A consultant I know spent three weeks building an internal research assistant on GPT-5.4. It worked beautifully in demos. Then it hit production: a 400-page policy document, a chain of conditional instructions, a precise output format. The model kept drifting off-spec after the first 80 pages. She rebuilt it on Claude Opus 4.6 in four days. The instruction following was tighter. The output format held. The project shipped.

That story isn’t an indictment of GPT-5.4. It’s a preview of the entire comparison: two genuinely excellent models that consistently win in different scenarios.

Short version: Claude Opus 4.6 for writing, long-document analysis, and precision instruction following. GPT-5.4 for computer use, multi-step web research, and breadth of professional tasks. Both support 1M-token context and extended reasoning. Neither is clearly better — they’re differently optimized.

Quick Verdict

Aspect	GPT-5.4	Claude Opus 4.6
Best For	Computer use, multi-step research, breadth	Writing, long docs, instruction precision
Context Window	272K standard / 1M via API	1M (standard pricing, GA since Mar 13)
API Pricing (input/output)	$2.50 / $15 per 1M tokens	$5 / $25 per 1M tokens
Extended Thinking	✓ 5 effort levels (none → xhigh)	✓ Thinking tokens billed as output
Computer Use	✓ Native (OSWorld: 75%)	✓ (OSWorld: 72.7%)
Coding (SWE-Bench)	77.2%	80.8%
Chatbot Arena ELO	—	#1 (1503)
ChatGPT/Claude Plan	Plus ($20/mo) or Pro ($200/mo)	Pro ($20/mo) or Max ($200/mo)

Bottom line: GPT-5.4 is cheaper and broader. Claude Opus 4.6 is more precise and leads on user preference and standard coding benchmarks. For most knowledge workers who write and analyze, Claude edges ahead. For tool-heavy agentic work and computer automation, GPT-5.4 is the stronger default.

The Short Version (If You’re in a Hurry)

Use GPT-5.4 when you need:

• Native computer use and screen-based automation
• Professional research across law, finance, and APEX-Agents-type tasks
• Lower API cost per token at standard context lengths
• A single model that handles varied knowledge tasks competently

Use Claude Opus 4.6 when you need:

• Precise multi-step instruction following across long outputs
• Writing that requires minimal editing
• Long-document analysis — the 1M context window is now fully standard-priced
• Top-ranked user preference performance (Chatbot Arena #1)

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What Actually Changed in March 2026

Both models dropped within ten days of each other: Claude Opus 4.6 on February 5th, GPT-5.4 on March 5th. That timing matters. For the first time in a while, you’re comparing two true contemporaries rather than a new model against a six-month-old rival.

A few things are genuinely new here vs. any older comparison:

For GPT-5.4: This is the first OpenAI general-purpose model with native computer use built in — not a bolt-on preview, but an actual Computer Use API that lets the model operate desktop applications. It also unifies OpenAI’s Codex and GPT lines into a single system, which means the best coding capabilities are now in the same model you use for writing and research.

For Claude Opus 4.6: Anthropic quietly dropped the price from $15/$75 per million tokens (what Opus 4.1 cost) down to $5/$25 — a 67% price reduction while improving performance. They also made 1M-token context generally available at standard pricing on March 13th, eliminating the long-context premium entirely.

Both facts are buried in release notes. But they completely change the ROI math.

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Where GPT-5.4 Wins

Computer Use and Automation

GPT-5.4 scores 75% on OSWorld (the benchmark for autonomous computer use) versus Claude Opus 4.6’s 72.7%. That gap isn’t huge in percentage terms. In practice, it compounds. When you’re running 20-step workflows that require the model to open applications, navigate UIs, and verify its own work, each additional accuracy point reduces the chance of cascade failures.

If your use case involves actual screen interaction (not just API calls), GPT-5.4 is the more mature choice. The Computer Use API launched as a first-class feature, not a research preview.

For more on what this unlocks, see the GPT-5.4 computer use review.

Multi-Step Professional Research

GPT-5.4 scored 83% on OpenAI’s GDPval test (knowledge work tasks) and leads Mercor’s APEX-Agents benchmark, which tests professional skills in law and finance. Its factual accuracy is also measurably better: individual claims are 33% less likely to be false compared to GPT-5.2.

The configurable reasoning system (five levels from “none” to “xhigh”) also gives you explicit cost control. On “low” it’s fast. On “xhigh” it takes time and burns tokens, but for a complex legal analysis or financial model review, you can dial in exactly how hard you want the model to think.

API Cost Efficiency

At standard context lengths (under 272K tokens), GPT-5.4 is meaningfully cheaper: $2.50/$15 vs Claude Opus 4.6’s $5/$25 per 1M input/output tokens. That’s 50% cheaper on input. For high-volume API workloads where cost scaling matters, GPT-5.4 wins on economics.

