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ease
features
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support

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Description

Featherless is a provider of AI models, granting subscribers access to an ever-growing collection of Hugging Face models. With the influx of hundreds of new models each day, specialized tools are essential to navigate this expanding landscape. Regardless of your specific application, Featherless enables you to discover and utilize top-notch AI models. Currently, we offer support for LLaMA-3-based models, such as LLaMA-3 and QWEN-2, though it's important to note that QWEN-2 models are limited to a context length of 16,000. We are also planning to broaden our list of supported architectures in the near future. Our commitment to progress ensures that we continually integrate new models as they are released on Hugging Face, and we aspire to automate this onboarding process to cover all publicly accessible models with suitable architecture. To promote equitable usage of individual accounts, concurrent requests are restricted based on the selected plan. Users can expect output delivery rates ranging from 10 to 40 tokens per second, influenced by the specific model and the size of the prompt, ensuring a tailored experience for every subscriber. As we expand, we remain dedicated to enhancing our platform's capabilities and offerings.

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 
Qwen Yes 
Alibaba Cloud No 
Alibaba Cloud Model Studio No 
ChatGPT Yes 
Cherry Studio No 
Cline No 
ClinePass No 
Happy Shrimp 1.0 No 
Hermes Agent No 
Llama Yes 
Llama 3 Yes 
Llama 3.1 Yes 
Llama 3.3 Yes 
Model Context Protocol (MCP) No 
ModelScope No 
Odysseus No 
OpenClaw No 
QwenCloud No 
QwenWork No 

Integrations

Hugging Face Yes 
Qwen Yes 
Alibaba Cloud Yes 
Alibaba Cloud Model Studio Yes 
ChatGPT No 
Cherry Studio Yes 
Cline Yes 
ClinePass Yes 
Happy Shrimp 1.0 Yes 
Hermes Agent Yes 
Llama No 
Llama 3 No 
Llama 3.1 No 
Llama 3.3 No 
Model Context Protocol (MCP) Yes 
ModelScope Yes 
Odysseus Yes 
OpenClaw Yes 
QwenCloud Yes 
QwenWork Yes 

Pricing Details

$10 per month
Free Trial No 
Free Version No 

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 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 No 

Vendor Details

Company Name

Featherless

Website

featherless.ai/

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwen.ai/blog

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