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ease
features
design
support

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Description

GigaChat 3 Ultra redefines open-source scale by delivering a 702B-parameter frontier model purpose-built for Russian and multilingual understanding. Designed with a modern MoE architecture, it achieves the reasoning strength of giant dense models while using only a fraction of active parameters per generation step. Its massive 14T-token training corpus includes natural human text, curated multilingual sources, extensive STEM materials, and billions of high-quality synthetic examples crafted to boost logic, math, and programming skills. This model is not a derivative or retrained foreign LLM—it is a ground-up build engineered to capture cultural nuance, linguistic accuracy, and reliable long-context performance. GigaChat 3 Ultra integrates seamlessly with open-source tooling like vLLM, sglang, DeepSeek-class architectures, and HuggingFace-based training stacks. It supports advanced capabilities including a code interpreter, improved chat template, memory system, contextual search reformulation, and 128K context windows. Benchmarking shows clear improvements over previous GigaChat generations and competitive results against global leaders in coding, reasoning, and cross-domain tasks. Overall, GigaChat 3 Ultra empowers teams to explore frontier-scale AI without sacrificing transparency, customizability, or ecosystem compatibility.

Description

Qwen3.5-35B-A3B is a member of the Qwen3.5 "Medium" model series, meticulously crafted as an effective multimodal foundation model that strikes a balance between robust reasoning capabilities and practical application needs. Utilizing a Mixture-of-Experts (MoE) architecture, it boasts a total of 35 billion parameters, yet activates only around 3 billion for each token, enabling it to achieve performance levels similar to much larger models while significantly cutting down on computational expenses. The model employs a hybrid attention mechanism that merges linear attention with traditional attention layers, which enhances its ability to handle extensive context and boosts scalability for intricate tasks. As an inherently vision-language model, it processes both textual and visual data, catering to a variety of applications, including multimodal reasoning, programming, and automated workflows. Furthermore, it is engineered to operate as a versatile "AI agent," proficient in planning, utilizing tools, and systematically solving problems, extending its functionality beyond mere conversational interactions. This capability positions it as a valuable asset across diverse domains, where advanced AI-driven solutions are increasingly required.

API Access

Has API

API Access

Has API

Screenshots View All

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Screenshots View All

Integrations

GigaChat
Hugging Face
ModelScope
Ollama
OpenClaw
Qwen
Qwen Chat

Integrations

GigaChat
Hugging Face
ModelScope
Ollama
OpenClaw
Qwen
Qwen Chat

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Sberbank

Founded

1841

Country

Russia

Website

giga.chat

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai/blog

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