A 4B model that estimates numbers from text with calibrated intervals
Stage
Startup
Not given
Founded
2024
Not given
Based in
US
Not given
Pricing model
Paid
Freemium
Pricing
Pay-as-you-go pricing for serverless inference charged per token and for on-demand deployments charged per GPU usage time. New users receive free credits. Text models range from $0.05 to $1.5 per 1M tokens (input and output), including Llama-3.2-1B-Instruct at $0.06/1M tokens, Meta-Llama-3.1-8B-Inst
First 1,000 estimates free. Pricing for additional estimates available upon request.
Key features
Text generation with multiple LLM models including Llama, Qwen, and DeepSeek
Embedding and reranking models for RAG applications
Text-to-image and text-to-video generation
Voice generation with ASR/TTS models
Single line of code integration
Agent application with ultra-low latency
Chat2DB application with real-time responsiveness
Inference acceleration capability
Competitive pricing with reduced costs
Returns median, quantiles, and calibrated intervals for numerical estimates
Processes text records in a single forward pass without text generation
Responds in approximately 160 milliseconds
Flags when targets are outside training distribution or intervals lack calibration guarantees
Supports few-shot learning with at least eight labeled examples
Trained on 36 public sources
Calculates probability of exceeding user-specified thresholds
For count targets can return probability of each whole number
Accepts text input without requiring schema declaration or preprocessing
Costs roughly two orders of magnitude less per prediction than frontier models
What makes it different
Out-of-the-box inference acceleration capability
Fast model updates and comprehensive model selection
Single line of code integration with no deployment complexity
Ultra-low latency for responsive applications
Free credits for new users to get started
Provides calibrated uncertainty quantification where language models cannot
Transparently reports when calibration guarantees are absent
Dramatically faster inference than text-generating alternatives at 160ms
Designed for unstructured text without requiring labeled training data
Explicitly signals new, unseen targets with fallback capability for code
maap