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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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Inference Providers Hardware Infrastructure Coding Agents AI Security Guardrails Model Hosting Inference AI Agents AI Agents Infrastructure

CometAPI

✓ verifiedPaid

Unified API to 500+ AI models (OpenAI, Anthropic, Google, etc.) with OpenAI-compatible calls priced ~20% below official rates.

363K visits/mo4.8K saves

ZenMux

✓ verifiedPaid

Enterprise unified API gateway giving one integration point to 100+ LLMs like Claude, GPT, and Gemini with reliability guarantees.

435K visits/mo11K saves

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

Kiro AI

✓ verifiedFreemium

Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.

3.8M visits/mo

hCaptcha

✓ verifiedFreemium

Privacy-focused CAPTCHA and bot/fraud-detection service, a drop-in reCAPTCHA alternative for websites and apps.

4.4M visits/mo

Pricing

Pay-as-you-go, min top-up $10

GPT-5.6: $4 / 1M tokens

Claude Sonnet 5: $1.6 / 1M tokens

Free trial available

No public pricing

Starter: $0/mo + compute ($30 free credit)

Team: $250/mo + compute

Free: $0/mo (50 credits)

Pro: $20/user/mo (1,000 credits)

Pro+: $40/user/mo (2,000 credits)

Pro Max: $100/user/mo (5,000 credits)

Power: $200/user/mo (10,000 credits)

Basic: Free

Pro: $139/month billed monthly, $99/month billed yearly

Enterprise: Contact sales

Free trial available

Core features

✦One key for 500+ models
✦OpenAI-compatible API
✦Pay-as-you-go credits (~20% below list)
✦Multimodal: text, image, video, audio
✦Usage analytics and budget alerts
✦Integrations (Claude Code, n8n, Zapier, etc.)

✦Unified API for 100+ AI models
✦Intelligent request routing across models
✦AI Model Insurance for quality/reliability guarantees
✦Enterprise-focused LLM access layer

✦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

✦Spec-driven development (requirements, design, tasks)
✦Parallel agents, local or cloud
✦Property-based and correctness testing
✦Works in IDE, CLI, web and mobile
✦Multiple models (Claude, open-weight, Auto)
✦Headless CLI for CI/CD
✦Context from tools like Figma and Terraform

✦AI bot detection
✦Transaction fraud protection
✦Account-takeover (ATO) defense
✦Pull-based SMS MFA
✦Private Learning ML risk models
✦Two-line reCAPTCHA migration
✦Hundreds of integrations

Use cases

→Consolidating multi-provider AI billing
→Switching models without re-integration
→Powering apps and automation pipelines
→Benchmarking models in one playground

→Building applications that need failover across multiple LLM providers
→Consolidating billing/access to many AI models under one API
→Enterprises requiring guaranteed model output reliability

→Deploying and scaling model inference
→Fine-tuning and training models
→Running batch/parallel AI jobs
→Executing untrusted code in sandboxes

→Turning prompts into maintainable, spec-matched code
→Catching bugs unit tests miss
→Reviewing PRs and fixing bugs in CI/CD

→Blocking bots and spam signups
→Preventing account takeover
→Reducing transaction and payment fraud
→Stopping credential stuffing

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