Compare tools
Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
⇄ Comparison dimension — pick the market you're actually shopping in
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liteLLM
✓ verifiedFreemium
Open-source AI gateway giving dev teams unified access, fallbacks and spend tracking across 100+ LLMs.
703K visits/mo
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Helicone
✓ verifiedFreemium
LLM observability platform and AI gateway that lets teams route, log, debug and analyze their model requests.
100K visits/mo
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LangWatch
✓ verifiedFreemium
Platform to test, evaluate and observe LLM and voice AI agents, with prompt management and red-teaming for production.
23K visits/mo6.4K saves
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Weights & Biases
✓ verifiedFreemium
Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.
2.5M visits/mo
Pricing
No public pricing
Open Source: $0 (self-hosted, 100+ providers)
Free trial available
Hobby: Free (10,000 requests/mo)
Pro: $79/mo (unlimited seats)
Team: $799/mo (SOC-2 & HIPAA)
Free trial available
Developer: €0 (50k events/mo)
Growth: €29/core-seat/mo (+ €5 per 100k events)
No public pricing
Core features
- ✦Dialogue with GLM large model
- ✦AI search
- ✦AI drawing
- ✦AI reading
- ✦AI-generated video (沉思清影-AI生视频)
- ✦AI-generated PPT
- ✦Data analysis tools
- ✦Code assistance (代码速写)
- ✦Intelligent agents
- ✦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
- ✦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
- ✦Scenario-based agent testing
- ✦LLM evaluation and quality scoring
- ✦Observability for cost and latency
- ✦Prompt management with GitHub sync
- ✦Voice AI simulation
- ✦LLM red-teaming and governance
- ✦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
Use cases
- →Engaging in conversations with an AI model
- →Generating images and videos using AI
- →Creating presentations with AI assistance
- →Analyzing data with AI tools
- →Assisting with code development
- →Giving developers governed access to many LLMs
- →Attributing and controlling LLM spend
- →Keeping apps running during provider outages
- →Monitoring and debugging LLM apps
- →Analyzing model usage and cost
- →Caching responses to cut spend
- →Managing prompts and testing datasets
- →Catch agent issues before production
- →Evaluate and monitor LLM quality
- →Test voice AI agents at scale
- →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
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