§ Guide · No. 04April 2026

OpenAI vs Claude API pricing.

Side-by-side for every current model, in the tier each belongs to, with cost-equivalence math on four real workloads. If you're choosing between providers or considering a migration, the decision lives below.

§ TL;DR

At every tier, OpenAI is cheaper by 10–30%. GPT-4o mini ($0.15/$0.60) is 85% cheaper than Claude Haiku 4.5 ($1/$5) for input-heavy work. GPT-4o ($2.50/$10) undercuts Claude Sonnet 4.6 ($3/$15). Claude Opus 4.7 output costs 25% more than o1 output.

Claude wins on context and often on long-document work. Every Claude model has a 200K-token context window. OpenAI's flagships cap at 128K. For RAG with large chunks, legal/contract analysis, or summarizing books, Claude's context advantage can outweigh the price premium.

§ Pricing, by tier

Side-by-side, per million tokens

§ Frontier tier
ModelInputOutputContext
Oo1$15.00$60.00200K
AClaude Opus 4.7$15.00$75.00200K
§ Flagship tier
ModelInputOutputContext
OGPT-4 Turbo$10.00$30.00128K
OGPT-4o$2.50$10.00128K
AClaude Sonnet 4.6$3.00$15.00200K
§ Balanced tier
ModelInputOutputContext
Oo1 mini$3.00$12.00128K
Oo3 mini$1.10$4.40128K
§ Efficient tier
ModelInputOutputContext
AClaude Haiku 4.5$1.00$5.00200K
OGPT-4o mini$0.15$0.60128K
OGPT-3.5 Turbo$0.50$1.5016K

Prices in USD per 1,000,000 tokens. Context is maximum combined input-plus-output window. “O” = OpenAI, “A” = Anthropic.

§ Capabilities — not just price

Where each provider leads

Pricing is only one axis. A cheaper model that can't do what your workload needs is not actually cheaper.

Context window
OpenAI128K on flagship; 200K on o1
Claude200K on every current model
Claude
Output rate limits
OpenAIHigher token-per-minute limits at tier 4+
ClaudeLower output rate limits; generous daily quotas
OpenAI for high-throughput
Vision
OpenAIAvailable on 4o, 4-turbo, o1; mini has limited support
ClaudeAvailable on all current Claude 4.x models
Comparable
Tool / function calling
OpenAIMature; strict mode available
ClaudeMature; similar shape, slightly different schema
Comparable
Structured outputs (JSON schema)
OpenAINative strict mode; high reliability
ClaudeAvailable; schema-conformance quality matches
Comparable
Batch API discount
OpenAI50% off; up to 24-hour turnaround
Claude50% off; up to 24-hour turnaround
Tie
Prompt caching
OpenAIAutomatic caching on repeated prefixes; discount varies
ClaudeExplicit caching via API; 90% discount on cached reads
Claude (larger, explicit discount)
Fine-tuning
OpenAIAvailable on gpt-4o and gpt-4o-mini; per-token premium
ClaudeNot generally available to individual developers
OpenAI
Frontier reasoning benchmarks
OpenAIo1 leads on math, code, complex reasoning
ClaudeOpus leads on long-context comprehension, writing
Workload-dependent
§ Cost equivalence — four real workloads

Same workload, both providers

Per-million-token rates are hard to intuit. Monthly dollars on your actual workload are not. Each row below runs the same job on the comparable tier from each provider.

Customer support chatbot
1,000 input / 500 output tokens. 2,000 conversations/day.
OpenAIGPT-4o mini$27.00/mo
ClaudeClaude Haiku 4.5$210.00/mo
OpenAI is $183.00/mo cheaper (87% lower)
RAG application
8,000 input / 800 output tokens. 300 queries/day.
OpenAIGPT-4o$252.00/mo
ClaudeClaude Sonnet 4.6$324.00/mo
OpenAI is $72.00/mo cheaper (22% lower)
Frontier reasoning agent
3,000 input / 4,000 output tokens. 200 runs/day.
OpenAIo1$1710.00/mo
ClaudeClaude Opus 4.7$2070.00/mo
OpenAI is $360.00/mo cheaper (17% lower)
High-volume classifier
500 input / 50 output tokens. 50,000 requests/day.
OpenAIGPT-4o mini$157.50/mo
ClaudeClaude Haiku 4.5$1125.00/mo
OpenAI is $967.50/mo cheaper (86% lower)

Assumes 30-day months with flat daily request volume. Real workloads are bursty; real bills have spikes. Use the calculator to model your own shape.

§ The decision, simplified

Pick OpenAI or Claude based on your workload shape

Cost-minimizing, simple tasks
OpenAI — GPT-4o mini
85% cheaper than Claude Haiku 4.5 at efficient tier. Good enough for classification, routing, moderation.
High-volume classifier
OpenAI — GPT-4o mini or o3 mini
Lowest per-request cost at scale; batch API discount applies.
Long-document / contract analysis
Claude — Sonnet 4.6 or Opus 4.7
200K context window on every Claude model; GPT-4o maxes at 128K. Fewer chunks, cleaner retrieval.
General-purpose production SaaS
OpenAI — GPT-4o
20–30% cheaper than Claude Sonnet at comparable quality. Wider ecosystem, more tutorials.
Math / code / complex reasoning
OpenAI — o1 or o1 mini
Reasoning benchmarks favor o1; 20% cheaper output than Claude Opus.
Long-form writing / RAG on long docs
Claude — Sonnet 4.6
Strong long-form generation; large context reduces retrieval burden.
Heavy prompt caching workload
Claude — any tier
90% discount on cached reads via explicit cache-control headers.
Need fine-tuning
OpenAI — GPT-4o or GPT-4o mini
Fine-tuning not widely available on Claude.
§ Migrating between providers

The real cost of switching

For most production services, migrating between OpenAI and Claude is a 4–8 hour engineering task per service — not a multi-week project. Here's what actually changes:

SDK shape

Anthropic's SDK mirrors OpenAI's on most patterns: messages, streaming, system prompts, tools. Biggest difference: no completions endpoint — everything goes through messages. System prompt is a top-level field, not a message role.

