What is Dhanishtha-2.0-preview?
Dhanishtha-2.0-preview is the world's first model to use Intermediate reasoning, which basically means reasoning in middle of responses. This approach makes reasoning/COT models more time and token efficient. Thus, lowering their cost.
Problem
Users rely on traditional chain-of-thought (CoT) AI models for reasoning tasks, which process entire responses sequentially. Traditional CoT models are time and token inefficient, leading to higher computational costs and slower outputs.
Solution
An AI model (Dhanishtha 2.0) that introduces intermediate reasoning mid-response, enabling partial reasoning steps during output generation. Users can reduce token usage by up to 30% while maintaining accuracy, lowering API costs.
Customers
AI developers, ML engineers, and data scientists building cost-sensitive NLP applications; startups optimizing AI inference budgets; enterprises scaling reasoning-heavy workflows.
Unique Features
First implementation of intermediate reasoning that pauses mid-response to refine logic, unlike sequential CoT. Claims 20-30% faster processing and reduced token consumption without accuracy loss.
User Comments
Improves budget efficiency for API-based AI services
Enables complex reasoning tasks on limited infrastructure
Reduces latency in real-time applications
Lower costs make experimentation more accessible
Requires adaptation of existing prompt engineering workflows
Traction
Launched as preview on Product Hunt; exact user/base metrics undisclosed. Positioning targets the $XX billion AI infrastructure market (Statista 2023). Founder active on AI efficiency forums with 1.2k followers.
Market Size
The global generative AI market is projected to reach $118.06 billion by 2032 (Allied Market Research), with enterprise AI adoption driving demand for cost-efficient models.
