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MiniMax logo
MiniMax
✓ verifiedFreemium

Chinese AGI company building multimodal LLMs, Hailuo video, speech and music models, plus AI apps and open APIs.

4.6M visits/mo
Openlayer logo
Openlayer
✓ verifiedFreemium

AI governance and observability platform with 100+ automated tests and real-time guardrails to evaluate and monitor ML/LLM systems.

24K visits/mo
Maxim AI logo
Maxim AI
✓ verifiedFreemium

End-to-end evaluation and observability platform for building, testing, and monitoring AI agents and LLM apps.

102K visits/mo
ApX Machine Learning logo
ApX Machine Learning
✓ verifiedFreemium

Tools, model specs and courses for LLM engineers-VRAM calculator, benchmarks and model directory-with free and paid tiers.

355K visits/mo
Pricing
Max Token Plan: 119 CNY/mo (frontier models, up to ~7.1B tokens/mo)
Basic: Free (20k inferences/mo, 1 member, 5 projects)
Developer: $0 (3 seats, 10k logs/mo)
Professional: $29/seat/mo (100k logs/mo)
Business: $49/seat/mo (500k logs/mo)

Free trial available

Basic: $0/mo (free forever)
Pro: $19/mo
Pro+: $59/mo
Core features
  • MiniMax M-series LLMs (M3, 1M context, MSA)
  • Hailuo AI video generation
  • Speech and music generation models
  • MiniMax Code agentic coding tool
  • Consumer apps (Hailuo, Xingye)
  • Open API and Token Plan for developers
  • 100+ automated AI tests
  • Offline evaluation and CI/CD for AI
  • Real-time observability and tracing
  • Guardrails against PII leaks, injection, hallucination
  • Data-quality and drift monitoring
  • Compliance/governance alignment
  • Git, SDK, CLI and REST API integration
  • Prompt IDE, versioning, and deployment
  • Agent simulation and evaluation
  • Production tracing and observability
  • Pre-built and custom evaluators
  • Human-in-the-loop evaluation
  • Bifrost LLM gateway
  • VRAM/GPU-memory calculator for LLMs
  • LLM performance rankings and benchmarks
  • Model directory and comparison
  • AI/ML courses and learning roadmap
  • Calculator API and exportable cost reports
  • Engineering blog and guides
Use cases
  • Coding and agentic tasks
  • AI video generation
  • Text-to-speech and music creation
  • Building on MiniMax model APIs
  • Evaluate models before production
  • Monitor live AI systems for issues
  • Prevent unsafe or non-compliant outputs
  • Catch data drift and quality problems
  • Testing and comparing prompts and models
  • Evaluating and simulating AI agents
  • Monitoring agents in production
  • Running human evaluation pipelines
  • Estimating GPU memory before training or inference
  • Comparing and selecting LLMs
  • Learning ML and LLM engineering
  • Modeling production deployment costs
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