Instructions to use inferencerlabs/Kimi-K2.6-MLX-3.6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use inferencerlabs/Kimi-K2.6-MLX-3.6bit with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("inferencerlabs/Kimi-K2.6-MLX-3.6bit") config = load_config("inferencerlabs/Kimi-K2.6-MLX-3.6bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
NOTICE
This model has been superseded by the higher quality Q3.5-INF version available here
INFORMATION
See Kimi-K2.6 MLX in action - demonstration video
Tested on a M3 Ultra 512GB RAM using Inferencer app
- Single inference ~24.04 tokens/s @ 1000 tokens (debug build)
- Vision inference ~20.55 (available from v1.11.0)
- Memory usage: ~437 GiB
Q3.6 typically achieves useable accuracy in our coding test and fits within a 512GB memory budget
| Quantization (bpw) | Perplexity | Token Accuracy | Missed Divergence | Size |
|---|---|---|---|---|
| Q3.5 | 1.1328125 | 94.92% | 42.71% | 450.19 GB |
| Q3.5-INF | 1.078125 | 96.67% | 22.04% | 455.68 GB |
| Q3.6 | 1.1484375 | 94.72% | 48.72% | 470.99 GB |
| Base | Untested | 100% | 0.000% | 658.59 GB |
- Perplexity: Measures the confidence for predicting base tokens (lower is better)
- Token Accuracy: The percentage of correctly generated base tokens
- Missed Divergence: Measures severity of misses; how much the token was missed by
Quantized with a modified version of MLX
For more details see demonstration video or visit Kimi-K2.6.
Disclaimer
We are not the creator, originator, or owner of any model listed. Each model is created and provided by third parties. Models may not always be accurate or contextually appropriate. You are responsible for verifying the information before making important decisions. We are not liable for any damages, losses, or issues arising from its use, including data loss or inaccuracies in AI-generated content.
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Model tree for inferencerlabs/Kimi-K2.6-MLX-3.6bit
Base model
moonshotai/Kimi-K2.6