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.

BoltAI logo
BoltAI
✓ verifiedPaid

Native macOS app that unifies 300+ AI models in one private workspace with agents, MCP tools, and one-time licensing.

81K visits/mo33K saves
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
Deep Infra logo
Deep Infra
✓ verifiedPaid

Low-cost inference cloud with developer APIs to run open ML models and on-demand GPUs, billed pay-per-use.

375K visits/mo
Claude logo
Claude
✓ verifiedFreemium

Anthropic's AI assistant for writing, coding, and analysis across web, mobile, and desktop, plus a developer API.

22M visits/mo231K saves
Pricing
Essential: $79 (1 seat, one-time)
Pro: $99 (2 seats + 1 mobile, one-time)
Team Perpetual: $99/seat/year

Free trial available

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

Free: $0
Pro: $17/month billed annually ($200 up front), or $20/month
Max: From $100/month
Team: $20/seat/month billed annually ($25 monthly); premium seats $100/seat/month annually ($125 monthly)
Enterprise: Contact sales
Core features
  • Switch across 300+ hosted and local AI models
  • Native macOS app with global shortcut and screenshot-to-answer
  • Reusable agents, projects, and forked chats
  • Multimodal analysis of PDFs, images, and code
  • MCP tools and code execution
  • Local chat storage with encryptable API keys
  • 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
  • Hosted inference for many open models
  • Simple REST/OpenAI-compatible API
  • Pay-per-token or per-time billing
  • On-demand GPU rental
  • Broad catalog (Llama, DeepSeek, Qwen, Flux, etc.)
  • DeepStart and DeepCluster tooling
  • Conversational writing and editing
  • Code generation and debugging (Claude Code)
  • Data analysis and visualization
  • Web search plus memory across chats
  • Connectors and remote MCP integrations
  • Extended thinking for complex tasks
Use cases
  • Using multiple AI providers in one place
  • Explaining or fixing on-screen content instantly
  • Building reusable task-specific agents
  • Analyzing documents and screenshots privately
  • Serving open models in production apps and agents
  • Fine-tuning models on private data
  • Powering code assistants, chatbots and RAG at scale
  • Serving open-source models via API
  • Building AI apps cost-efficiently
  • Renting GPUs for inference or training
  • Scaling inference up and down on demand
  • Drafting and refining written content
  • Building and debugging software
  • Analyzing datasets for insights
  • Research and learning support
  • Team and enterprise automation
Visit
More in AI Agents Infrastructure