One caveat: cross the 272K token threshold and GPT-5.4’s input price doubles to $5/M — erasing that advantage for long-context jobs.

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Where Claude Opus 4.6 Wins

Instruction Following at Scale

This is Claude’s clearest edge for everyday professional use. Give Claude a complex prompt with 12 conditional rules, a specific output schema, and 200 pages of source material — and it will follow those instructions for the full output. GPT-5.4 is good at this too, but I’ve consistently seen it “soften” or drift from restrictive formatting rules in long outputs, especially when the instructions contradict what the model thinks sounds better.

This isn’t a criticism of GPT-5.4’s intelligence. It’s a difference in how the models are trained. Claude’s reinforcement learning from human feedback places heavy weight on doing exactly what the user asked. That shows up in practice.

Writing Quality

I draft and edit a lot of text. Claude’s writing output requires less editing. The sentences have more variation. The structure is less formulaic. GPT-5.4 has improved significantly from earlier generations, but it still occasionally slips into a corporate consultant register — complete sentences, parallel structures, qualifications stacked on qualifications.

Claude writes more like a person who has thought carefully about what they want to say. Whether that matters depends entirely on what you’re writing. For internal memos and reports, both are fine. For anything a client or customer will actually read? The editing lift is noticeably lower with Claude.

See how both perform on specific content tasks in our best AI writing tools roundup.

Coding Depth on Standard Tasks

On SWE-Bench Verified (the standard industry benchmark for software engineering), Claude Opus 4.6 scores 80.8% vs GPT-5.4’s 77.2%. For day-to-day development tasks (debugging, refactoring, code review, writing tests), Claude holds the edge.

GPT-5.4 flips this on SWE-Bench Pro, the harder benchmark, scoring 57.7% vs Claude’s ~45.9%. For extremely difficult, novel engineering problems, GPT-5.4 may pull ahead. For the 80% of coding work that’s not novel, the typical professional developer’s day, Claude is more reliable.

Our coding assistants comparison goes deeper on where each model fits in a dev workflow.

Long-Context Reliability (1M Tokens, Standard Pricing)

As of March 13, 2026, Claude Opus 4.6’s full 1M context window is generally available at standard pricing — no long-context premium. You pay $5/$25 per million tokens whether your request is 9K or 900K tokens.

GPT-5.4 technically supports 1M tokens via API too, but the pricing structure bites: any prompt over 272K tokens triggers 2x input pricing. So for long-document workflows (entire codebases, 400-page policy documents, research archives), Claude Opus 4.6 is both more reliable and more cost-effective.

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Pricing, Broken Down

API Pricing (Per Million Tokens)

Tier	GPT-5.4	Claude Opus 4.6
Input (standard)	$2.50	$5.00
Output	$15.00	$25.00
Long context (>272K input)	$5.00 (2x)	$5.00 (no premium)
Cached input	$1.25	$0.50 (10% of input)
Batch API discount	~50%	50%
“Max effort” / Pro tier	$30/$180 (GPT-5.4 Pro)	$30/$150 (Fast mode)

View OpenAI pricing →

View Anthropic pricing at anthropic.com/claude

Subscription Plans

Both flagship models require a paid subscription to access via chat interfaces:

• GPT-5.4: Available on ChatGPT Plus ($20/mo) with usage caps, or unlimited via ChatGPT Pro ($200/mo).
• Claude Opus 4.6: Available on Claude Pro ($20/mo) with usage limits, or Claude Max ($200/mo) for unlimited access including Agent Teams.

For individual professionals doing moderate daily use, the $20/month tier for either model is the right starting point. Heavy API users or teams running automated workflows should compare per-token costs against expected volume.

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The Stuff Nobody Talks About

GPT-5.4’s Steerability Is Genuinely New

The ability to adjust GPT-5.4’s reasoning mid-response, to see the model’s plan and redirect it before it commits, is not a gimmick. For complex, high-stakes tasks (legal analysis, financial modeling, architectural decisions), catching a wrong assumption at the planning stage beats getting a beautifully written wrong answer.

Claude doesn’t have this yet. It thinks first, then shows you the output of that thinking. GPT-5.4 shows you the plan.

Claude’s 1M Context Is More Usable in Practice

GPT-5.4’s 1M context technically works, but the 272K pricing threshold means you’re paying double for any session that goes long. Claude’s flat pricing across the full 1M window makes long-context use more predictable and cheaper for document-heavy workflows.

Neither Model Should Be Your Fact-Checker

Both GPT-5.4 and Claude Opus 4.6 produce confident-sounding statements that are occasionally wrong. GPT-5.4’s factual accuracy improvements (33% fewer false individual claims vs. GPT-5.2) are real, but “better than GPT-5.2” is not “reliable.” Claude is more likely to say “I’m not certain about this” — which at least flags uncertainty. For anything where accuracy is critical, verify against primary sources.

