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Average Ratings 0 Ratings
Description
Mercury 2.5 represents the pinnacle of production models from Inception, demonstrating a remarkable enhancement in quality compared to its predecessor, Mercury 2, all while upholding an impressive low-latency serving profile. It stands out as the most advanced diffusion language model currently available and is touted by Inception as the largest diffusion LLM ever developed. With a 40% boost in intelligence over Mercury 2, its performance aligns closely with that of cost-efficient frontier models like GPT-5.6 Luna (Low), Gemini 3.5 Flash-Lite, and Claude Haiku 4.5. The model boasts a generation speed of 1,107 tokens per second on commonly accessible NVIDIA GPUs and accommodates a generous 260K-token context window. Among its features are adjustable reasoning capabilities, simultaneous tool calls, and JSON that aligns with schemas. Specifically engineered for latency-sensitive tasks, it is well-suited for scenarios involving numerous model calls during a single interaction. In applications such as search agents and RAG pipelines, Mercury 2.5 excels in functions like planning, query rewriting, re-ranking, fact structuring, source summarization, and answer verification, all while ensuring rapid response times, making it an essential tool for developers seeking efficiency in their workflows.
Description
Pinecone Rerank V0 is a cross-encoder model specifically designed to enhance precision in reranking tasks, thereby improving enterprise search and retrieval-augmented generation (RAG) systems. This model processes both queries and documents simultaneously, enabling it to assess fine-grained relevance and assign a relevance score ranging from 0 to 1 for each query-document pair. With a maximum context length of 512 tokens, it ensures that the quality of ranking is maintained. In evaluations based on the BEIR benchmark, Pinecone Rerank V0 stood out by achieving the highest average NDCG@10, surpassing other competing models in 6 out of 12 datasets. Notably, it achieved an impressive 60% increase in performance on the Fever dataset when compared to Google Semantic Ranker, along with over 40% improvement on the Climate-Fever dataset against alternatives like cohere-v3-multilingual and voyageai-rerank-2. Accessible via Pinecone Inference, this model is currently available to all users in a public preview, allowing for broader experimentation and feedback. Its design reflects an ongoing commitment to innovation in search technology, making it a valuable tool for organizations seeking to enhance their information retrieval capabilities.
API Access
Has API
API Access
Has API
Integrations
Airbyte
Anyscale
Box
Cohere
Context Data
Databricks
Datadog
Datavolo
Flowise
Google Cloud Platform
Integrations
Airbyte
Anyscale
Box
Cohere
Context Data
Databricks
Datadog
Datavolo
Flowise
Google Cloud Platform
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$25 per month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Inception
Country
United States
Website
www.inceptionlabs.ai/blog/introducing-mercury-2-5
Vendor Details
Company Name
Pinecone
Founded
2019
Country
United States
Website
www.pinecone.io/blog/pinecone-rerank-v0-announcement/