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Description

Pixtral Large is an expansive multimodal model featuring 124 billion parameters, crafted by Mistral AI and enhancing their previous Mistral Large 2 framework. This model combines a 123-billion-parameter multimodal decoder with a 1-billion-parameter vision encoder, allowing it to excel in the interpretation of various content types, including documents, charts, and natural images, all while retaining superior text comprehension abilities. With the capability to manage a context window of 128,000 tokens, Pixtral Large can efficiently analyze at least 30 high-resolution images at once. It has achieved remarkable results on benchmarks like MathVista, DocVQA, and VQAv2, outpacing competitors such as GPT-4o and Gemini-1.5 Pro. Available for research and educational purposes under the Mistral Research License, it also has a Mistral Commercial License for business applications. This versatility makes Pixtral Large a valuable tool for both academic research and commercial innovations.

Description

Qwen3.5 represents a major advancement in open-weight multimodal AI models, engineered to function as a native vision-language agent system. Its flagship model, Qwen3.5-397B-A17B, leverages a hybrid architecture that fuses Gated DeltaNet linear attention with a high-sparsity mixture-of-experts framework, allowing only 17 billion parameters to activate during inference for improved speed and cost efficiency. Despite its sparse activation, the full 397-billion-parameter model achieves competitive performance across reasoning, coding, multilingual benchmarks, and complex agent evaluations. The hosted Qwen3.5-Plus version supports a one-million-token context window and includes built-in tool use for search, code interpretation, and adaptive reasoning. The model significantly expands multilingual coverage to 201 languages and dialects while improving encoding efficiency with a larger vocabulary. Native multimodal training enables strong performance in image understanding, video processing, document analysis, and spatial reasoning tasks. Its infrastructure includes FP8 precision pipelines and heterogeneous parallelism to boost throughput and reduce memory consumption. Reinforcement learning at scale enhances multi-step planning and general agent behavior across text and multimodal environments. Overall, Qwen3.5 positions itself as a high-efficiency foundation for autonomous digital agents capable of reasoning, searching, coding, and interacting with complex environments.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

No images available

Screenshots View All

Integrations

1min.AI Yes 
302.AI Yes 
Amazon Bedrock Yes 
Expanse Yes 
Fleak Yes 
GaiaNet Yes 
Kiin Yes 
Klee Yes 
LibreChat Yes 
Lunary Yes 
Memo AI Yes 
Nutanix Enterprise AI Yes 
OpenLIT Yes 
Pipeshift Yes 
Qwen3.5-Plus No 
Superinterface Yes 
Together AI No 
Verta Yes 
Wordware Yes 

Integrations

1min.AI No 
302.AI No 
Amazon Bedrock No 
Expanse No 
Fleak No 
GaiaNet No 
Kiin No 
Klee No 
LibreChat No 
Lunary No 
Memo AI No 
Nutanix Enterprise AI No 
OpenLIT No 
Pipeshift No 
Qwen3.5-Plus Yes 
Superinterface No 
Together AI Yes 
Verta No 
Wordware No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Mistral AI

Founded

2023

Country

France

Website

mistral.ai/news/pixtral-large/

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai

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