := Matrix(n, n); for i to n do B[i, i] := 1 end do; for i to n-1 do B[i, i+1] := 1; B[i+1, i] := 1 end do;
z := CharacteristicPolynomial(B, x); u := x; v := x^2-1; for i from 3 to k do w := v; v := rem(vx-u, z, x); u := w end do; Digits := 1150;
Q := unapply(v, x); r := 1; for i to n do r := evalf(rQ(1+2*cos(i*Pi/(n+1)))) end do; print(r); time()-d;
$2.44387846087090290145607732170537391377490420405227812708050615\\
28277319341932844677382952399933460059814926416716644013099963\\
42708968356667589737763656457680692376518632271970928028188495\\
28837548232087652163820090152818313133799717624970641029956038\\
21298982012250961831581518578716473316074214193004344884914447\\
80091522565037919891219503197811771573350002012798682732589728\\
91073456252754229360553614557394171698663316722024355474750138\\
99058808405660398400447542745412413310559180910765198835081950\\
16753460456828320406836683930343030087726159407318434195928328\\
91168720495008933297278988838511004283717390785348840943983494\\
94573265138514209244141811048121198105502888315873129747553394\\
28745956498781145738030840450505861505489488623215771119102138\\
24860932438498432031584839888927118146735452787049842756602723\\
13071431049603803135820994521439844817046772204723218141987299\\
65625418270767015593634878034477052797174424114584736827230518\\
99846006803088990947026408309411889789175194098825709435984858\\
82242334251648224773936990898407542151092941240200527201190067\\ 27465966535881736354100000000000000000000000000000000143203220\\
133487059755244617410791395080\times 10^{1075}$
Best Answer
We could go from the determinant of one window to the determinant of the next using a rank-1 update and the matrix determinant lemma.
Let $v_1,v_2,\dots,v_{64}$ denote the columns of the first window $B_1$, and let $v_{65}$ denote the first column of $A$ outside the window $B$. We note that $$ \det B_2 = \det \pmatrix{v_2 & v_3 & \cdots & v_{64} & v_{65}} = \\ (-1)^{64 - 1} \det \pmatrix{v_{65} & v_2 & v_3 & \cdots & v_{64}} = \\ (-1)^{64 - 1} \det \left[\pmatrix{v_{65} - v_1 & 0&0& \cdots & 0} + \pmatrix{v_{1} & v_2 & v_3 & \cdots & v_{64}}\right] = \\ - \det[(v_{65} - v_1)e_1^T + B_1], $$ where $e_1^T = (1 \ \ 0 \ \ \cdots \ \ 0)$. By the matrix determinant lemma, this means that $$ \det(B_2) = -(1 + e_1^TB_1^{-1}(v_{65} - v_1)) \det(B_1). $$
We might be able to make things more efficient still if, instead of computing $B_k^{-1}(v_{k+m} - v_k)$ or $e_1^TB_k^{-1}$ directly each time, we use a rank-1 update formula for this as well. Let $P$ denote the permutation matrix $$ P = \pmatrix{&&&1\\1\\&\ddots\\&&1}. $$ We find that $$ B_{k+1} = [(v_{k+m} - v_k)e_1^T + B_k]P \implies B_{k+1}^{-1} = P^T[B_k + (v_{k+m} - v_k)e_1^T]^{-1}. $$ By the Sherman Morrison formula, we have $$ [B_k + (v_{k+m} - v_k)e_1^T]^{-1} = B_k^{-1} - \frac{B_k^{-1}(v_{k+m} - v_k)e_1^TB_k^{-1}}{1 + e_1^TB_k^{-1}(v_{k+m} - v_k)}. $$