LLM Token Usage and Cost Trackers
Monitor and analyze API consumption, token counts, and operational expenses for large language model integrations.
LLM Token Usage and Cost Trackers
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- coaidev/coai
coaidev/coai
9,212View on GitHubCoAI is an enterprise-grade, self-hostable AI gateway platform that unifies access to over 200 AI models from more than 35 providers through a single OpenAI-compatible API endpoint. It functions as a multi-tenant gateway, routing requests across providers with load balancing, automatic failover, and priority-based routing, while exposing standard OpenAI API endpoints for chat, image generation, model listing, and billing to enable seamless integration with existing tools and clients. The platform distinguishes itself through a comprehensive set of operational capabilities built around the gat
CoAI is a self-hostable AI gateway that unifies access to hundreds of models and providers, with built-in usage metering, billing breakdowns, and AI usage dashboards — directly covering token logging, cost estimation, and multi-provider monitoring for this search.
TypeScriptAI Usage and Routing DashboardsAI Usage Dashboards - ryoppippi/ccusage
ryoppippi/ccusage
10,826View on GitHubThis project is a command-line utility designed to monitor and analyze token consumption and financial expenditure for AI coding assistants. By parsing local session logs directly on the user's machine, it provides a privacy-focused way to track development activity without transmitting sensitive data to external servers. The tool distinguishes itself through its ability to aggregate disparate log formats from multiple coding assistants into a unified, schema-agnostic representation. It features a decoupled pricing engine that allows users to apply custom model-specific cost multipliers, over
ccusage is a CLI utility that monitors token consumption and costs specifically for AI coding assistants, parsing local logs across multiple tools with a custom pricing engine — it fits the broad category of LLM token usage and cost tracking, though its focus on coding assistants rather than all LLM API calls makes it a narrower match.
TypeScriptConversation Cost AggregatorsAI Cost MonitoringLLM Cost Management - helicone/helicone
Helicone/helicone
5,830View on GitHubHelicone is an AI gateway and observability platform designed to intercept, manage, and monitor interactions with large language models. By acting as a reverse-proxy, it provides a centralized layer for routing requests across multiple AI providers, allowing developers to maintain consistent application logic while gaining deep visibility into model performance, usage, and costs. The platform distinguishes itself through a robust suite of traffic management and prompt engineering tools. It enables policy-driven control, including automatic failover between providers, rate limiting, and edge-b
Helicone is an AI gateway and observability platform that intercepts and logs LLM API calls across multiple providers, giving you detailed visibility into token usage, per-model costs, and billing breakdowns — exactly the centralized monitoring and tracking setup this search asks for.
TypeScriptAI Cost Monitoring - mnfst/manifest
mnfst/manifest
7,022View on GitHubManifest is a language model provider unification system that standardizes access to multiple AI backends through a single interface. It functions as a centralized management layer for integrating various cloud-based and local model providers to simplify how applications request completions. The system provides intelligent model routing and high availability infrastructure by directing queries based on complexity and automatically triggering model fallbacks when a primary provider fails. It distinguishes itself through multi-tenant AI management, organizing agents into isolated groups with de
Manifest is a provider unification system that standardizes multi-provider LLM access with built-in token usage analytics, cost monitoring, spending quotas, and model pricing management, making it a good fit for tracking token consumption and costs across different backends.
TypeScriptAI Cost MonitoringToken Usage Analytics - langfuse/langfuse
langfuse/langfuse
29,190View on GitHubLangfuse is an open-source observability and evaluation platform designed for language model applications. It provides a centralized system for tracking execution traces, monitoring performance metrics, and managing prompt templates. By capturing hierarchical units of work and telemetry data, the platform enables developers to debug complex application lifecycles and analyze token usage, latency, and model interactions in production environments. The platform distinguishes itself through an integrated evaluation framework that allows for systematic benchmarking and automated scoring of model
Langfuse is a full-featured LLM observability platform that monitors token usage, latency, and cost across multiple providers, making it a comprehensive solution for tracking and analyzing consumption and spend.
TypeScriptLLM ObservabilityAI Observability and EvaluationAutomated Trace Evaluation - nanbingxyz/5ire
nanbingxyz/5ire
5,029View on GitHub5ire is a conversational AI interface and client that integrates large language models with external tools and local data. It functions as an AI prompt manager, a local retrieval-augmented generation knowledge base, and a monitoring tool for tracking API usage and spending across multiple model providers. The project specifically implements the Model Context Protocol to connect AI assistants with live data and executable system tools. It supports tool installation via custom application protocol URIs and uses schema-driven input generation to create interactive configuration forms for server
5ire is a conversational AI client that explicitly includes built-in API usage and cost monitoring across multiple model providers, with features like token usage analytics and spending tracking that directly match the need for token consumption and billing analysis, though it embeds these capabilities within a broader chat interface rather than being a standalone dashboard.
TypeScriptAI Cost MonitoringToken Usage Analytics - traceloop/openllmetry
traceloop/openllmetry
7,202View on GitHubOpenLLMetry is an OpenTelemetry-based observability framework and instrumentation library for generative AI applications. It provides toolsets for tracing and monitoring large language model workflows, capturing telemetry from model providers, agent frameworks, and vector databases using standardized semantic conventions. The project distinguishes itself by providing a specialized evaluation and experimentation suite that associates user feedback and prompt version hashes with specific execution traces. It includes a system for tracking model reasoning paths and enforcing security guardrails
OpenLLMetry is an OpenTelemetry-based observability framework that traces LLM API calls and captures token usage and cost data across multiple providers, making it well-suited for monitoring and analyzing token consumption and budgeting, though you may need to set up external dashboards for visualization.
PythonLLM Cost ManagementToken Consumption Trackers - agentops-ai/agentops
AgentOps-AI/agentops
5,654View on GitHubAgentOps is an observability platform and developer toolkit for monitoring the execution, performance, and reliability of autonomous agents powered by large language models. It serves as a system for tracking AI agent behavior, debugging complex workflows, and benchmarking model performance. The platform is distinguished by its ability to visualize multi-agent workflows through execution path graphing and session replays. It provides specific tools for calculating financial spend across various language model providers and supports a self-hosted observability stack for users who require full
AgentOps is an observability platform that tracks LLM token usage and costs across providers, with automatic telemetry, financial spend calculation, and workflow visualizations—it directly covers the requested monitoring, logging, and cost analysis even though it is broader than a dedicated cost tracker.
PythonLLM Cost Management - agenta-ai/agenta
Agenta-AI/agenta
3,860View on GitHubAgenta is a Prompt Ops lifecycle manager and prompt management platform that decouples prompt engineering from application code. It serves as a centralized system for developing, versioning, and deploying prompt templates and model configurations across different environments. The platform functions as an AI agent orchestrator with a visual interface for building agent workflows and connecting models to external tools. It further acts as an evaluation framework and observability tool, utilizing OpenTelemetry to capture execution traces, monitor latency, and track token costs. The system cove
Agenta is a prompt ops lifecycle manager and observability platform that explicitly tracks token costs and logs API calls using OpenTelemetry, making it a suitable tool for monitoring and analyzing LLM token usage, though its broader scope includes agent orchestration and evaluation beyond pure cost tracking.
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