Model Pricing And Context Window Database

via “model-pricing-and-context-window-database”

Unified API for 100+ LLM providers — OpenAI format, load balancing, spend tracking, proxy server.

Unique: Maintains a comprehensive JSON database (model_prices_and_context_window.json) with pricing and context windows for 100+ models. Includes provider-specific pricing tiers (e.g., GPT-4 Turbo has different prices for different context windows). Automatically used by cost_calculator.py for per-request cost calculation.

vs others: More comprehensive than provider-specific pricing pages (covers 100+ models); automatically used for cost calculation vs manual lookup; includes context windows vs pricing-only databases

via “context-window-optimization-and-routing”

** - The ultimate open-source server for advanced Gemini API interaction with MCP, intelligently selects models.

Unique: Implements automatic context window selection based on request analysis, routing transparently to appropriate model variants without client-side logic

vs others: Eliminates manual context window selection overhead compared to raw API clients, while remaining more flexible than fixed-window approaches

via “context window and capability filtering for model selection”

100+ LLM models. Pricing, capabilities, context windows. Always current.

Unique: Exposes a queryable metadata schema that allows developers to filter models by technical capabilities (vision, function calling, fine-tuning) and cost constraints in a single operation, rather than requiring manual cross-referencing of provider documentation.

vs others: Enables programmatic, constraint-based model selection in application code rather than manual research; more flexible than provider-specific SDKs which lock you into one vendor

via “context window and throughput specification database”

Compare AI models across benchmarks, pricing, speed, and context window.

Unique: Consolidates scattered specification data from multiple provider documentation pages into a single queryable schema with consistent units and filtering, enabling constraint-based model selection rather than manual documentation review

vs others: Faster than reading individual model cards and enables filtering by multiple constraints simultaneously; differs from provider dashboards by aggregating across all providers in one place

via “model-context-window-management”