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Average Ratings 0 Ratings

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ease
features
design
support

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Description

We are thrilled to present DBRX, a versatile open LLM developed by Databricks. This innovative model achieves unprecedented performance on a variety of standard benchmarks, setting a new benchmark for existing open LLMs. Additionally, it equips both the open-source community and enterprises crafting their own LLMs with features that were once exclusive to proprietary model APIs; our evaluations indicate that it outperforms GPT-3.5 and competes effectively with Gemini 1.0 Pro. Notably, it excels as a code model, outperforming specialized counterparts like CodeLLaMA-70B in programming tasks, while also demonstrating its prowess as a general-purpose LLM. The remarkable quality of DBRX is complemented by significant enhancements in both training and inference efficiency. Thanks to its advanced fine-grained mixture-of-experts (MoE) architecture, DBRX elevates the efficiency of open models to new heights. In terms of inference speed, it can be twice as fast as LLaMA2-70B, and its total and active parameter counts are approximately 40% of those in Grok-1, showcasing its compact design without compromising capability. This combination of speed and size makes DBRX a game-changer in the landscape of open AI models.

Description

Ling 2.6 represents an independently developed and open-source series of large language models created by Ant Group, utilizing a Mixture of Experts (MoE) architecture to enhance inference efficiency, long context modeling, training methodologies, and collaborative reasoning for AI agents. By employing this MoE architecture, Ling effectively directs each token to engage only the most pertinent expert subnetworks, significantly reducing the computational load while preserving the extensive capabilities of the model. This series makes strides in long-sequence modeling, exemplified by Ling-2.6-1T, which accommodates a native context window of up to 1 million tokens and offers a 256K context window through its official API; additionally, Ling-2.6-flash features a native 256K context window, enabling it to handle around 200,000 characters in lengthy inputs. These models are meticulously crafted to ensure dependable retrieval of long-range information without any discernible loss of quality, regardless of whether the data is located at the start, middle, or end of the context. This innovative approach to long-context processing sets a new benchmark for efficiency and reliability in language model performance.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Claude Code No 
Cogent DataHub Yes 
Double Yes 
GPT-3.5 Yes 
GPT-4 Yes 
Hermes Agent No 
Kilo Code No 
OpenAI No 
OpenClaw No 
OpenRouter No 
Rayven Yes 
Visplore Yes 
ZenML Yes 

Integrations

Claude Code Yes 
Cogent DataHub No 
Double No 
GPT-3.5 No 
GPT-4 No 
Hermes Agent Yes 
Kilo Code Yes 
OpenAI Yes 
OpenClaw Yes 
OpenRouter Yes 
Rayven No 
Visplore No 
ZenML No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$0.0028 per 1M tokens
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

Databricks

Country

United States

Website

www.databricks.com/blog/introducing-dbrx-new-state-art-open-llm

Vendor Details

Company Name

Ant Group

Founded

2014

Country

China

Website

developer.ant-ling.com/en/docs/models/ling/

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