GPT-5.4 vs Gemini 3.1 Pro - Breadth Meets Reasoning Depth
GPT-5.4 leads on computer use and enterprise productivity. Gemini 3.1 Pro leads on science reasoning and math at 20% lower cost. A benchmark-by-benchmark comparison.
6 min read
GPT-5.4 launched March 5 with native computer use, a 1M token context window, and three variants at $2.50/$15 per million tokens. Gemini 3.1 Pro has been available since February 19 with the highest science reasoning scores ever recorded and four-modality input at $2.00/$12 per million tokens.
Both models target the same 1M context tier. Both cost roughly the same. The split is in what they focus on: GPT-5.4 bets on computer interaction and enterprise productivity, while Gemini 3.1 Pro bets on deep reasoning and multimodal breadth.
TL;DR
- Choose GPT-5.4 if you need computer use (OSWorld 75% vs no equivalent), enterprise productivity (GDPval 83%, spreadsheet modeling 87.5%), or the broadest competitive benchmark coverage across all categories
- Choose Gemini 3.1 Pro if you need the strongest science reasoning (GPQA Diamond 94.3% vs 92.8%), abstract reasoning (ARC-AGI-2 77.1% vs 73.3%), multimodal input (text, image, audio, video), or the lowest pricing at $2/$12
Quick Comparison
| Feature | GPT-5.4 | Gemini 3.1 Pro |
|---|---|---|
| Developer | OpenAI | Google DeepMind |
| Release Date | March 5, 2026 | February 19, 2026 |
| Architecture | GPT-5 Transformer | Transformer MoE |
| Context Window | 1M | 1M |
| Output Limit | Not disclosed | 64K |
| Input Modalities | Text, images | Text, images, audio, video |
| API Pricing (Input) | $2.50/M | $2.00/M (<=200K), $4.00/M (>200K) |
| API Pricing (Output) | $15.00/M | $12.00/M (<=200K), $18.00/M (>200K) |
| Computer Use | Native | No |
| Dynamic Thinking | Via Thinking variant | Built-in (adjustable) |
| Status | GA | Preview |
| OSWorld-Verified | 75.0% | - |
| GPQA Diamond | 92.8% | 94.3% |
| ARC-AGI-2 | 73.3% | 77.1% |
| Terminal-Bench 2.0 | 75.1% | 68.5% |
| AIME 2025 | - | 100% |
| SWE-bench Verified | 77.2% | 80.6% |
GPT-5.4: Desktop Automation and Enterprise
GPT-5.4's computer use capability has no Gemini equivalent. The model operates software autonomously - clicking, typing, navigating - and scores 75.0% on OSWorld-Verified, surpassing the human baseline of 72.4%. For workflows that require interacting with applications rather than just producing text, GPT-5.4 is the only frontier model with built-in support at this level.
Terminal-Bench 2.0 at 75.1% leads Gemini's 68.5% by 6.6 points. GDPval at 83.0% covers knowledge work across 44 occupations. The spreadsheet modeling benchmark at 87.5% with native Excel and Google Sheets plugins positions GPT-5.4 as the strongest model for financial and business analysis workflows.
GPT-5.4 ships in three variants. The base model handles general tasks. Thinking adds extended chain-of-thought with visible reasoning. Pro uses parallel reasoning threads and an "extreme" thinking mode for the hardest problems at $30/$180 per million tokens.
The compaction feature lets GPT-5.4 prune long agent trajectories while preserving critical context, keeping multi-step workflows viable without manual context management.
Gemini 3.1 Pro: Reasoning Depth and Multimodal Input
Gemini 3.1 Pro holds the highest science reasoning scores of any model. GPQA Diamond at 94.3% leads GPT-5.4's 92.8% by 1.5 points. ARC-AGI-2 at 77.1% - a test of novel pattern reasoning - leads GPT-5.4's 73.3% by 3.8 points. AIME 2025 at a perfect 100% with code execution is the math ceiling.
The multimodal advantage is significant. Gemini processes text, images, audio, and video natively. GPT-5.4 handles text and images only. For workloads involving video analysis, audio transcription integrated with reasoning, or mixed-media documents, Gemini has a capability that GPT-5.4 lacks entirely.
On coding, Gemini's SWE-bench Verified at 80.6% leads GPT-5.4's 77.2% by 3.4 points. MCP Atlas at 69.2% for tool coordination also edges GPT-5.4's 67.2%.
