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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

DeepSeek V3.1 stands as a revolutionary open-weight large language model, boasting an impressive 685-billion parameters and an expansive 128,000-token context window, which allows it to analyze extensive documents akin to 400-page books in a single invocation. This model offers integrated functionalities for chatting, reasoning, and code creation, all within a cohesive hybrid architecture that harmonizes these diverse capabilities. Furthermore, V3.1 accommodates multiple tensor formats, granting developers the versatility to enhance performance across various hardware setups. Preliminary benchmark evaluations reveal strong results, including a remarkable 71.6% on the Aider coding benchmark, positioning it competitively with or even superior to systems such as Claude Opus 4, while achieving this at a significantly reduced cost. Released under an open-source license on Hugging Face with little publicity, DeepSeek V3.1 is set to revolutionize access to advanced AI technologies, potentially disrupting the landscape dominated by conventional proprietary models. Its innovative features and cost-effectiveness may attract a wide range of developers eager to leverage cutting-edge AI in their projects.

Description

Qwen3.8-Flash-Next represents an open-weight multimodal Mixture-of-Experts architecture and serves as an initial glimpse into the design intended for Qwen4. This model strategically enhances attention mechanisms, residual pathways, embeddings, and optimization techniques to boost its capabilities, improve computational efficiency, expand model capacity, and ensure training stability. Its innovative hybrid architecture merges Gated DeltaNet, which adeptly compresses past information, with Qwen Sparse Attention, enabling the selection of significant context at a micro-block level to lessen both attention and indexing costs associated with lengthy sequences. The Gated Residual feature broadens the residual pathway into four streams, dynamically managing the flow of information across different layers. Additionally, the N-gram Embedding integrates large-scale local-pattern memory with minimal added computation per token, and it can be transferred to host memory for further efficiency. The model is structured around a 125B-parameter main network supplemented by 51B parameters dedicated to N-gram embeddings, activating only 6B parameters for each token processed. This sophisticated framework highlights the ongoing advancements in machine learning architectures, setting a promising stage for future developments.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Hugging Face Yes 
Ollama Yes 
Aider Yes 
Alibaba Cloud No 
Alibaba Cloud Model Studio No 
Cline No 
ClinePass No 
EaseMate AI Yes 
Happy Shrimp 1.0 No 
Intrascope Yes 
LLM Council Yes 
Model Context Protocol (MCP) No 
ModelArk Yes 
ModelScope No 
OfoxAI No 
Okara Yes 
OpenClaw No 
Python No 
QwenCloud No 
QwenWork No 

Integrations

Hugging Face Yes 
Ollama Yes 
Aider No 
Alibaba Cloud Yes 
Alibaba Cloud Model Studio Yes 
Cline Yes 
ClinePass Yes 
EaseMate AI No 
Happy Shrimp 1.0 Yes 
Intrascope No 
LLM Council No 
Model Context Protocol (MCP) Yes 
ModelArk No 
ModelScope Yes 
OfoxAI Yes 
Okara No 
OpenClaw Yes 
Python Yes 
QwenCloud Yes 
QwenWork Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

$2 per 1M (input)
Free Trial No 
Free Version No 

Deployment

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

Deployment

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

Customer Support

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

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

DeepSeek

Founded

2023

Country

China

Website

deepseek.ai/blog/deepseek-v31

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai/blog

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