GPT-5.4 vs Claude Opus 4.6 vs Gemini 3.1 Pro: The Ultimate March 2026 Showdown

I read through official documentation (OpenAI's GPT-5.4 announcement, Anthropic's Opus 4.6 blog, Google's Gemini 3.1 Pro post), system cards, API pricing pages, and independent benchmarks. This is the full breakdown, exact numbers only, no marketing language. For a broader look at how these compare to older models, see our AI reasoning models comparison.

28 days. That's the gap between the first release (Claude Opus 4.6, February 5) and the last (GPT-5.4, March 5).

You can read the strategy in the timing. OpenAI saw Claude's agentic lead and baked computer use straight into GPT-5.4. Google saw both competitors charging $5-15 per million input tokens and came in at $2. Anthropic, rather than chasing computer use, went deeper on sustained agentic performance.

A year ago, one model could credibly claim to be "the best." That's done. Each of these three leads in different areas, and the gaps are real. If you want a task-by-task breakdown of which model to use for what, we have a dedicated guide for that.

Coding Benchmarks

Reasoning & Science Benchmarks

Gemini 3.1 Pro went from 31.1% to 77.1% on ARC-AGI-2. That's not an incremental jump. On GPQA Diamond (PhD-level science questions), its 94.3% is the highest published score from any model right now.

Professional & Agentic Benchmarks

Long-Context Retrieval

Claude Opus 4.6's 76% accuracy on the hardest long-context retrieval test (8-needle at 1M tokens) is a 4x improvement over Sonnet 4.5's 18.5%. This matters for real-world use: feeding entire codebases or document collections into a single prompt.

Benchmark Summary: Who Wins Where

Pricing sourced from official docs: OpenAI API pricing, Claude API pricing, and Gemini API pricing.

API Pricing (per 1M tokens)

GPT-5.4 Pro costs $30 input / $180 output per million tokens, which is 12x the standard GPT-5.4 rate. You need ChatGPT Pro ($200/month) or Enterprise to access it.

Claude Opus 4.6 Fast Mode (research preview) runs $30 input / $150 output, 6x the standard rate, for faster output when you need it.

Consumer Subscription Comparison

Key difference: Claude's free tier gives you no Opus 4.6 access, only Sonnet 4.6. ChatGPT sometimes auto-routes free users to GPT-5.4 Thinking. Google's free tier is Flash-only, not the full 3.1 Pro. Wondering about ChatGPT's free tier changes? We covered that in our ChatGPT ads and alternatives guide.

Real-World Daily Cost (1M input + 200K output)

With batch pricing, Claude Opus 4.6 becomes competitive with GPT-5.4. Gemini 3.1 Pro remains the cheapest option at every tier.

GPT-5.4: Native Computer Use

GPT-5.4 has computer use built directly into the model, not added as an external tool. It captures screenshots, generates mouse and keyboard actions, executes them, then verifies its own work. The loop is: build, run, verify, fix.

At 75% OSWorld (human baseline: 72.4%), it can navigate desktops, fill forms, and operate applications with more accuracy than most humans.

GPT-5.4: Tool Search (Deferred Loading)

Most models load all tool definitions into the prompt upfront, burning tokens on tools they never use. GPT-5.4 gets a lightweight list and looks up definitions only when needed. This cuts token usage by up to 47% when you're running multi-tool agent workflows. Nothing else does this.

Claude Opus 4.6: 14.5-Hour Task Horizon

On METR's Time Horizons benchmark, Opus 4.6 hit a 50% time horizon of roughly 14.5 hours. That means it reliably completes software tasks that take a skilled human half a day. For comparison, GPT-4o scored in single-digit minutes on the same test in mid-2024. Task-completion capability is doubling about every 123 days.

Claude Opus 4.6: Adaptive Thinking

The old approach: toggle extended thinking on or off. The new approach: Claude figures out how much to think on its own. Simple question? Instant answer. Complex refactor? Deep reasoning kicks in without you asking.

The part that actually matters: adaptive thinking lets Claude reason between tool calls, not just before them. It thinks after each tool result, which is why it handles multi-step coding tasks better than models that plan everything upfront and hope for the best.

Claude Opus 4.6: Context Compaction

"Context rot" is the problem where model output degrades as the conversation gets longer. Claude fixes this by monitoring token usage, generating compressed summaries, and swapping out older context automatically. The result: agents can keep running without hitting the wall. No other model does server-side compaction like this.

Claude Opus 4.6: Agent Teams

Multiple Claude Code instances work as a coordinated team: one lead, multiple teammates, shared task lists with dependency tracking. The difference from basic subagent spawning? Teammates talk to each other directly, not just back to the lead. They can also review each other's plans before executing.

Gemini 3.1 Pro: Broadest Multimodal Input

Gemini 3.1 Pro processes up to 8.4 hours of audio and up to 1 hour of video in a single prompt, alongside text, images, and code. Claude and GPT can't do this. If your workflow touches transcripts, recorded meetings, or video analysis, Gemini is the only real option right now. For more on Google's AI lineup, see our Gemini Flash complete guide.

Gemini 3.1 Pro: Google Search Grounding

Built-in web search during inference. The model cites real sources, and a single API call can simultaneously search Google, run Python code, and return both structured JSON and generated visuals. No other model combines search + code execution + visual output in one step.

