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Claude Sonnet 5 vs GPT-5.4

Anthropic's 1M-context mid-tier takes on OpenAI's most affordable mid-tier. Same output price ($15/1M), but Sonnet 5 delivers 2.5x the context for just $0.50 more per 1M input tokens. Which is the smarter pick?

Pricing data verified: Jul 3, 2026

SpecificationClaude Sonnet 5 (Anthropic)GPT-5.4 (OpenAI)
Input Price (per 1M tokens)$3.00$2.50
Output Price (per 1M tokens)$15.00$15.00
Context Window1M tokens400K tokens
TierMidMid
ProviderAnthropicOpenAI

Calculate Your Exact Costs

See the real cost difference — GPT-5.4 saves on input, but Sonnet 5's 2.5x context may be worth the extra $0.50/1M.

Anthropic
Claude Sonnet 5
$0.00
per month
Input cost
Output cost
Cost per request
Requests/month
OpenAI
GPT-5.4
$0.00
per month
Input cost
Output cost
Cost per request
Requests/month

Other Mid-Tier Models

Claude Opus 4.8
Anthropic
$5 / $25 per 1M
1M context
Gemini 3.1 Pro
Google
$2.00 / $12 per 1M
1M context
GPT-5.5
OpenAI
$5 / $30 per 1M
1.05M context

Which Model for Which Use Case?

Long Document Processing

Legal contracts, research papers, book-length text. Sonnet 5's 1M context handles documents up to 2.5x longer than GPT-5.4's 400K limit. For any task involving large documents, Sonnet 5 is the only viable option between these two.

Clear winner: Sonnet 5

Code Generation

Both models handle coding well. Sonnet 5's 1M context means you can feed entire large codebases for context. GPT-5.4 at 400K is sufficient for most individual files and modules. Output pricing is identical at $15/1M.

Large codebases: Sonnet 5 | Smaller projects: GPT-5.4

Content Generation

Blog posts, marketing copy, documentation. Output cost is identical at $15/1M for both models. GPT-5.4 saves 17% on input ($2.50 vs $3.00), which matters for content workflows with large prompts. Both produce high-quality output.

Slight edge: GPT-5.4 (cheaper input)

High-Volume Batch Processing

At scale, GPT-5.4's 17% input savings add up. For 10M input + 5M output tokens/month: Sonnet 5 costs $105 vs GPT-5.4's $100 — saving $5/month. The savings are modest because output pricing is identical. Context needs should drive the decision more than cost here.

Budget batch: GPT-5.4 | Large-context batch: Sonnet 5

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Frequently Asked Questions

How much does Claude Sonnet 5 cost compared to GPT-5.4?

Claude Sonnet 5 costs $3.00 input / $15.00 output per 1M tokens. GPT-5.4 costs $2.50 input / $15.00 output per 1M tokens. Output pricing is identical at $15/1M, but GPT-5.4 is 17% cheaper on input ($2.50 vs $3.00). For a typical workload of 1M input + 500K output tokens/month, Sonnet 5 costs $10.50 vs GPT-5.4's $10.00 — a difference of just $0.50/month.

Which has a larger context window — Sonnet 5 or GPT-5.4?

Claude Sonnet 5 has a dramatically larger context window at 1M tokens compared to GPT-5.4's 400K tokens. That's 2.5x more context. If you work with long documents, large codebases, or need extensive conversation history, Sonnet 5 is the clear winner on context capacity.

Is GPT-5.4 worth choosing over Sonnet 5?

GPT-5.4 at $2.50/$15 is a solid choice when you need a mid-tier model under 400K context and want the lowest input cost. However, Claude Sonnet 5 at $3/$15 offers 2.5x the context window for just $0.50 more per 1M input tokens. For most use cases, Sonnet 5's massive context advantage outweighs the small input cost savings of GPT-5.4.

Does Sonnet 5 have introductory pricing?

Yes. Claude Sonnet 5 offers introductory pricing of $2/$10 per MTok through August 31, 2026 — 33% cheaper than standard. During the intro period, Sonnet 5 is actually cheaper than GPT-5.4 on input ($2 vs $2.50). After August 31, it returns to $3/$15. GPT-5.4 has no announced introductory pricing.

Can GPT-5.4 handle the same tasks as Sonnet 5?

Both are mid-tier models capable of coding, content generation, analysis, and chatbot workloads. The key limitation of GPT-5.4 is its 400K context window — tasks requiring processing of very long documents (legal contracts, large codebases, book-length text) will need Sonnet 5's 1M context. For shorter-context tasks, both perform comparably.

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