OpenAI and Anthropic are the two dominant API providers for most production AI workloads. Their pricing structures look similar on the surface — per-token input and output costs — but the actual cost of running a workload can vary dramatically depending on which models you pick and how you use them.
Here's the full breakdown for February 2026, with every model priced, compared, and calculated for real workloads.
[stat] 100× The price gap between OpenAI's cheapest model (GPT-5 Nano at $0.05/M input) and Anthropic's most expensive (Claude Opus 4.6 at $5/M input)
The Complete Lineup
OpenAI Models
OpenAI now has three distinct product lines: the GPT series for general-purpose work, the o-series for reasoning, and the legacy models still hanging around.
GPT-5 family:
- GPT-5.2: $1.75 / $14.00 per 1M tokens — 1M context
- GPT-5.2 pro: $21.00 / $168.00 per 1M tokens — 1M context
- GPT-5.1: $1.25 / $10.00 per 1M tokens — 1M context
- GPT-5: $1.25 / $10.00 per 1M tokens — 1M context
- GPT-5 mini: $0.25 / $2.00 per 1M tokens — 500K context
- GPT-5 nano: $0.05 / $0.40 per 1M tokens — 128K context
Reasoning (o-series):
- o3-pro: $20.00 / $80.00 per 1M tokens — 1M context
- o3: $2.00 / $8.00 per 1M tokens — 1M context
- o4-mini: $1.10 / $4.40 per 1M tokens — 2M context
- o3-mini: $1.10 / $4.40 per 1M tokens — 500K context
Anthropic Models
Anthropic keeps it simpler with a three-tier naming scheme: Opus (flagship), Sonnet (mid-range), and Haiku (fast/cheap).
- Claude Opus 4.6: $5.00 / $25.00 per 1M tokens — 200K context
- Claude Sonnet 4.6: $3.00 / $15.00 per 1M tokens — 1M context
- Claude Sonnet 4.5: $3.00 / $15.00 per 1M tokens — 200K context
- Claude Haiku 4.5: $1.00 / $5.00 per 1M tokens — 200K context
- Claude 3.5 Haiku: $0.80 / $4.00 per 1M tokens — 200K context
💡 Key Takeaway: OpenAI offers 16 models spanning $0.05–$168/M tokens. Anthropic offers 7 models spanning $0.80–$25/M tokens. OpenAI has far more pricing tiers, giving you finer control over cost-quality trade-offs.
Head-to-Head: Equivalent Tiers
The real question isn't "which provider is cheaper" — it's which model at each tier gives you the best cost-to-quality ratio.
Flagship Tier
OpenAI wins on price by a wide margin. GPT-5 costs 75% less on input and 60% less on output. For most tasks where both models perform comparably, GPT-5 is the obvious choice on cost alone. If you need Anthropic's flagship, you're paying a premium — but Opus 4.6 excels at nuanced instruction-following and long-form writing where GPT-5 can feel more formulaic.
For the latest GPT-5 variant, GPT-5.2 at $1.75/$14.00 is still significantly cheaper than Opus while offering newer capabilities including audio input.
Mid-Range Tier
GPT-5 mini at $0.25/$2.00 vs Claude Sonnet 4.6 at $3.00/$15.00.
This is where it gets interesting. GPT-5 mini is 12× cheaper on input and 7.5× cheaper on output — but Sonnet 4.6 is a significantly more capable model. Sonnet competes with flagship models from a year ago. The fairer comparison is GPT-5 vs Sonnet 4.6, where OpenAI is still cheaper at $1.25/$10.00 vs $3.00/$15.00 but the gap narrows to about 2×. See the full comparison.
📊 Quick Math: At 100K requests/month (1,000 input + 500 output tokens each), GPT-5 mini costs $125/month while Claude Sonnet 4.6 costs $1,050/month. That's $925/month saved — but only if GPT-5 mini's quality meets your bar.
Budget Tier
GPT-5 nano at $0.05/$0.40 vs Claude 3.5 Haiku at $0.80/$4.00.
OpenAI dominates the ultra-cheap end. GPT-5 nano is 16× cheaper on input and 10× cheaper on output. Even Claude Haiku 4.5 at $1.00/$5.00 is 20× more expensive on input than nano. If you're doing high-volume extraction, classification, or simple tasks, OpenAI's nano tier is hard to beat on price.
That said, Claude Haiku 4.5 produces noticeably better output quality for tasks requiring nuance. The question is whether that quality gap matters for your specific use case. For structured extraction with clear schemas, GPT-5 nano is fine. For customer-facing responses where tone matters, Haiku's quality may justify the premium.
