GPT-5.4 vs Claude Sonnet 4.6 Pricing (2026)
Compare GPT-5.4 and Claude Sonnet 4.6 pricing, caching, and real-world costs for coding, support, and agent workloads in 2026.
If you are choosing between OpenAI GPT-5.4 and Anthropic Claude Sonnet 4.6, the first surprise is how close the pricing is.
This is not one of those matchups where one model is 4x cheaper. GPT-5.4 is only 17% cheaper on input tokens, both models cost the same on output tokens, and both offer heavily discounted cached input pricing. That means the decision is less about raw token price and more about what kind of work you want the model to do.
In practice, GPT-5.4 is the cleaner choice for general-purpose premium workloads, especially if you can use OpenAI’s batch discount. Claude Sonnet 4.6 remains extremely compelling for coding, where many teams will gladly pay a small premium if it improves first-pass quality.
For current provider-wide pricing, start with our OpenAI pricing page, Anthropic pricing page, and token calculator.
Quick Verdict
| GPT-5.4 | Claude Sonnet 4.6 | |
|---|---|---|
| Input | $2.50 / 1M tokens | $3.00 / 1M tokens |
| Cached input | $0.25 / 1M tokens | $0.30 / 1M tokens |
| Output | $15.00 / 1M tokens | $15.00 / 1M tokens |
| Context window | 270K tokens | 200K tokens |
| Batch pricing | Yes, 50% off | No comparable discount |
| Best fit | General premium workloads, agents, batch jobs | Coding, code review, developer workflows |
The headline math is simple:
- GPT-5.4 is cheaper on uncached input
- GPT-5.4 is cheaper on cached input
- Output pricing is identical
- OpenAI gets much cheaper if you can use Batch API
So if your workload is output-heavy, the raw price gap is tiny. If your workload is input-heavy or async, GPT-5.4 pulls ahead faster.
Feature Comparison Matrix
Price is close enough here that the feature differences matter more than usual.
| Factor | GPT-5.4 | Claude Sonnet 4.6 | Why it matters |
|---|---|---|---|
| Sticker-price input cost | Lower | Slightly higher | GPT-5.4 wins in direct token cost |
| Output cost | Same | Same | Long completions cost the same either way |
| Cached prompts | Lower cached rate | Slightly higher cached rate | GPT-5.4 still keeps a small edge |
| Context window | 270K | 200K | GPT-5.4 gives you more room for long prompts |
| Batch processing | 50% discount available | No batch equivalent | Big deal for offline jobs |
| Coding reputation | Strong | Excellent | Sonnet often wins when code quality is the top priority |
| Best buying case | Premium general-purpose API | Premium coding API | The better choice depends on the job |
This is what makes the matchup interesting.
With GPT-5.4 mini vs Claude Sonnet 4.6, cost alone often settles the argument because the gap is huge. With GPT-5.4 full vs Sonnet 4.6, cost rarely settles it by itself. Both sit in the premium tier, and both are realistic choices for serious applications.
If your team is really choosing based on budget, it is worth stepping back and asking whether you should be comparing GPT-5.4 mini, GPT-5.4 nano, or another cheaper model instead. We cover that in How to Calculate AI API Costs (2026) and OpenAI vs Anthropic API Pricing (2026).
Scenario 1: Coding Assistant with Heavy Prompt Reuse
This is the most common real-world reason to compare these two models.
Assume your monthly usage looks like this:
- 20M uncached input tokens
- 80M cached input tokens
- 20M output tokens
That is a realistic shape for a coding assistant that keeps reusing repo context, system instructions, and formatting rules.
GPT-5.4 cost
- Uncached input: 20M × $2.50 = $50.00
- Cached input: 80M × $0.25 = $20.00
- Output: 20M × $15.00 = $300.00
- Total: $370.00/month
Claude Sonnet 4.6 cost
- Uncached input: 20M × $3.00 = $60.00
- Cached input: 80M × $0.30 = $24.00
- Output: 20M × $15.00 = $300.00
- Total: $384.00/month
What this means
The difference is just $14/month.
That is tiny. If Claude Sonnet 4.6 saves even a little engineering time by producing better code suggestions, cleaner refactors, or fewer failed tool calls, the premium disappears instantly.
For coding-heavy teams, this is the key takeaway: you are not really making a price decision here, you are making a quality decision with a very small pricing penalty.
That is why so many engineering teams end up with a split stack:
- use Claude Sonnet 4.6 for code generation, review, and agentic dev workflows
- use GPT-5.4 mini or nano for cheaper surrounding tasks like summaries, classification, or routing
Scenario 2: Premium Support or Research Agent with Little Cache
Now look at a more input-heavy workload with less prompt reuse.