Tool use

Similar concept, slightly different schema. OpenAI calls tool results tool messages; Claude calls them tool_result content blocks. Migration is mechanical — a search-and-replace over your tool-call dispatching code.

Prompt portability

Prompts often transfer with minimal changes. Claude tends to prefer XML-tagged structure (<instructions>...</instructions>) in its system prompts; GPT prefers plain-text delimiters. A well-written GPT prompt will usually work on Claude with minor formatting nudges — but re-evaluate on your test set, because token counts differ between tokenizers.

Evaluation cost

Budget 1–2 days to re-run your eval suite on the new provider. Quality-neutral migrations are common; quality-different migrations happen and need to be caught. Running evals in Batch API mode halves this cost.

Rate limit tier reset

Each provider has its own rate limit tier system. A migration to Claude starts you at tier 1 regardless of your OpenAI usage history. Scale up gradually; tier progression typically takes 1–2 weeks of sustained traffic.

§ Tracking spend across both

One cap, two providers

If you run both — dual-provider is common for redundancy or workload-specific optimization — your monthly exposure is the sum. The provider dashboards each show only their own bill. You need something that sums them.

Capped reads from OpenAI's /v1/organization/costs endpoint and Anthropic's /v1/organizations/cost_report endpoint in the same sync, aggregates into a single monthly total, and fires one desktop notification at 80%, 100%, and 150% of your combined cap. Read-only admin keys. Keys stay in your browser on the free tier.

§ FAQ

Frequently asked

Which is cheaper: OpenAI or Claude API?

It depends on the tier. At the efficient tier, GPT-4o mini ($0.15/$0.60 per million tokens) is the cheapest option on either provider. At the flagship tier, GPT-4o ($2.50/$10) is cheaper than Claude Sonnet 4.6 ($3/$15). At the frontier tier, OpenAI's o1 ($15/$60) is cheaper than Claude Opus 4.7 ($15/$75) because Opus's output rate is 25% higher. For high-output workloads, OpenAI is consistently cheaper at comparable quality tiers.

Is GPT-4o or Claude Sonnet better for general-purpose work?

Both are flagship models with similar capabilities. GPT-4o is cheaper ($2.50/$10 vs $3/$15). Claude Sonnet 4.6 has a 200K-token context window (vs GPT-4o's 128K) and is often preferred for long-document analysis. For cost-sensitive general work, GPT-4o. For long-context work, Claude Sonnet.

What's the cheapest Claude model?

Claude Haiku 4.5, at $1 per million input tokens and $5 per million output tokens. It has a 200K-token context window (larger than GPT-4o mini's 128K) but is more expensive per token. For cost-minimizing workloads, GPT-4o mini at $0.15/$0.60 is still cheaper.

How does Claude Opus compare to OpenAI o1?

Both are frontier reasoning models at the top of each provider's pricing. o1 is $15/$60 per million tokens; Opus 4.7 is $15/$75. Input prices are identical, but Opus's output is 25% more expensive. In benchmarks, Opus often leads on long-context reasoning and complex analysis; o1 leads on math and code where its reasoning tokens earn their keep. Your choice depends on workload — run evals on your specific prompts.

Can I migrate from OpenAI to Claude without rewriting my code?

Mostly yes. Anthropic's SDK has a similar shape to OpenAI's — messages, system prompt, tools, streaming. Key differences: Anthropic does not use the 'completions' endpoint (messages-only), tool-use schemas are slightly different, and system prompts are passed as a separate field rather than a message. Budget 4–8 hours per production service for a clean migration. Both providers support vision, tool calling, and structured output — capability parity is high.

Does Claude have a Batch API like OpenAI?

Yes. Anthropic's Batch API offers 50% off list pricing for asynchronous workloads with 24-hour turnaround, matching OpenAI's. For bulk embeddings, offline evaluation, and nightly enrichment, both providers offer the same discount structure.

Can one tool track both OpenAI and Claude costs?

Yes. Capped is a Chrome extension that tracks both providers from the same interface. It uses OpenAI's /v1/organization/costs endpoint and Anthropic's /v1/organizations/cost_report endpoint — both require read-only organization admin keys. Monthly cap is set in dollars; desktop notifications fire at 80%, 100%, and 150% of the cap regardless of which provider contributes what.

How much more expensive is Claude Opus output vs GPT-4o output?

Claude Opus 4.7 output costs $75 per million tokens. GPT-4o output costs $10 per million tokens. That is a 7.5x difference at the output layer. For any workload that generates long responses (summarization, long-form writing, reasoning), Opus will cost 7.5x more per response than GPT-4o.

§ Methodology & sources

Prices reflect publicly listed per-million-token rates as of April 2026. This article is updated quarterly. Worked examples assume 30-day months with flat daily request patterns; real production workloads spike. Cost-equivalence comparisons pair models at the comparable tier from each provider, not always at identical capability — for capability-matched comparisons, rely on the decision matrix and capability table rather than raw monthly cost.