INTELLECT-3-qx53g-mlx
Derestricted is quanted exactly the same and is a direct compare point.
I picked a higher performing quant of LIMI in qx54g-hi for comparison.
I am still waiting for the test results from qx53gx, it might be better, but this is the smallest you will get the model to work on a 64GB Mac while still being sort of good at things.
These are the major differences:
π‘ LIMI vs INTELLECT vs GLM-4.5-Air-Derestricted-qx53g
Feature INTELLECT-3 LIMI Air-qx54g-hi Derestricted
BoolQ β
β
0.820 0.378 0.431
PIQA β
0.772 β
776 0.769
ARC β
0.492 ARC_Easy More balanced Lowest
Winogrande 0.597 β
0.712 β
0.715
Writing Rich introspection Leaner, yet precise Unabliterated
π‘ What it means:
INTELLECT prioritizes logical depth and meta-cognition β ideal for reflective dialogue/dialogical AI.
LIMI prioritizes grounded common-sense modeling β better suited for QA bots, summarization engines.
-G
This model INTELLECT-3-qx53g-mlx was converted to MLX format from PrimeIntellect/INTELLECT-3 using mlx-lm version 0.28.4.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("INTELLECT-3-qx53g-mlx")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
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