Gemini 3.1 Pro: Thought Signatures

Encrypted snapshots of intermediate reasoning. When the model pauses to run a tool and comes back, thought signatures preserve its reasoning state across API calls. Claude and GPT lose some reasoning continuity across multi-turn tool use. Gemini doesn't, at least architecturally.

GPT-5.4 is better at general desktop tasks: clicking through apps, filling out forms, navigating menus. Claude is better at coding tasks that happen to use a computer: debugging in a terminal, running test suites, navigating an IDE. Same capability, different sweet spots. If you're choosing between Claude Code and an IDE-based tool, our Claude Code vs Cursor comparison covers the tradeoffs.

GPT-5.4 gives you the most control. Five levels, including none which kills chain-of-thought entirely for raw speed. You can also see its plan mid-response and redirect if it's going the wrong way.

Claude Opus 4.6 makes the decision for you. Adaptive thinking picks the right reasoning depth automatically. The max level (Opus-only) goes deeper than anything else available.

Gemini 3.1 Pro has fewer knobs but its HIGH mode turns on Deep Think Mini, the reasoning system that scored 77.1% on ARC-AGI-2. That's more than double its predecessor.

Claude and GPT both support 128K output tokens. That's enough to generate a small application in one response. Gemini caps at 64K, half as much.

AI Coding Tool Support

Claude Opus 4.6 is exclusive to Claude Code, the terminal-based coding agent that hit #1 among developer tools in under 8 months, passing both Copilot and Cursor. If you want Opus 4.6 for agentic coding, Claude Code is the only way in. We have a full Claude Code guide if you want the details.

Cloud Provider Availability

Claude Opus 4.6 is the only model on all three major clouds (Azure, AWS, and GCP), plus direct API and OpenRouter. GPT-5.4 is Azure-only. Gemini 3.1 Pro is GCP-only. If you need multi-cloud flexibility, Claude is your only option.

Gemini 3.1 Pro outputs 120.3 tokens per second, more than 2x Claude and 1.6x GPT-5.4. If your use case cares about throughput (batch processing, content generation, real-time responses), Gemini wins by a wide margin.

Worth noting: routing Claude Opus 4.6 through Google Vertex AI drops time-to-first-token to 1.25 seconds, compared to 21.61s through Anthropic's direct API. Provider choice matters. Speed benchmarks sourced from Artificial Analysis.

Use GPT-5.4 When:

• Desktop automation — computer use that navigates apps, fills forms, runs multi-step workflows
• Professional knowledge work — financial modeling, presentations, spreadsheet analysis (87.3% on IB analyst tasks)
• Multi-tool agent workflows — Tool Search saves 47% on tokens in complex agent setups
• Security-sensitive applications — highest cyber safety mitigations of any model
• Codex worktrees — multiple parallel agents working on the same repo with Git isolation

Use Claude Opus 4.6 When:

• Complex coding tasks — SWE-bench lead, Terminal-Bench lead, and 14.5-hour autonomous task horizon
• Long agentic sessions — context compaction enables infinite conversations without quality degradation
• Multi-cloud deployment — only model on Azure + AWS + GCP + direct API
• Legal and compliance work — 90.2% BigLaw Bench, lowest over-refusal rate
• Creative writing — #1 on Chatbot Arena with the most natural, human-sounding prose
• Life sciences — nearly 2x better than its predecessor on computational biology and organic chemistry

Use Gemini 3.1 Pro When:

• Budget is the priority — cheapest API pricing at $2/$12, half the cost of Claude
• Audio/video processing — only model that natively ingests 8.4 hours of audio or 1 hour of video
• Hard reasoning problems — 77.1% ARC-AGI-2, 94.3% GPQA Diamond
• High-throughput applications — 120.3 tokens/sec, 2x faster than Claude
• Google ecosystem — native integration with Workspace, Chrome auto-browse, BigQuery
• Research with live data — Google Search grounding provides verifiable citations during inference

Six months ago, you could pick one model and use it for everything. That worked. It doesn't anymore.

Claude Opus 4.6 is what I reach for when the code matters. 81.4% SWE-bench, a 14.5-hour task horizon, and context compaction mean it handles enterprise-scale codebases for hours without losing quality. For production software, I'd start here.

GPT-5.4 is the one that operates your computer. Native computer use that beats human experts, 83% GDPval on knowledge work, and a Tool Search system that saves nearly half your tokens. If you need an AI that automates desktop workflows, this is it.

Gemini 3.1 Pro does 80% of what the other two do at 40% of the price. $2/$12 per million tokens, the strongest reasoning scores (77.1% ARC-AGI-2, 94.3% GPQA Diamond), and 2x the output speed. For high-volume work, multimodal inputs, or tight budgets, the math is hard to argue with.

This race isn't slowing down. Gemini 3 Pro was deprecated 18 days after 3.1 Pro launched. GPT-5.2 retires in June. The specific models will keep changing. But the habit of matching models to tasks, rather than picking a favorite and sticking with it, will outlast every benchmark score on this page. If you want to keep up with the cost side of this race, we also compared Claude vs Kimi K2 on cost efficiency and DeepSeek V4 vs Qwen3 Max for the open-source angle.

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