OpenAI vs Anthropic API Pricing in 2026

OpenAI vs Anthropic API Pricing: Quick Summary

OpenAI vs Anthropic API pricing is a decision every team building with LLMs has to navigate. The raw numbers matter — but the right choice depends heavily on your workload type, volume, and context window requirements. This page breaks down the 2026 pricing for both providers and explains which scenarios favor each.

Bottom line: Anthropic's Claude 3.5 Sonnet is cheaper than GPT-4o at the frontier tier. OpenAI's o3-mini is the best value for reasoning-heavy tasks. Both providers offer cheap small models (GPT-4o-mini and Claude Haiku) that cost 20–30× less than their flagship models.

Full Pricing Comparison Table (2026)

All prices are per million tokens as of early 2026. Prices change — verify at each provider's pricing page before committing to architecture decisions.

OpenAI Models

| Model | Input ($/1M tokens) | Output ($/1M tokens) | Context Window | |-------|--------------------|-----------------------|----------------| | GPT-4o | $5.00 | $15.00 | 128K | | GPT-4o mini | $0.15 | $0.60 | 128K | | o1 | $15.00 | $60.00 | 200K | | o1-mini | $3.00 | $12.00 | 128K | | o3-mini | $1.10 | $4.40 | 200K | | GPT-3.5 Turbo | $0.50 | $1.50 | 16K |

Anthropic Models

| Model | Input ($/1M tokens) | Output ($/1M tokens) | Context Window | |-------|--------------------|-----------------------|----------------| | Claude 3.5 Sonnet | $3.00 | $15.00 | 200K | | Claude 3.5 Haiku | $0.80 | $4.00 | 200K | | Claude 3 Opus | $15.00 | $75.00 | 200K | | Claude 3 Sonnet | $3.00 | $15.00 | 200K | | Claude 3 Haiku | $0.25 | $1.25 | 200K |

Key Observations

Claude 3.5 Sonnet beats GPT-4o on input cost — $3 vs $5 per million tokens, with equal output pricing ($15). For input-heavy workloads (long documents, large context RAG), this is a 40% cost difference.
Claude Haiku 3 is the cheapest quality option at $0.25/$1.25 — cheaper than GPT-4o-mini for input. But GPT-4o-mini's output is cheaper ($0.60 vs $1.25).
o1 is extremely expensive — $15/$60 per million tokens. Reserve it for tasks that genuinely require deep multi-step reasoning. Most use cases do not.
o3-mini is the best reasoning value — At $1.10/$4.40, it delivers o1-class reasoning at a fraction of the price. For code generation, math, and structured reasoning tasks, test o3-mini before assuming you need the full o1.
Anthropic's 200K context is consistent across tiers — Even Claude Haiku gets 200K context. OpenAI's small model (GPT-4o-mini) is limited to 128K.

Cost Modeling by Workload Type

Customer Support Chatbot (High Volume)

Assume 1,000 support tickets per day. Average: 500 input tokens + 300 output tokens per conversation.

| Model | Daily Cost | Monthly Cost | |-------|-----------|-------------| | GPT-4o | $9.00 | $270 | | Claude 3.5 Sonnet | $6.00 | $180 | | GPT-4o-mini | $0.27 | $8.10 | | Claude 3.5 Haiku | $0.52 | $15.60 | | Claude 3 Haiku | $0.22 | $6.60 |

Winner for high-volume chat: Claude 3 Haiku or GPT-4o-mini. For most customer support use cases, these models are sufficient and cost 95% less than frontier models.

Long-Document Analysis (RAG / Contract Review)

Assume 100 documents per day. Average: 50,000 input tokens + 1,000 output tokens per document.

| Model | Daily Cost | Monthly Cost | |-------|-----------|-------------| | GPT-4o | $25.15 | $754 | | Claude 3.5 Sonnet | $15.15 | $454 | | GPT-4o-mini | $0.82 | $24.60 | | Claude 3.5 Haiku | $4.04 | $121 |

Winner for long documents: Claude 3.5 Sonnet on cost. GPT-4o-mini is cheapest but may not maintain quality on complex long-form analysis — test it on your actual documents first.