Monthly usage:
- 100M uncached input tokens
- 0 cached input tokens
- 20M output tokens
GPT-5.4 cost
- Input: 100M × $2.50 = $250.00
- Output: 20M × $15.00 = $300.00
- Total: $550.00/month
Claude Sonnet 4.6 cost
- Input: 100M × $3.00 = $300.00
- Output: 20M × $15.00 = $300.00
- Total: $600.00/month
What this means
Here GPT-5.4 saves $50/month, or $600/year.
That is still not a massive gap for a premium workload, but it is enough to matter if you are scaling to many internal tools or many customers. The more your app behaves like a high-volume general assistant rather than a code specialist, the more GPT-5.4 starts to look like the better buy.
This is also where the wider context window matters. If your agent keeps long instructions, tool traces, or multi-document context in the prompt, 270K tokens vs 200K gives GPT-5.4 more headroom before you need aggressive trimming.
Scenario 3: Overnight Batch Jobs
Batch pricing is where GPT-5.4 gets a real structural advantage.
Assume you run a nightly summarization or content pipeline with:
- 40M input tokens
- 10M output tokens
GPT-5.4 standard pricing
- Input: 40M × $2.50 = $100.00
- Output: 10M × $15.00 = $150.00
- Standard total: $250.00/month
GPT-5.4 with Batch API
- 50% off standard rate
- Batch total: $125.00/month
Claude Sonnet 4.6 standard pricing
- Input: 40M × $3.00 = $120.00
- Output: 10M × $15.00 = $150.00
- Total: $270.00/month
What this means
If your workload can wait for asynchronous processing, GPT-5.4 becomes dramatically cheaper.
In this example, GPT-5.4 Batch is $145/month cheaper than Claude Sonnet 4.6, even though the standard sticker prices were already fairly close. This is a meaningful edge for:
- offline document processing
- nightly reporting
- evaluation jobs
- large backfills
- content enrichment
- support-ticket tagging
If your product has both interactive and offline traffic, it often makes sense to separate them. Keep a premium real-time model where it matters, then move background work to the cheapest batch-friendly path you can support.
When to Choose GPT-5.4
Choose GPT-5.4 if most of these are true:
- you want one premium model for many different workloads
- your app is input-heavy and you care about small but steady cost savings
- you need a larger context window
- you can use batch processing for some traffic
- you want the slightly cleaner pricing story across uncached and cached input
The strongest argument for GPT-5.4 is not that it crushes Sonnet on price. It does not. The strongest argument is that it is a little cheaper nearly everywhere and much cheaper in batch use cases.
That makes it a safe default premium model, especially for teams that do not want to optimize around a model that is mainly famous for coding.
When to Choose Claude Sonnet 4.6
Choose Claude Sonnet 4.6 if most of these are true:
- coding is your primary use case
- your team already sees better real output from Sonnet in IDEs or internal evals
- you care more about first-pass code quality than saving a few dollars on input tokens
- your pricing model can absorb a small premium without stress
The case for Sonnet is straightforward: if it writes better code for your environment, the price premium is too small to dominate the decision.
That is especially true when you compare it against GPT-5.4 full rather than GPT-5.4 mini. Once you are already shopping in the premium tier, quality differences matter more than a 50-cent input gap per million tokens.
Token Calculator Examples You Can Reuse
If you want to model your own workload, plug these numbers into our token calculator:
Example A: coding copilot
- input: 20,000,000
- cached input: 80,000,000
- output: 20,000,000
Example B: premium support agent
- input: 100,000,000
- cached input: 0
- output: 20,000,000
Example C: overnight batch workload
- input: 40,000,000
- cached input: 0
- output: 10,000,000
Then compare the result against lower-cost alternatives too. For many teams, the real answer is not just GPT-5.4 or Sonnet. It is often Sonnet for coding, cheaper models for everything else.
FAQ
Which model is cheaper, GPT-5.4 or Claude Sonnet 4.6?
GPT-5.4 is slightly cheaper on input and cached input. Output pricing is the same.
Is Claude Sonnet 4.6 worth the premium?
Usually yes, if coding quality is central to your workflow. Usually no, if you just need a general premium model and care more about cost control.
Does caching change the result?
A little, but not dramatically. GPT-5.4 keeps a small cost edge on cached input too.
What if I mainly care about budget?
Then you probably should not start with either of these models. Look at cheaper options first, especially GPT-5.4 mini, GPT-5.4 nano, or other budget-focused models on our pricing hub.
Bottom Line
GPT-5.4 is the better pure pricing play. Claude Sonnet 4.6 is the better coding bet.
Because output pricing is identical and input pricing is close, this comparison is really about whether Sonnet’s quality advantage in developer workflows is worth a modest premium.
For general-purpose premium work, I would lean GPT-5.4. For coding-heavy teams, I would lean Claude Sonnet 4.6. For cost-sensitive production systems, I would seriously consider stepping down a tier and comparing cheaper models before choosing either one.
If you want a wider view, read our ChatGPT vs Claude pricing comparison, OpenAI vs Anthropic API pricing guide, and How to Calculate AI API Costs.