Compare the listed model data for Google Gemini 3.1 Pro by Google and OpenAI GPT-5.4 Pro by OpenAI. Benchmark and pricing records are not a controlled test and may change.
Data last updated: 2026-10-16. Verify current model details with each provider.
What the listed data says
Google Gemini 3.1 Pro: 1M tokens; OpenAI GPT-5.4 Pro: 128K tokens. Google Gemini 3.1 Pro has the larger listed context window. Google Gemini 3.1 Pro is listed for coding, reasoning, vision, multimodal input, agentic workflows, long-context tasks; OpenAI GPT-5.4 Pro is listed for coding, reasoning, vision, multimodal input, agentic workflows, long-context tasks. Shared catalog benchmark entries: MMLU: Google Gemini 3.1 Pro 93.8%; OpenAI GPT-5.4 Pro 93.5%; HumanEval: Google Gemini 3.1 Pro 92.1%; OpenAI GPT-5.4 Pro 94.3%; MATH: Google Gemini 3.1 Pro 94.2%; OpenAI GPT-5.4 Pro 93.8%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
Catalog source links
Use these model and provider links to verify current specifications, pricing, and availability.
The listed context windows are 1M tokens and 128K tokens; the larger is 7.81× the smaller.
On shared numeric benchmark entries, MMLU: Google Gemini 3.1 Pro − OpenAI GPT-5.4 Pro = +0.3 percentage points (93.8% vs 93.5%); HumanEval: Google Gemini 3.1 Pro − OpenAI GPT-5.4 Pro = -2.2 percentage points (92.1% vs 94.3%); MATH: Google Gemini 3.1 Pro − OpenAI GPT-5.4 Pro = +0.4 percentage points (94.2% vs 93.8%).
The first listed parameter quantities are ~300B+ (frontier MoE, exact size proprietary) and ~220B+ MoE (professional tier, exact size proprietary); the larger quantity is 1.36× the smaller. Total and active MoE parameters are not directly equivalent.
A release-date gap cannot be calculated from the catalog values (Google Gemini 3.1 Pro: 2026; OpenAI GPT-5.4 Pro: 2026).
Cost example: 1M input and 1M output tokens
A cost example for 1M input plus 1M output tokens cannot be calculated reliably because separate numeric input and output rates are not listed for both models.
Choose Google Gemini 3.1 Pro if…
Choose Google Gemini 3.1 Pro when your task aligns with catalog-listed uses or strengths such as Enterprise multimodal analysis: video understanding, document comprehension, image analysis at scale, Scientific research synthesis from very long research corpora, Complex coding projects requiring codebase-wide context (1M tokens), Advanced mathematical reasoning and scientific problem solving.
Choose OpenAI GPT-5.4 Pro if…
Choose OpenAI GPT-5.4 Pro when your task aligns with catalog-listed uses or strengths such as Enterprise software engineering requiring complex multi-file project management, Advanced data analysis, financial modeling, and quantitative research, Multimodal business intelligence: combining documents, charts, and data, Legal and compliance document analysis at scale.
Via LITHOVEX AI free. Google Gemini API rates apply.
Via LITHOVEX AI free. OpenAI API: premium pricing.
Listed input/output cost per 1M tokens
Separate numeric input/output rates not listed
input $5, output $20 per 1M tokens
License
Proprietary
Proprietary
Coding support
Listed
Listed
Reasoning support
Listed
Listed
Vision input
Listed
Listed
Multimodal
Listed
Listed
Open weights
No
No
Benchmark: MMLU
93.8%
93.5%
Benchmark: HumanEval
92.1%
94.3%
Benchmark: MATH
94.2%
93.8%
Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.
Frequently Asked Questions
What is different between Google Gemini 3.1 Pro and OpenAI GPT-5.4 Pro?
Google Gemini 3.1 Pro: 1M tokens; OpenAI GPT-5.4 Pro: 128K tokens. Google Gemini 3.1 Pro has the larger listed context window. Google Gemini 3.1 Pro is listed for coding, reasoning, vision, multimodal input, agentic workflows, long-context tasks; OpenAI GPT-5.4 Pro is listed for coding, reasoning, vision, multimodal input, agentic workflows, long-context tasks. Shared catalog benchmark entries: MMLU: Google Gemini 3.1 Pro 93.8%; OpenAI GPT-5.4 Pro 93.5%; HumanEval: Google Gemini 3.1 Pro 92.1%; OpenAI GPT-5.4 Pro 94.3%; MATH: Google Gemini 3.1 Pro 94.2%; OpenAI GPT-5.4 Pro 93.8%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
What benchmark values are listed for Google Gemini 3.1 Pro and OpenAI GPT-5.4 Pro?
MMLU: Google Gemini 3.1 Pro 93.8%; OpenAI GPT-5.4 Pro 93.5%; HumanEval: Google Gemini 3.1 Pro 92.1%; OpenAI GPT-5.4 Pro 94.3%; MATH: Google Gemini 3.1 Pro 94.2%; OpenAI GPT-5.4 Pro 93.8%. The catalog values may use different versions and evaluation setups, so they are reference points rather than a controlled head-to-head result.
Which model has the larger listed context window?
Google Gemini 3.1 Pro: 1M tokens; OpenAI GPT-5.4 Pro: 128K tokens. Google Gemini 3.1 Pro has the larger listed context window.
What are the listed costs per million tokens for Google Gemini 3.1 Pro and OpenAI GPT-5.4 Pro?
Google Gemini 3.1 Pro: Separate numeric input/output rates not listed (Via LITHOVEX AI free. Google Gemini API rates apply.). OpenAI GPT-5.4 Pro: input $5, output $20 per 1M tokens (Via LITHOVEX AI free. OpenAI API: premium pricing.). Where separate numeric input and output rates are available, the worked example uses 1M input plus 1M output tokens. Confirm current terms with each provider.
How far apart are the listed release dates for Google Gemini 3.1 Pro and OpenAI GPT-5.4 Pro?
The catalog lists Google Gemini 3.1 Pro as 2026 and OpenAI GPT-5.4 Pro as 2026; a release-date gap cannot be calculated from both records.
When was the comparison data last updated?
The model catalog records 2026-10-16 as its data update date. Provider specifications and prices may have changed since then.
How should I choose between Google Gemini 3.1 Pro and OpenAI GPT-5.4 Pro?
Compare the listed specifications and capabilities, review the benchmark notes, then test both with the same representative prompt for your task. This page does not claim a universal winner.
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