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GPT-5.4 vs Claude Sonnet 4.6: which is cheaper for production?

Use GPT-5.4 for one-off tasks with short context. Use Claude Sonnet 4.6 for long-document processing or agentic loops where context caching drastically reduces the cost.

The workhorse model pricing showdown.

GPT-5.4 and Claude Sonnet 4.6 are the two most popular models for general-purpose applications. While GPT-5.4 has a lower base input cost, Claude Sonnet 4.6's aggressive prompt caching can make it cheaper for long-context agentic workflows.

By TechCompare · Updated

Cost Comparison

Based on 100,000 input tokens (50% cached), 5,000 output tokens, and 100 requests.

Option A
GPT-5.4
Wins 2 of 4 compared specs
Option B
Claude Sonnet 4.6
Wins 1 of 4 compared specs

Side-by-side specs

SpecGPT-5.4Claude Sonnet 4.6
Input Cost (per M)$2.50 (better on this spec)$3.00
Output Cost (per M)$15.00$15.00
Cached Input (per M)$0.25 (better on this spec)$0.30
Best for Agentic LoopsCapableOptimal (better on this spec)

How they differ

GPT-5.4 charges $2.50 per million input tokens and $15.00 for output. Claude Sonnet 4.6 charges $3.00 for input and $15.00 for output, but offers a 90% discount on cached input tokens, reducing the effective input price to $0.30 per million for repetitive context.

Verdict

GPT-5.4 saves you 50 cents per million input tokens ($2.50 against $3.00) and ties on output at $15.00/M. The math narrows once you cache: Sonnet 4.6's cached input at $0.30/M only trails GPT-5.4's $0.25/M by a nickel, and on a 70% reuse agentic loop that 90% discount closes most of the base gap without ever overtaking the cheaper base. So match the model to the prompt's lifespan, not its size.

Which should you pick?

Choose GPT-5.4

Short conversations, independent API calls without shared context.

Choose Claude Sonnet 4.6

Agentic loops, RAG, and workflows where the system prompt and history are heavily reused.

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Frequently asked questions

Is GPT-5.4 or Claude Sonnet 4.6 cheaper for high-volume cached workloads?
GPT-5.4, narrowly. Claude Sonnet 4.6 loses on cached inputs at $0.30/M (90% discount) versus GPT-5.4's $0.25/M, and the gap is small. For workloads with 70%+ prompt reuse and long shared system prompts, Sonnet 4.6's 90% cache discount narrows the gap against higher base context volumes, but it never closes it. GPT-5.4's $2.50/M uncached input stays cheaper for single-pass tasks.
Which model should I pick for a coding agent with tool calls?
Claude Sonnet 4.6. Its tool-use is tighter than GPT-5.4's and Anthropic's prompt caching lets you reuse the system prompt and tool definitions across thousands of calls without paying full input each time. At $15.00/M output the cost matches GPT-5.4, so the agentic ergonomics tip the decision.
What does 90% prompt caching actually save me on Claude Sonnet 4.6?
It drops cached input from $3.00/M to $0.30/M. On a 50K-token system prompt reused 10,000 times per day, that cuts roughly $1,500 of daily input cost down to $150. The cache TTL is 5 minutes by default and refreshes on each hit, so steady-state agentic loops keep the discount active.