The major providers of Large Language Models for building AI-powered product features. Each offers different strengths in reasoning, cost, speed, and specialized capabilities.
| Tool | Best For | Pricing |
|---|---|---|
| OpenAI (GPT-4) | Broadest capabilities, best tool/function calling, largest ecosystem | GPT-4o-mini $0.15/1M in, GPT-4o $2.50/1M in |
| Anthropic (Claude) | Long-context tasks, content generation, and nuanced conversations | Haiku $0.25/1M in, Sonnet $3/1M in, Opus $15/1M in |
| Google (Gemini) | Multimodal applications and Google Cloud-integrated workflows | Flash $0.075/1M in, Pro $1.25/1M in |
| Mistral | Cost-efficient inference and self-hosting with open weights | Small $0.10/1M in, Medium $0.40/1M in, Large $2/1M in |
| Meta (Llama) | Full data control, custom fine-tuning, and eliminating API costs | Free (open-source, self-hosted compute costs) |
The most widely adopted LLM platform with models ranging from GPT-4o-mini (fast, cheap) to GPT-4 Turbo (most capable). Strongest ecosystem of tools and integrations.
GPT-4o-mini $0.15/1M in, GPT-4o $2.50/1M in
Broadest capabilities, best tool/function calling, largest ecosystem
Claude models with 200K token context windows, strong instruction following, and nuanced writing quality. Excels at long-document analysis and content generation.
Haiku $0.25/1M in, Sonnet $3/1M in, Opus $15/1M in
Long-context tasks, content generation, and nuanced conversations
Gemini models with native multimodal capabilities (text, image, video, audio). Deep integration with Google Cloud services and competitive pricing.
Flash $0.075/1M in, Pro $1.25/1M in
Multimodal applications and Google Cloud-integrated workflows
European AI lab offering efficient models with strong performance-to-cost ratios. Open-weight models available for self-hosting alongside managed API access.
Small $0.10/1M in, Medium $0.40/1M in, Large $2/1M in
Cost-efficient inference and self-hosting with open weights
Open-source Llama models that can be self-hosted for full control over data and costs. Community fine-tunes available for specialized tasks.
Free (open-source, self-hosted compute costs)
Full data control, custom fine-tuning, and eliminating API costs
Spending $10K+/month on OpenAI or Anthropic? Here are the exact tactics that reduced our LLM costs from $15K to $3K/month without sacrificing quality.
Forget the 'act as an expert' templates. After shipping dozens of LLM features in production, here are the prompt engineering techniques that actually improve outputs, reduce costs, and scale reliably.
An honest look at when each approach makes sense, with real cost comparisons and performance data.