Dynamic thinking is built into the base model with adjustable depth via the thinking_level parameter, rather than requiring a separate "Thinking" variant.
The pricing is the lowest among frontier models. At $2.00/$12.00 standard, Gemini is 20% cheaper on input and 20% cheaper on output compared to GPT-5.4. The Batch API at $1.00/$6.00 and context caching at $0.20/M make high-volume workloads even more affordable.
The preview status is the caveat. Developers have reported capacity issues and quota bugs during the preview period. GPT-5.4 launched at GA.
Benchmark Comparison
| Benchmark | GPT-5.4 | Gemini 3.1 Pro | Winner |
|---|---|---|---|
| GPQA Diamond (science) | 92.8% | 94.3% | Gemini (+1.5) |
| ARC-AGI-2 (reasoning) | 73.3% | 77.1% | Gemini (+3.8) |
| AIME 2025 (math) | - | 100% | Gemini |
| SWE-bench Verified (coding) | 77.2% | 80.6% | Gemini (+3.4) |
| Terminal-Bench 2.0 (agentic) | 75.1% | 68.5% | GPT-5.4 (+6.6) |
| OSWorld-Verified (desktop) | 75.0% | - | GPT-5.4 |
| GDPval (knowledge work) | 83.0% | - | GPT-5.4 |
| MMMU Pro (visual) | 81.2% | 81.0% | Tied |
| MCP Atlas (tool coordination) | 67.2% | 69.2% | Gemini (+2.0) |
| WebArena-Verified (browser) | 67.3% | - | GPT-5.4 |
| Spreadsheet modeling | 87.5% | - | GPT-5.4 |
The benchmark wins split clearly by category. Gemini leads on reasoning, math, science, and coding. GPT-5.4 leads on desktop automation, enterprise productivity, and browser navigation. MMMU Pro (visual reasoning) is basically tied.
Pricing Analysis
| Cost Factor | GPT-5.4 | Gemini 3.1 Pro |
|---|---|---|
| Input (per 1M tokens) | $2.50 | $2.00 (<=200K) / $4.00 (>200K) |
| Output (per 1M tokens) | $15.00 | $12.00 (<=200K) / $18.00 (>200K) |
| Batch API | TBD | $1.00/$6.00 (50% off) |
| Context Caching | TBD | $0.20/M |
| Premium tier | $30/$180 (Pro) | N/A |
| 100M output tokens/month | $1,500 | $1,200 |
At standard rates, Gemini is 20% cheaper on both input and output for prompts under 200K tokens. Above 200K tokens, Gemini's extended pricing ($4.00/$18.00) narrows the gap - Gemini remains cheaper on input but costs more on output than GPT-5.4's flat $15.
Gemini's Batch API at $1.00/$6.00 and context caching at $0.20/M are significant advantages for high-volume and repetitive workloads. GPT-5.4 hasn't yet published batch or caching pricing.
Verdict
Choose GPT-5.4 if computer use is part of your workflow. No Gemini model currently offers autonomous desktop interaction, and GPT-5.4's 75% OSWorld score represents a real, deployable capability. Also choose GPT-5.4 for enterprise productivity tasks - spreadsheet analysis, financial modeling, document-heavy business workflows - where the GDPval and spreadsheet benchmarks show clear advantages. The Pro variant gives access to maximum reasoning compute when needed.
Choose Gemini 3.1 Pro if you need the deepest reasoning on science, math, or abstract problems. A perfect AIME 2025 score, 94.3% GPQA Diamond, and 77.1% ARC-AGI-2 are the highest recorded by any model. Also choose Gemini for multimodal workloads involving audio or video, and for cost-sensitive production deployments where the 20% pricing advantage and batch API discounts compound at scale. The coding edge (80.6% vs 77.2% SWE-bench) also favors Gemini.
The practical choice depends on whether you're building tools that interact with software or tools that reason about information. GPT-5.4 is the better choice for agentic workflows that need to click buttons, fill forms, and navigate applications. Gemini is the better choice for analytical workflows that need to reason deeply about scientific data, solve math problems, or process video and audio alongside text. At similar price points, the deciding factor is capability match, not cost. For a framework on routing between models, see our guide on how to choose the right LLM in 2026.
Sources
