Atom Pricing Intelligence

Search and filter AI inference models across all tracked vendors and SKUs. Query by modality (Text, Image, Audio, Video, Multimodal), vendor, creator, model family, open-source status, price range, context window, and parameter count. Returns matching models with pricing. Free tier shows count + price range; paid tier shows full details. Examples: - "Find open-source text models under $1/M tokens" → open_source=true, modality="Text", max_price=0.001 - "What multimodal models does Google offer?" → vendor="Google", modality="Multimodal" - "Models with 128K+ context window" → min_context_window=128000

Deep dive on a single AI model: technical specs + pricing across all vendors. Returns model_registry data (context window, parameters, open-source status, training cutoff, model family) plus all SKU pricing across every vendor that offers this model. Examples: - "Tell me everything about GPT-4o" → model_name="GPT-4o" - "Claude Sonnet 4.5 specs and pricing" → model_name="Claude Sonnet 4.5"

Cross-vendor price comparison for a specific model or model family. Shows the same model (or family) priced across different vendors, sorted cheapest first. Essential for cost optimization and vendor selection. Examples: - "Compare Llama 3.1 70B pricing across vendors" → model_name="Llama 3.1 70B" - "Cheapest GPT-4 family output pricing" → model_family="GPT-4", direction="Output" - "Claude pricing comparison" → model_family="Claude"

Full catalog for a specific vendor: all models, modalities, and pricing. Returns vendor metadata (country, region, pricing page URL) plus every model and SKU they offer. Examples: - "What does Together AI sell?" → vendor="Together AI" - "OpenAI's text model pricing" → vendor="OpenAI", modality="Text" - "Amazon Bedrock catalog" → vendor="Amazon Bedrock"

Aggregate AI inference market intelligence. Returns total vendor/model/SKU counts, price distribution (median, mean, quartiles, min/max), and modality breakdown. Optionally filter by modality. Examples: - "AI inference market overview" → (no params) - "Text model pricing statistics" → modality="Text" - "Image generation market stats" → modality="Image"

AIPI (ATOM Inference Price Index) — chained matched-model price benchmarks for AI inference. Returns benchmark indexes across four categories: - Modality: Text, Multimodal, Image, Audio, Video, Voice, Embeddings - what does this type of inference cost? - Channel: Model Developers, Cloud Marketplaces, Inference Platforms, Neoclouds - where should you buy? - Tier: Frontier, Budget, Mid, Reasoning - what's the premium for capability? - Special: Open-Source - how much cheaper is open-weight inference? Each index includes input, cached input, and output pricing per period. These are market-wide benchmarks, not individual vendor prices. Use them to understand where the market is and how it's moving. Fully public — available to all tiers. Examples: - "What's the current benchmark for text inference?" → index_category="Modality" - "Show me all AIPI indexes" → (no params) - "Neocloud pricing benchmark" → index_code="AIPI NCL GLB" - "Channel pricing comparison" → index_category="Channel" - "Open-source vs market pricing" → index_code="AIPI OSS GLB"

ATOM Inference Market KPIs — 9 cost and structure metrics derived from live pricing data across all tracked vendors: - Output Price Premium: how much more output tokens cost vs input - Caching Discount Rate: average discount for cached input pricing - Open Source Discount Rate: price gap between open-source and proprietary - Context Window Cost: price multiplier for 128K+ vs smaller context - Model Size Spread: price ratio between large and small models - Reasoning Premium: cost of reasoning models vs standard text - Platform Discount Rate: inference platforms vs buying direct - Neocloud Discount Rate: GPU-native providers vs model developers - Caching Availability: % of text models offering cached pricing These KPIs are available to all tiers — they demonstrate ATOM's market intelligence.

ATOM Model Intelligence — 6 capability and coverage metrics derived from the metadata behind every tracked model. Complements the pricing KPIs in get_kpis. Returns 6 metrics: - Reasoning Tier Share: % of general-purpose text models that are reasoning-tier - Long-Context Saturation: % of models shipping 128K+ context windows - Frontier Context Ceiling: context multiplier between top-decile and median models - Output Ceiling Spread: max output token multiplier between top-decile and median - Training Cutoff Lag: median months between model training cutoff and today - Vendor Modality Breadth: median number of modalities offered per vendor Read alongside pricing, these explain why a model is priced the way it is. Available to all tiers. Examples: - "How stale are AI models on average?" → Training Cutoff Lag - "What share of models support long context?" → Long-Context Saturation - "How rare are reasoning models?" → Reasoning Tier Share

List all AI inference vendors tracked by ATOM. Returns vendor name, country, region, and pricing page URL. Vendors span four channel types: Model Developers, Cloud Marketplaces, Inference Platforms, and Neoclouds. Optionally filter by region or country. Examples: - "List all vendors" → (no params) - "European AI vendors" → region="Europe" - "Chinese AI vendors" → country="China"