Compare tools
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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SiliconFlow
✓ verified
Developer platform serving 200+ optimized LLMs via APIs; high traffic.
434K visits/mo1.1K saves
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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
✕
Weights & Biases
✓ verifiedFreemium
Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.
2.5M visits/mo
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Fiddler AI
✓ verifiedFreemium
Enterprise AI observability and security platform to monitor, evaluate, and govern agentic and ML systems with guardrails.
51K visits/mo
Pricing
No public pricing
Open Source: $0 (self-hosted, 100+ providers)
Free trial available
No public pricing
No public pricing
Free: $0 (real-time guardrails)
Developer: $0.002 per trace
Core features
- ✦Access over 200 optimized models, including LLMs, image, video, and audio processing.
- ✦Achieve low-latency, high-throughput inference with SiliconFlow's self-developed acceleration frameworks.
- ✦Deploy models via serverless inference, dedicated endpoints, or reserved GPUs to suit various workloads.
- ✦Customize models to your data with built-in monitoring and elastic compute resources.
- ✦Ensure data privacy and business security with dynamic scaling and fault tolerance mechanisms.
- ✦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
- ✦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
- ✦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
- ✦End-to-end agentic and ML observability
- ✦Real-time guardrails (hallucination, PII, jailbreak)
- ✦Continuous evaluations and custom judges
- ✦Root-cause analysis and decision lineage
- ✦AI governance, risk, and compliance controls
- ✦Flexible SaaS, VPC, or on-prem deployment
Use cases
- →Quickly deploy various AI models via a simple API, supporting tasks like text, image, audio, and video processing.
- →Utilize serverless GPUs to automatically scale AI applications, ensuring flexibility and cost-efficiency.
- →Access high-performance GPUs for demanding workloads, such as large-scale inference and video generation.
- →Deploy custom models with guaranteed performance and scalability, tailored to specific business needs.
- →Giving developers governed access to many LLMs
- →Attributing and controlling LLM spend
- →Keeping apps running during provider outages
- →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
- →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 production AI agents
- →Enforcing safety guardrails on LLM apps
- →Evaluating and debugging model behavior
- →Governance and compliance for enterprise AI
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