Reasoning Tier
o3 at $2.00/$8.00 vs Claude Opus 4.6 at $5.00/$25.00.
OpenAI's reasoning models don't have a direct Anthropic equivalent. Anthropic relies on extended thinking within its standard models rather than offering dedicated reasoning-optimized variants. If your workload is reasoning-heavy (math, code analysis, multi-step logic), o3 or o4-mini at $1.10/$4.40 give you specialized performance at lower cost than Opus.
For the most demanding reasoning tasks, o3-pro at $20.00/$80.00 is OpenAI's premium option. It's expensive, but there's nothing comparable in Anthropic's lineup for raw reasoning performance. Learn more about reasoning model costs in our thinking tokens guide.
⚠️ Warning: Reasoning models (o3, o4-mini) generate internal "thinking" tokens that get billed but don't appear in your output. Your actual cost per request can be 2–5× higher than the base token price suggests. Always monitor real token consumption.
Real-World Cost Scenarios
Scenario 1: Customer Support Chatbot (100K conversations/month)
Average: 800 input tokens, 400 output tokens per conversation.
| Model | Monthly Input | Monthly Output | Total |
|---|---|---|---|
| GPT-5 nano | $4.00 | $16.00 | $20 |
| GPT-5 mini | $20.00 | $80.00 | $100 |
| Claude Haiku 4.5 | $80.00 | $200.00 | $280 |
| Claude Sonnet 4.6 | $240.00 | $600.00 | $840 |
For a support chatbot, GPT-5 nano at $20/month is a no-brainer if quality is sufficient. Even stepping up to GPT-5 mini at $100/month saves you 64% over Haiku 4.5. The key test: run 500 real support queries through both models and have your team rate the responses. If nano scores above 80% satisfaction, you just saved $260/month.
Scenario 2: Code Review Pipeline (10K PRs/month)
Average: 3,000 input tokens (diff + context), 1,500 output tokens per review.
| Model | Monthly Input | Monthly Output | Total |
|---|---|---|---|
| o3 | $60.00 | $120.00 | $180 |
| GPT-5 | $37.50 | $150.00 | $188 |
| Claude Sonnet 4.6 | $90.00 | $225.00 | $315 |
| Claude Opus 4.6 | $150.00 | $375.00 | $525 |
For code review, o3 edges out GPT-5 on total cost while offering stronger reasoning about code correctness. Claude Sonnet 4.6 costs 75% more than o3 — hard to justify unless you specifically need Anthropic's coding style. If you're already in the Anthropic ecosystem, Sonnet is reasonable; otherwise, o3 is the clear winner here.
Scenario 3: Content Generation Platform (5K articles/month)
Average: 500 input tokens (brief), 2,000 output tokens per article.
| Model | Monthly Input | Monthly Output | Total |
|---|---|---|---|
| GPT-5 | $3.13 | $100.00 | $103 |
| GPT-5.2 | $4.38 | $140.00 | $144 |
| Claude Sonnet 4.6 | $7.50 | $150.00 | $158 |
| Claude Opus 4.6 | $12.50 | $250.00 | $263 |
Content generation is output-heavy, so the output price matters most. GPT-5 at $10.00/M output vs Sonnet 4.6 at $15.00/M output saves you 35%. But if writing quality is your differentiator, Opus 4.6's output quality may justify the 2.5× premium. Test both with your actual content briefs before committing.
Context Window Comparison
One area where the providers diverge significantly:
| Context Size | OpenAI | Anthropic |
|---|---|---|
| 2M tokens | o4-mini | — |
| 1M tokens | GPT-5.2, GPT-5.1, GPT-5, o3-pro, o3 | Claude Sonnet 4.6 |
| 500K tokens | GPT-5 mini, o3-mini | — |
| 200K tokens | GPT-4.1, GPT-4o | Claude Opus 4.6, Sonnet 4.5, Haiku 4.5 |
| 128K tokens | GPT-5 nano, GPT-4o mini | Claude 3.5 Haiku |
If you're processing entire codebases or long documents, OpenAI gives you more room across more price points. Anthropic's 200K context on Opus 4.6 is still generous for most use cases, but the gap matters for specific workloads like repository-wide code analysis or processing entire books.
💡 Key Takeaway: OpenAI offers context windows up to 2M tokens (o4-mini) with most flagship models at 1M. Anthropic tops out at 1M tokens on a single model (Sonnet 4.6). For long-context workloads, OpenAI has a clear structural advantage.
Prompt Caching and Batch Discounts
Both providers offer ways to cut costs beyond the base token price:
OpenAI Prompt Caching: Automatically caches repeated prompt prefixes at 50% discount on input tokens. No configuration needed — if your requests share a common system prompt, you're already saving.