Claude’s Agent Teams Are Experimental

Claude Opus 4.6 includes Agent Teams — the ability to split long tasks across multiple Claude agents, each with independent context. This is powerful for complex software projects. It’s also marked as experimental and not yet reliably production-ready for most teams. Don’t pick Claude for Agent Teams unless you’re willing to do significant prompt engineering.

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My Actual Workflow

Here’s how I actually use these two models after testing both extensively:

Task	My Choice	Why
First draft of long-form writing	Claude Opus 4.6	Less editing, follows structure brief
Deep research across the web	GPT-5.4	Better multi-step research, web access
Code review and debugging	Claude Opus 4.6	More reliable on SWE-Bench-type tasks
Document analysis (100+ pages)	Claude Opus 4.6	1M context, no pricing penalty
Automated screen-based workflows	GPT-5.4	Native computer use is ahead
Quick Q&A and general questions	Either	Marginal difference at this level
Professional report with strict format	Claude Opus 4.6	Instruction following is tighter
Law/finance research at depth	GPT-5.4	APEX-Agents performance, reasoning depth

I pay for both. At $20/month each, that’s $40/month — roughly the cost of a lunch. For professionals who use AI daily, both models are worth having.

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How to Decide

Choose GPT-5.4 if:

• You need computer use or screen automation
• API cost at standard context lengths matters
• You want five configurable reasoning effort levels
• Multi-step professional research in law or finance is core to your work
• You value the ability to steer the model’s reasoning mid-task

Choose Claude Opus 4.6 if:

• You work with long documents regularly (and want predictable 1M context pricing)
• Writing quality and instruction fidelity matter
• You do substantial coding work (SWE-Bench advantage)
• User-preference benchmarks matter to you (Chatbot Arena #1)

Get Both if:

• You’re a developer building on top of AI and want to route by task type
• You do varied knowledge work that spans writing, research, and automation
• $40/month is justifiable given your AI usage volume

For a deeper look at how these models fit into broader agentic frameworks, see our AI agent platforms guide. Or compare pricing across the full market in our AI pricing comparison.

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The Bottom Line

If I had to pick one?

For most knowledge workers (people who write reports, analyze documents, research topics, and occasionally code), Claude Opus 4.6 is the stronger daily driver in March 2026. The instruction following is tighter, the writing is better, the long-context pricing is simpler, and users prefer it in blind tests.

For professionals who need computer automation, tool-heavy agentic pipelines, or maximum performance on professional research benchmarks, GPT-5.4 is the right call.

The benchmark gaps have closed enough that real-world fit matters more than leaderboard scores. Both models are genuinely capable. Pick based on your actual use cases, not hype.

Start here:

• Try GPT-5.4 via ChatGPT Plus →
• Try Claude Opus 4.6 via Claude Pro →

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Frequently Asked Questions

Is GPT-5.4 or Claude Opus 4.6 better for everyday professional use?

For most professionals who write, research, and analyze documents, Claude Opus 4.6 edges ahead due to tighter instruction following, better writing quality, and simpler long-context pricing. GPT-5.4 wins for computer use and multi-step professional research tasks.

How do GPT-5.4 and Claude Opus 4.6 compare on price?

At standard context lengths, GPT-5.4 is cheaper: $2.50/$15 per million input/output tokens vs. Claude Opus 4.6’s $5/$25. For long documents over 272K tokens, the gap closes because GPT-5.4 doubles its input price. Claude Opus 4.6 charges the same $5/M input regardless of context length.

Do both models support extended thinking or reasoning modes?

Yes. GPT-5.4 has five configurable reasoning effort levels (none, low, medium, high, xhigh). Claude Opus 4.6 supports extended thinking tokens billed as output at $25/M. Both allow you to trade cost for reasoning depth.

Which model is better for coding?

It depends on the type of coding. Claude Opus 4.6 leads SWE-Bench Verified (80.8% vs 77.2%) for standard software engineering tasks. GPT-5.4 leads SWE-Bench Pro (57.7% vs ~45.9%) for harder, more novel problems. For most developers, Claude’s standard coding performance is more relevant. See our coding assistants comparison.

Is Claude Opus 4.6 worth the price increase over Sonnet 4.6?

For precision-critical tasks, yes. Sonnet 4.6 costs $3/$15 per million tokens — 40% cheaper on input. The gap justifies Opus 4.6 when output quality, instruction fidelity, or long-document performance directly affects the value of the work.

What happened to the older flagship pricing?

Claude Opus 4.1 was priced at $15/$75 per million tokens. Opus 4.6 dropped that to $5/$25 — a 67% price reduction while improving performance. OpenAI followed a similar trajectory. The “flagship models are too expensive” argument is about 6 months out of date.

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Last updated: March 15, 2026. Pricing and benchmarks verified against OpenAI API pricing and Anthropic’s published model pricing.