Kimi-K2.7-Code

About

What Kimi-K2.7-Code is

Model Overview Description: The NVIDIA Kimi-K2.7-Code NVFP4 model is the quantized version of the Moonshot AI's Kimi-K2.7-Code model, which is an auto-regressive language model that uses an optimized transformer architecture. For more information, please check here. The NVIDIA Kimi-K2.7-Code NVFP4 model is quantized with Model Optimizer. This model is ready for commercial or non-commercial use. <br Third-Party Community Consideration This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see link to Non-NVIDIA (Kimi-K2.7-Code) Model Card. License/Terms of Use: Governing Terms: Use of this model is governed by the NVIDIA Open Model License. ADDITIONAL INFORMATION : Modified MIT License. Kimi-K2.7-Code . Deployment Geography: Global <br Use Case: Kimi-K2.7-Code Use case: developers and inference providers who need ready-to-deploy, pre-quantized versions of popular generative models for NVIDIA GPU inference. Release Date: Hugging Face 07/06/2026 via https://huggingface.co/nvidia/Kimi-K2.7-Code-NVFP4 <br Model Architecture: Architecture Type: Transformers <br Network Architecture: DeepSeek V3 <br Number of Model Parameters: 1T in total and 32B activated <br Input: Input Type(s): Text, Image, Video <br Input Format(s): String, Binary(Base64 encoded), Binary(Base64 encoded) <br Input Parameters: One-Dimensional (1D), Two-Dimensional (2D), Three-Dimensional (3D) <br Other Properties Related to Input: Context length: 256k<br Output: Output Type(s): Text <br Output Format: String <br Output Parameters: 1D (One Dimensional): Sequences <br Other Properties Related to Output: Outputs may include natural-language responses, code, structured JSON, tool-call requests, agent coordination instructions, and generated artifacts depending on serving configuration and application-level tooling. <br Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA's hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions. <br Software Integrat

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How language models work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys kimi-k2-7-code for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (kimi-k2-7-code below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"kimi-k2-7-code","messages":[{"role":"user","content":"Hello"}]}'

Details

Languages, data & research

Licence

Commercial licence needed

Sources

Weights & code

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