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What is Nemotron 3.5 Super VL?

NVIDIA Nemotron 3.5 Super VL is an open multimodal artificial intelligence model designed to support specialized autonomous agents, enterprise automation, and complex reasoning tasks. Introduced in October 2026, the model combines language processing, visual understanding, software engineering capabilities, and external tool interactions within a unified architecture. It uses a 120-billion-parameter mixture-of-experts design with approximately 12 billion active parameters per token to optimize inference efficiency. The model was distilled from NVIDIA Nemotron 3 Ultra and incorporates additional training focused on coding, multimodal reasoning, and agentic task execution. Its vision-language capabilities support analysis of images, charts, tables, diagrams, multipage documents, and video content. Document intelligence workflows can extract structured information, interpret visual evidence, connect information across pages, and generate summaries or reports. Software engineering features enable the model to analyze repositories, identify programming errors, test code, and recommend modifications across development workflows. Its agentic capabilities support web research, external tool usage, multistep problem-solving, cybersecurity vulnerability analysis, and enterprise process automation. NVIDIA NeMo provides customization tools for supervised fine-tuning, low-rank adaptation, and reinforcement learning using proprietary datasets, organizational policies, and specialized workflows. The model incorporates LiLiCorr speculative decoding, multi-token prediction, context reuse, and NVFP4 quantization to improve inference performance on compatible hardware. Nemotron 3.5 Super VL is distributed with open weights and supports local, cloud, and data center deployment through NVIDIA infrastructure and tools such as NVIDIA NIM.

What is Kimi K3?

Kimi K3 is Moonshot AI’s most advanced model, designed for high-end reasoning, software engineering, multimodal understanding, knowledge work, and agentic AI applications. The model has 2.8 trillion parameters and is built on Kimi Delta Attention, a hybrid linear attention mechanism created for long-context performance. It also uses Attention Residuals and supports a native context window of up to 1 million tokens. This makes Kimi K3 suitable for tasks involving large codebases, long research materials, enterprise documentation, multi-file analysis, legal documents, technical manuals, and complex workflows. Kimi K3 always has thinking mode enabled, with reasoning effort configured through the reasoning_effort field and maximum effort currently supported as the default. Developers can use the model through an OpenAI-compatible API, making it easier to integrate with existing SDKs, clients, and application infrastructure. The model supports streaming responses with separate reasoning and final-answer deltas, allowing applications to display reasoning progress and final content differently. Kimi K3 also supports strict structured output with JSON Schema, partial mode for continuing from a prefix, custom tool calling, required tool use, and dynamic tool loading through system messages. Its vision capabilities support image and video inputs through base64 or uploaded files, enabling analysis of visual content alongside text. Automatic context caching helps workflows that reuse long prefixes, such as large knowledge bases or persistent system context, without requiring developers to manage cache IDs manually. By combining frontier-scale parameters, long-context processing, visual input, structured outputs, tool orchestration, and developer-friendly API compatibility, Kimi K3 gives teams a strong foundation for advanced AI agents, coding assistants, research systems, enterprise automation, and multimodal applications.

Media

Media

Integrations Supported

OpenRouter

Integrations Supported

.NET
APIFree
Cheaper Inference
ClinePass
CoreWeave
Fireworks AI
HTML
JavaScript
JetBrains Junie
Kimi Code CLI
OpenClaw
OpenCode Go
PHP
Python
Scala
SiliconFlow
Tabbit Browser
Together AI
YAML

API Availability

Has API

API Availability

Has API

Pricing Information

$0
The model is available at no charge under the OpenMDW-1.1 license. Hosted inference through third-party providers may have separate charges.
Free Version

Pricing Information

$3 per 1M tokens (input)
Kimi K3 is priced per 1 million tokens:

Cached input: $0.30
Uncached input: $3.00
Output: $15.00
Context window: 1,048,576 tokens

Cached inputs cost 90% less than uncached inputs, while generated output is the most expensive token category. Prices exclude applicable taxes, which are calculated based on the customer’s jurisdiction.

Supported Platforms

SaaS
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

nvidia.com

Company Facts

Organization Name

Moonshot AI

Date Founded

2023

Company Location

China

Company Website

kimi.ai

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Popular Alternatives

Popular Alternatives

Kimi K2 Reviews & Ratings

Kimi K2

Moonshot AI