Kimi K2.6 Eagle3 Mla Alternatives

kimi-k2.6-eagle3-mla is an open-source speculative-decoding draft model designed for use with Kimi-K2.6. It features Multi-Head Latent Attention and is compatible with vLLM, enabling faster and more efficient language model inference for AI researchers and developers.

An Eagle3 MTP (Multi-Token Prediction) draft model trained to accelerate inference of the Kimi-K2.5 language model using speculative decoding. It was trained with the TorchSpec framework and is designed to work in tandem with the target model to improve generation speed. The model and training data are available on Hugging Face.

Kimi-K2.5 is a community port of the Kimi model optimized for the MLX framework, allowing efficient inference on Apple devices. The model supports advanced features including multimodal inputs (text, image, video), tool calling, and custom chat templates. It is distributed on Hugging Face and can be used with both pip and npm tooling for local deployment.

Kimi-K2.6 is an open-source large language model available on Hugging Face, designed for local text generation and research. It supports Python and Docker deployment, enabling developers and researchers to run advanced language models on their own infrastructure.

Kimi-K2.5-NVFP4 is an open-weight multimodal foundation model published by NVIDIA on Hugging Face. It supports text, image, video, and tool-calling capabilities through a custom chat template. The model is designed for local inference and developer integration via the Hugging Face ecosystem and Transformers library.

Kimi-K2.7-Code-NVFP4 is an NVIDIA-provided, precision-optimized version of the Kimi code model. It supports multimodal inputs including code, text, images, and video for advanced coding assistance. The model is hosted on Hugging Face for local and cloud inference by software developers.

Kimi-K2.7-Code-NVFP4 is a specialized, quantized version of the Kimi model series optimized for code-related tasks. It uses the NVFP4 format for efficient inference while maintaining strong performance on programming, debugging, and software engineering benchmarks. The model is distributed on Hugging Face and can be used with standard transformer or vLLM inference stacks.

Kimi K2.7-Code is an open-source AI model designed for efficient code generation and completion. It offers improved token efficiency and can be used via API or CLI, making it suitable for developers and researchers seeking customizable AI coding solutions.

GGUF quantized version of the Kimi K2.7 code model provided by Unsloth. It is designed for local execution using tools such as llama.cpp, Ollama, or LM Studio. The model supports code generation, completion, and instruction following in a variety of programming languages.