I made WinterGoliath and it felt a bit off compared to regular Goliath. I was wondering if left bias was really present in the models after that so I made an automatic benchmark using politiscales test.

Interpreting the data

b0/b1 : Internationalism/Nationalism
c0/c1 : Constructivism/Essentialism
e0/e1 : Ecology/Production
j0/j1 : Rehabilitative Justice/Punitive Justice
m0/m1 : Regulation/Laissez-faire
p0/p1 : Communism/Capitalism
s0/s1 : Progressive/Conservative
t0/t1 : Revolution/Reform
reli : Religiousness
comp : Belief in a worldwide conspiracy
prag : Pragmatism
mona : Monarchism
vega : VEGAN
anar : Anarchism
femi: : Radical feminism

Suggestions for calculations

Whackiness of the model=anar+comp+mona+reli
Certainty=(x0+x1), calculate average of all values
Bias towards value(logratio)=LOG(x0/x1;2)
Left-right bias=b_logratio+c_logratio+e_logratio+j_logratio+m_logratio+p_logratio+s_logratio-t_logratio

Results

Mixtral-instruct0.1 hates violence(-3.1 logratio_t!!!), religion(0.4%), pragmatic politics(1.4%), monarchy(0.6%), anarchy(5.7%) and conspiracy theories(0.2%); likes regulation(1.5 logratio_t), globalism(1.4) and ecology(0.64). The MOST vegan(72%!!!) model tested so far. EXTREME left-wing bias.
LLAMA2-70b is fairly neutral, with slight bias to the left.
Dicephal-123(self-merge of llama2-70B) is also fairly neutral, with slight bias to the right. Sadly, it is the most right-wing model that I tested.
Xwin, Goliath, Nous-Hermes have low left-wing bias.
DoubleGold and WinterGoliath have medium left-wing bias.
WinterGoddess and Euryale have high left-wing bias.

My suspicions were correct, WinterGoliath has stronger left wing bias than Goliath and is less whacky, I cannot consider it an upgrade, just a sidegrade.

Limitations

The tests were done without any special prompting. How models perform on the test does not reflect how they perform with the right prompting, it just shows the bias of the model.

This test does NOT measure censorship.