GPT-OSS-120B - TurboQuant MLX 2-bit
2-bit weight-quantized MLX version of openai/gpt-oss-120b with TurboQuant KV-cache quantization. Optimized for Apple Silicon inference via the MLX framework. The smallest variant, enabling GPT-OSS-120B to fit on more accessible Mac hardware; expect some quality degradation vs higher-bit variants. GPT-OSS-120B is OpenAI's flagship open-weights Mixture-of-Experts model (Apache 2.0), approaching o4-mini quality for reasoning tasks.
Approximate model size: ~30 GB
Model Specifications
| Property | Value |
|---|---|
| Base Model | openai/gpt-oss-120b |
| Parameters | 120 billion (MoE) |
| Architecture | Mixture-of-Experts (MoE) Transformer |
| License | Apache 2.0 (commercial use OK) |
| Weight Quantization | 2-bit (~30 GB) |
| KV-Cache Quantization | TurboQuant |
| Framework | MLX (Apple Silicon) |
Quickstart
from mlx_lm import load, generate
from turboquant import TurboQuantCache
model, tokenizer = load("majentik/gpt-oss-120b-TurboQuant-MLX-2bit")
prompt = "Explain the theory of relativity."
response = generate(model, tokenizer, prompt=prompt, max_tokens=512)
print(response)
What is TurboQuant?
TurboQuant (arXiv: 2504.19874) compresses the KV cache used during autoregressive generation. Combined with aggressive 2-bit weight quantization in MLX, this produces the smallest possible footprint for GPT-OSS-120B, making the flagship open model accessible on more modest Apple Silicon hardware.
KV-Cache Quantization Comparison
| Method | Prefill Speed | Decode Speed | Memory Savings | Reference |
|---|---|---|---|---|
| TurboQuant | 1x (baseline) | 1x (baseline) | High | arXiv: 2504.19874 |
| RotorQuant | 5.3x faster | 28% faster | High | GitHub |
Memory Estimates (GPT-OSS-120B)
| Precision | Approximate Size | MLX Variant |
|---|---|---|
| BF16 (original) | ~240 GB | -- |
| 8-bit quantized | ~120 GB | TurboQuant-MLX-8bit |
| 4-bit quantized | ~65 GB | TurboQuant-MLX-4bit |
| 2-bit quantized | ~30 GB | This model |
Hardware Requirements
This model requires approximately 30 GB of unified memory. Recommended hardware:
- Apple M1 Max (32 GB+)
- Apple M2 Max (32 GB+)
- Apple M3 Max (36 GB+)
- Apple M4 Max (36 GB+)
- Any Apple Silicon Mac with 36 GB+ unified memory
See Also
- openai/gpt-oss-120b -- Base model
- majentik/gpt-oss-120b-TurboQuant -- TurboQuant KV-cache only (transformers)
- majentik/gpt-oss-120b-TurboQuant-MLX-8bit -- MLX 8-bit variant
- majentik/gpt-oss-120b-TurboQuant-MLX-4bit -- MLX 4-bit variant
- majentik/gpt-oss-120b-RotorQuant-MLX-2bit -- RotorQuant MLX 2-bit variant
- TurboQuant Paper (arXiv: 2504.19874)
- MLX Framework
Quantized
Model tree for majentik/gpt-oss-120b-TurboQuant-MLX-2bit
Base model
openai/gpt-oss-120b