toolspool

Compare tools

Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

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
Kiro AI logo
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
Fireworks AI logo
Fireworks AI
✓ verifiedPaid

Developer platform for fast serverless inference and training of open generative models, billed per token or GPU-second.

611K visits/mo1.3K saves
Lightning  AI logo
Lightning AI
✓ verifiedFreemium

Cloud platform from the makers of PyTorch Lightning for building, training and deploying AI in browser-based GPU Studios.

467K visits/mo3.8K saves
Pricing
Max Token Plan: 119 CNY/mo (frontier models, up to ~7.1B tokens/mo)
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)
On-Demand H100/H200: $7/GPU-hour
On-Demand B200: $10/GPU-hour
On-Demand B300: $12/GPU-hour
Fine-tuning (LoRA SFT, models up to 16B): from $0.50 per 1M training tokens

No public pricing

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
  • 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
  • Serverless per-token inference with OpenAI/Anthropic-compatible APIs
  • On-demand dedicated and reserved GPU deployments
  • Fine-tuning and reinforcement-learning training pipelines
  • Large library of open LLM, vision, image and audio models
  • Optimized inference engine for throughput and latency
  • Browser-based Lightning Studios with on-demand GPUs
  • PyTorch Lightning training framework
  • Model training, fine-tuning and deployment
  • Collaborative, shareable ML environments
  • Scalable multi-GPU/multi-node compute
Use cases
  • Coding and agentic tasks
  • AI video generation
  • Text-to-speech and music creation
  • Building on MiniMax model APIs
  • Turning prompts into maintainable, spec-matched code
  • Catching bugs unit tests miss
  • Reviewing PRs and fixing bugs in CI/CD
  • Serving open models in production apps and agents
  • Fine-tuning models on private data
  • Powering code assistants, chatbots and RAG at scale
  • Prototype and train ML models in the cloud
  • Fine-tune and deploy foundation models
  • Run reproducible AI experiments collaboratively
Visit
More in Model Hosting Inference