SirSahOl/stablelm-2-1_6b-chat-mlx-16bit

stablelm-2-1_6b-mlx-16bit

16-bit MLX conversion of stabilityai/stablelm-2-1_6b for Apple Silicon.

Converted by: SirSahOl Source model: stabilityai/stablelm-2-1_6b Framework: MLX by Apple Quantization: 16-bit Format: safetensors License: other

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Quick Start

Installation

pip install mlx-lm

CLI Usage

# Chat interactively
mlx_lm.chat --model SirSahOl/stablelm-2-1_6b-chat-mlx-16bit

# Generate text
mlx_lm.generate --model SirSahOl/stablelm-2-1_6b-chat-mlx-16bit --prompt "Your prompt here"

Python Usage

from mlx_lm import load, generate

model, tokenizer = load("SirSahOl/stablelm-2-1_6b-chat-mlx-16bit")
response = generate(model, tokenizer, prompt="Your prompt here", max_tokens=256)
print(response)

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Performance Benchmarks

| Metric | 4-bit | 8-bit | 16-bit | |--------|--------|--------|--------|| Tokens/sec | 47.84 | 29.85 | 16.53 | | TTFT | 20.9 ms | 33.52 ms | 60.49 ms | | Peak Memory | 915.6 MB | 40.4 MB | 43.9 MB |

Benchmarked on Apple M1 with 8GB unified memory. Average over 5 runs with 256 max tokens.

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Who Should Use This?

Your Hardware	Recommended Quantization
M1/M2 (8GB)	4-bit — Best balance of quality and memory usage
M1/M2 Pro/Max (16-32GB)	8-bit — Higher quality with reasonable memory
M2/M3/M4 Ultra (64GB+)	16-bit — Full precision, no quality loss

General guidance:

• Use 4-bit if you want to run this model alongside other applications
• Use 8-bit if you have the memory and want better quality
• Use 16-bit for research, evaluation, or if memory isn't a concern

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Other Quantization Variants

Variant	Link
4-bit	SirSahOl/stablelm-2-1_6b-chat-mlx-4bit
8-bit	SirSahOl/stablelm-2-1_6b-chat-mlx-8bit
16-bit	SirSahOl/stablelm-2-1_6b-chat-mlx-16bit

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Conversion Details

Property	Value
Source Model	stabilityai/stablelm-2-1_6b
Quantization	16-bit
mlx-lm Version	0.31.3
Conversion Time	11.43s
Output Size	3.1 GB
Date	2026-09-10T22:51:53.477974+00:00

Reproduction

To reproduce this conversion:

pip install mlx-lm==0.31.3
python3 -m mlx_lm.convert --hf-path stabilityai/stablelm-2-1_6b --mlx-path output/stablelm-2-1_6b-mlx-16bit

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Limitations & Known Issues

• Performance may degrade with very long contexts (>8K tokens) at lower quantization levels.
• This is a weight-only conversion; the model architecture and behavior are inherited from the source model.
• Quantization introduces a small quality loss compared to the original model. Lower bit counts = more loss.
• This model requires Apple Silicon (M1 or later) to run with MLX.

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License

This model conversion inherits the license of the source model: other.

See the original model card for full license details.

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Changelog

Version	Date	Changes
v1.0	2026-09-10	Initial conversion

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Converted with MLX Foundry — a professional pipeline for converting models to Apple MLX format.