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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

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.

Description

Reka Flash 3 is a cutting-edge multimodal AI model with 21 billion parameters, crafted by Reka AI to perform exceptionally well in tasks such as general conversation, coding, following instructions, and executing functions. This model adeptly handles and analyzes a myriad of inputs, including text, images, video, and audio, providing a versatile and compact solution for a wide range of applications. Built from the ground up, Reka Flash 3 was trained on a rich array of datasets, encompassing both publicly available and synthetic information, and it underwent a meticulous instruction tuning process with high-quality selected data to fine-tune its capabilities. The final phase of its training involved employing reinforcement learning techniques, specifically using the REINFORCE Leave One-Out (RLOO) method, which combined both model-based and rule-based rewards to significantly improve its reasoning skills. With an impressive context length of 32,000 tokens, Reka Flash 3 competes effectively with proprietary models like OpenAI's o1-mini, making it an excellent choice for applications requiring low latency or on-device processing. The model operates at full precision with a memory requirement of 39GB (fp16), although it can be efficiently reduced to just 11GB through the use of 4-bit quantization, demonstrating its adaptability for various deployment scenarios. Overall, Reka Flash 3 represents a significant advancement in multimodal AI technology, capable of meeting diverse user needs across multiple platforms.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Alibaba Cloud Yes 
Alibaba Cloud Model Studio Yes 
Cherry Studio Yes 
Cline Yes 
Happy Shrimp 1.0 Yes 
Hermes Agent Yes 
Hugging Face Yes 
Model Context Protocol (MCP) Yes 
ModelScope Yes 
Nexus No 
Novita AI Yes 
Odysseus Yes 
OfoxAI Yes 
Ollama Yes 
OpenClaw Yes 
Qwen Yes 
Qwen Studio Yes 
QwenCloud Yes 
QwenWork Yes 
Space No 

Integrations

Alibaba Cloud No 
Alibaba Cloud Model Studio No 
Cherry Studio No 
Cline No 
Happy Shrimp 1.0 No 
Hermes Agent No 
Hugging Face No 
Model Context Protocol (MCP) No 
ModelScope No 
Nexus Yes 
Novita AI No 
Odysseus No 
OfoxAI No 
Ollama No 
OpenClaw No 
Qwen No 
Qwen Studio No 
QwenCloud No 
QwenWork No 
Space Yes 

Pricing Details

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

Pricing Details

No price information available.
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 No 
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 No 

Types of Training

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

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai/blog

Vendor Details

Company Name

Reka

Founded

2022

Country

United States

Website

www.reka.ai/news/introducing-reka-flash

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