Compute Comparison
Enterprise tier$5.00 – $75.00 / 1M tokens

Frontier LLM Pricing for Enterprise AI Workloads

Frontier-tier models at $5–$75/M tokens. The highest intelligence scores, longest context windows, and strongest reasoning capabilities — for enterprise workflows where quality is non-negotiable.

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Top picks
Ideal use cases
  • Complex legal, medical, and financial document analysis
  • State-of-the-art code generation and architecture review
  • Research and scientific reasoning pipelines
  • Enterprise agentic systems with high-stakes decisions
  • Multi-modal workflows combining vision and reasoning
  • Long-context analysis of entire codebases or reports
Budget guide

Enterprise-tier models cost $5–$75/M tokens. Most enterprise teams spend $5,000–$50,000/month. Volume discounts and prompt caching (up to 90% off) are critical at this scale.

Not the right tier if you need…
  • High-volume, low-complexity tasks (use Starter)
  • Cost-sensitive consumer applications
  • Simple classification or extraction pipelines

Enterprise-tier models(0)

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Frequently asked questions

Which frontier model has the highest intelligence score?

As of July 2026, Claude Opus 4.5 leads with a score of 90, followed by Gemini 2.5 Pro (87) and o3 (88). The best choice depends on your specific task — coding, reasoning, or vision.

Is Claude Opus or GPT-4o better for enterprise use?

Claude Opus 4.5 scores higher on reasoning and coding benchmarks. GPT-4o offers broader ecosystem integrations and a lower price point. For pure capability, Opus leads; for ecosystem fit, GPT-4o is often preferred.

How do enterprise LLM contracts differ from pay-as-you-go?

Enterprise contracts typically offer committed-use discounts (20–50%), SLA guarantees, data privacy agreements (no training on your data), and dedicated capacity. Minimum commitments usually start at $10K/month.

What is a reasoning model and when should I use one?

Reasoning models (o3, o4-mini, Claude Opus 4.5) use chain-of-thought internally before responding. They score significantly higher on math, coding, and logic tasks but have higher latency (2–8s TTFT) and cost more per output token.