OpenAI Batch API: Submit non-urgent requests in batches for a 50% discount on all token costs. If your workload can tolerate 24-hour turnaround, this effectively halves your bill. Read our Batch API guide for implementation details.
Anthropic Prompt Caching: Requires explicit cache headers, but offers up to 90% discount on cached input tokens. The initial cache write costs 25% more, so it only pays off if you reuse the same context 3+ times. Anthropic's caching is more manual but potentially cheaper for high-reuse patterns.
📊 Quick Math: A production chatbot sending the same 2,000-token system prompt on every request makes 100K calls/month. Without caching: $500 in system prompt costs on Claude Sonnet 4.6. With Anthropic's 90% cache discount: $50. That's $450/month saved from one optimization.
When to Use Which
Choose OpenAI when:
- Cost is your primary constraint (GPT-5 nano and mini are unmatched on price)
- You need massive context windows (1M–2M tokens)
- Reasoning-heavy workloads benefit from the o-series
- High-volume, simple tasks where nano saves thousands per month
- You want batch processing discounts (50% off via Batch API)
Choose Anthropic when:
- Output quality for writing and nuanced tasks is critical
- You value consistent instruction-following over raw speed
- Your workload fits within 200K context (most do)
- You prefer Anthropic's safety approach and content policies
- You need computer use capabilities (Sonnet 4.6 exclusive)
Mix both when:
- Route simple tasks to GPT-5 nano, complex ones to Claude Opus 4.6
- Use OpenAI for extraction/classification, Anthropic for generation
- A tiered approach can cut costs 40–60% versus using a single premium model
For a broader multi-provider comparison including Google and DeepSeek, check our Gemini vs GPT-5 vs Claude guide.
The Bottom Line
OpenAI is cheaper across every tier, sometimes dramatically so. But cheaper isn't always better — Anthropic's models earn their premium on specific workloads where quality and reliability matter more than cost per token.
The smartest approach is model routing: use the cheapest model that meets your quality bar for each task type. A support chatbot doesn't need Opus. A legal document review probably does. The best budget models can handle the bulk of your traffic at a fraction of the cost.
✅ TL;DR: OpenAI is 2–16× cheaper than Anthropic at every tier. Use GPT-5 nano ($0.05/$0.40) for high-volume simple tasks, GPT-5 ($1.25/$10) for general purpose, and Claude Opus 4.6 ($5/$25) only when quality justifies the premium. Mix providers with model routing for 40–60% savings.
Run your own numbers with real traffic data. Try the AI Cost Check calculator to compare costs across your actual usage patterns.
Frequently asked questions
Is OpenAI or Anthropic cheaper for AI API usage?
OpenAI is cheaper at every price tier. Their cheapest model (GPT-5 Nano) costs $0.05/$0.40 per million tokens, while Anthropic's cheapest (Claude 3.5 Haiku) costs $0.80/$4.00 — a 16× difference on input. At the flagship level, GPT-5 at $1.25/$10.00 is 4× cheaper on input than Claude Opus 4.6 at $5.00/$25.00.
When should I choose Anthropic over OpenAI despite higher prices?
Choose Anthropic when output quality is your top priority — particularly for nuanced writing, complex instruction-following, and tasks where tone matters. Claude Opus 4.6 consistently outperforms GPT-5 on long-form content generation and detailed analysis. Also choose Anthropic if you need Sonnet 4.6's computer use capabilities for browser automation.
How much can I save by mixing OpenAI and Anthropic models?
A mixed-provider strategy typically saves 40–60% compared to using a single premium model. Route high-volume, simple tasks (classification, extraction) to GPT-5 Nano at $0.05/M input, and send only complex tasks (reasoning, creative writing) to Claude Opus 4.6. Use our calculator to model your specific mix.
What's the best model for a startup on a tight budget?
Start with GPT-5 Nano ($0.05/$0.40) for prototyping and simple tasks — a chatbot handling 10,000 conversations/day costs just $20/month. Scale up to GPT-5 Mini ($0.25/$2.00) when you need better quality. Only move to premium models like Claude Sonnet 4.6 ($3/$15) once you've validated that the quality improvement drives measurable business value.
Do OpenAI and Anthropic charge differently for cached prompts?
Yes, and the approaches differ significantly. OpenAI applies prompt caching automatically with a 50% input discount — no code changes needed. Anthropic requires explicit cache headers but offers up to 90% input discount for cached content. Anthropic's approach saves more per cached token but requires engineering effort to implement. For details, see our cost optimization guide.