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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.

Groq logo
Groq
✓ verifiedFreemium

Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.

3.6M visits/mo
OpenRouter logo
OpenRouter
✓ verifiedFreemium

Unified API gateway that routes requests to 400+ LLMs across 70+ providers with failover and no subscription.

17M visits/mo
4.4M visits/mo
Modal logo
Modal
✓ verifiedFreemium

Serverless AI cloud for running inference, training and sandboxes on GPUs with fast cold starts and pay-per-use billing.

988K visits/mo
Fiddler AI logo
Fiddler AI
✓ verifiedFreemium

Enterprise AI observability and security platform to monitor, evaluate, and govern agentic and ML systems with guardrails.

51K visits/mo
Pricing
GPT-OSS 20B: $0.075 per 1M input tokens ($0.30 per 1M output)
GPT-OSS 120B: $0.15 per 1M input tokens
Free: $0
Pay-as-you-go: Per-token, no subscription
Enterprise: Talk to sales

No public pricing

Starter: $0/mo + compute ($30 free credit)
Team: $250/mo + compute
Free: $0 (real-time guardrails)
Developer: $0.002 per trace
Core features
  • LPU custom inference hardware
  • GroqCloud tokens-as-a-service API
  • High-speed, low-latency inference
  • Pay-as-you-go token pricing
  • Free API key to start
  • Broad open-model support
  • One unified, OpenAI-compatible API for 400+ models
  • Automatic provider failover for higher uptime
  • Edge routing for low latency
  • Custom data and provider policies
  • Pay-as-you-go credits usable across any model
  • 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
  • Serverless GPU compute defined in Python
  • Sub-second container cold starts
  • Autoscale 0 to 1000+ GPUs
  • Inference, training and batch workloads
  • Secure sandboxes for untrusted code
  • Built-in logging and observability
  • 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
  • Running LLM inference at high speed
  • Cutting inference costs at scale
  • Powering low-latency AI chat apps
  • Serving models via a hosted API
  • Accessing many LLMs through one integration
  • Adding provider redundancy to AI apps
  • Comparing model price and performance
  • Powering agents and AI-native products
  • 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
  • Deploying and scaling model inference
  • Fine-tuning and training models
  • Running batch/parallel AI jobs
  • Executing untrusted code in sandboxes
  • 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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