Code Generation and Review

Assume 500 code tasks per day. Average: 2,000 input tokens + 800 output tokens.

| Model | Daily Cost | Monthly Cost | |-------|-----------|-------------| | GPT-4o | $11.00 | $330 | | o3-mini | $4.60 | $138 | | Claude 3.5 Sonnet | $9.00 | $270 | | Claude 3.5 Haiku | $4.00 | $120 |

Winner for code tasks: o3-mini or Claude 3.5 Haiku. Both deliver strong coding performance at a much lower price point. For complex architectural reasoning, test o3-mini explicitly — it often punches above its price.

Prompt Caching: A Hidden Cost Lever

Both providers offer prompt caching that can dramatically reduce costs for applications with repeated system prompts or large shared context.

OpenAI caches prompts automatically for inputs over 1,024 tokens. Cache hits are billed at 50% of the standard input rate.
Anthropic offers explicit cache control with cache_control headers. Cached tokens are billed at ~10% of the standard input rate, with a small cache write fee.

For applications with a large, stable system prompt (e.g., a RAG system with shared instructions and few-shot examples), Anthropic's more aggressive caching discount makes Claude significantly cheaper in practice than the base pricing suggests.

A 10,000-token system prompt sent 10,000 times per day:

Without caching: $30/day (at Claude 3.5 Sonnet input rates)
With Anthropic caching: ~$3/day + small write cost

If your application has this pattern, factor caching into your cost model.

Batch API Pricing

Both providers offer async batch processing at a 50% discount for workloads that don't need real-time responses:

OpenAI Batch API: 50% discount on input and output tokens
Anthropic Message Batches API: 50% discount on input and output tokens

For offline tasks (bulk document classification, nightly report generation, data enrichment pipelines), batch APIs cut your LLM cost in half with no quality trade-off.

Deployment Path: Direct API vs Cloud Providers

Pricing above reflects direct API access. Both providers are also available through major cloud platforms:

| Platform | Provider | Notes | |----------|----------|-------| | AWS Bedrock | Anthropic, Meta, Cohere, Mistral | Slightly higher pricing; unified billing, IAM, VPC | | Azure OpenAI | OpenAI | Enterprise SLA, dedicated capacity available | | Google Vertex AI | Anthropic, Google | GCP-native billing, regional availability |

Cloud-hosted models typically cost 10–20% more than direct API access, but offer unified billing, compliance infrastructure, and dedicated throughput. For enterprises already on AWS or GCP, the convenience usually outweighs the price premium. See our AWS Bedrock vs Azure OpenAI comparison for a full breakdown.

Which Provider Should You Choose?

| Your Situation | Recommended Choice | |---------------|-------------------| | Long-document processing (>50K tokens) | Anthropic Claude — cheaper input, larger context | | High-volume simple tasks | Claude 3 Haiku or GPT-4o-mini — comparable cost | | Complex reasoning / math / code | o3-mini — best cost-performance for reasoning | | Multimodal (audio, image generation) | OpenAI — broader multimodal ecosystem | | AWS-first infrastructure | Claude on Bedrock — native IAM, unified billing | | Azure-first infrastructure | OpenAI on Azure — enterprise SLA, Microsoft stack |

Cost Optimization Checklist

Before finalizing your model choice and pricing model:

[ ] Test both models on your actual eval set — pricing means nothing if quality differs
[ ] Enable prompt caching if you have a stable system prompt over 1,024 tokens
[ ] Use batch API for all non-real-time workloads
[ ] Model route — cheap model for simple queries, expensive model only when necessary
[ ] Set a spend alert before you go to production — API costs scale with usage instantly
[ ] Monitor token counts per request — unexpected cost spikes are usually prompt bloat

[Unsure which model fits your budget and workload? Book a 15-min architecture call → — we'll help you model your costs before you build.]

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