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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

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Weights & Biases logo
Weights & Biases
✓ verifiedFreemium

Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.

2.5M visits/mo
Helicone logo
Helicone
✓ verifiedFreemium

LLM observability platform and AI gateway that lets teams route, log, debug and analyze their model requests.

100K visits/mo
liteLLM logo
liteLLM
✓ verifiedFreemium

Open-source AI gateway giving dev teams unified access, fallbacks and spend tracking across 100+ LLMs.

703K visits/mo
portkey.ai logo
portkey.ai
✓ verified

AI gateway and observability suite for governing and optimizing LLM apps; strong dev-tool traffic.

266K visits/mo
Latitude logo
Latitude
✓ verifiedFreemium

Open-source AI-agent observability platform for tracing sessions, clustering failures and running evals on live traffic.

57K visits/mo
Pricing

No public pricing

Hobby: Free (10,000 requests/mo)
Pro: $79/mo (unlimited seats)
Team: $799/mo (SOC-2 & HIPAA)

Free trial available

Open Source: $0 (self-hosted, 100+ providers)

Free trial available

No public pricing

No public pricing

Core features
  • Experiment tracking and visualization for ML training runs
  • Model and artifact versioning and management
  • Hyperparameter optimization tooling
  • Collaborative dashboards and reports for ML teams
  • LLM application tracing and evaluation tooling
  • Request logging and LLM observability
  • AI gateway with routing and automatic fallbacks
  • Caching and rate limiting
  • Session, user and custom-property analytics
  • Prompts, playground and datasets for testing
  • Integrations with OpenAI, Anthropic, Azure and more
  • Unified access to 100+ LLMs in OpenAI format
  • Cost/spend tracking per key, user and team
  • Budgets and rate limiting
  • Automatic provider fallbacks and retries
  • Virtual keys and team management
  • Logging and observability integrations
  • AI Gateway for reliable LLM routing
  • Prompt Engineering for collaborative prompt management
  • Guardrails for enforcing reliable LLM behavior
  • Observability Suite for monitoring costs, quality, and latency
  • MCP Client for building AI agents with real-world tool access
  • Agent trace capture and conversation intelligence
  • Semantic and exact-text search across all traces
  • Automatic issue discovery with Slack/email/webhook alerts
  • OpenTelemetry-compatible SDK with no lock-in
  • Automated evals and golden dataset generation
  • Failure-mode clustering and MCP server integration
Use cases
  • ML engineers tracking and comparing training experiments
  • Research teams versioning datasets and model checkpoints
  • Teams building and evaluating LLM-powered applications
  • Organizations collaborating on machine learning projects
  • Monitoring and debugging LLM apps
  • Analyzing model usage and cost
  • Caching responses to cut spend
  • Managing prompts and testing datasets
  • Giving developers governed access to many LLMs
  • Attributing and controlling LLM spend
  • Keeping apps running during provider outages
  • Monitor costs, quality, and latency of AI applications.
  • Route to 250+ LLMs reliably with a single endpoint.
  • Streamline and scale prompt engineering.
  • Enforce reliable LLM behavior with guardrails.
  • Build agents with access to real-world tools.
  • Monitoring AI agents in production
  • Debugging and triaging agent failures
  • Building regression evals from real traffic
  • Getting alerted on new or escalating issues
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