supra-1.5-50m-instruct-exp-fp16-mlx

MLX quantization of SupraLabs/Supra-1.5-50M-Instruct-exp for Apple Silicon.

Variant: BFloat16 (lossless reference)
Disk size: 101 MB
Quantized by: sahilchachra

Benchmark results

Evaluated on Apple M4 Pro with MLX. Model loaded once; performance and quality measured in a single pass.

Performance

	This model	FP16 baseline
Decode tok/s (avg, long traces)	1025.59	1025.59
Peak memory (GB)	0.223	0.223
Disk size (MB)	101	101

Quality

Benchmark	This model	FP16 baseline	n
IFEval (instruction following)	15.9%	15.9%	44
Alpaca-cleaned (instruct F1 vs reference)	40.9	40.9	50

Context scaling (decode tok/s)

Context length	Decode tok/s
~128 tokens	1057.2
~256 tokens	1026.0
~512 tokens	1021.4
~1024 tokens	997.7

Usage

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("sahilchachra/supra-1.5-50m-instruct-exp-fp16-mlx")
response = generate(model, tokenizer, prompt="Your prompt here", max_tokens=256, verbose=True)

All variants in this collection

Model	Variant
sahilchachra/supra-1.5-50m-instruct-exp-mxfp4-mlx	Block float MX FP4
sahilchachra/supra-1.5-50m-instruct-exp-mxfp8-mlx	Block float MX FP8

Notes

• Requires Apple Silicon (M1 or later) with MLX
• Benchmarks run on Apple M4 Pro, 24 GB unified memory
• License: see SupraLabs/Supra-1.5-50M-Instruct-exp for the original model's license

Original model

See SupraLabs/Supra-1.5-50M-Instruct-exp for full model details and intended use.