GPT-4o and Gemini 3.1 Pro serve different strengths. GPT-4o is a reliable older multimodal model with image understanding and voice in ChatGPT. Gemini 3.1 Pro is newer, cheaper on input ($2 vs $2.50/1M), offers a 1M-token context window (about eight times GPT-4o's 128K) and scored 77.1% on ARC-AGI-2 at launch. For research, large-document analysis and cost-sensitive workloads, Gemini 3.1 Pro is the stronger pick; GPT-4o now mainly suits existing integrations.
OpenAIBalanced
GPT-4o
Legacy multimodal model — kept for existing integrations, not new work.
VS
GooglePremium
Gemini 3.1 Pro
Google's Pro model — 1M context and native multimodal input at $2/$12.
Winner
At a glance
GPT-4o
Gemini 3.1 Pro
Input cost / 1M tokens
$$2.50/1M
$$2.00/1M
Output cost / 1M tokens
$$10.00/1M
$$12.00/1M
Context window
128k tokens
1M tokens
Speed
Fast
Balanced
Price tier
Balanced
Premium
Benchmarks
SWE-bench (coding)
46%
80.6%
Arena Elo
1,295
1,380
MMLU
88.7%
90%
How they compare
Which model wins for each use case — and why.
Research & Long ContextGemini 3.1 Pro wins
Gemini 3.1 Pro has a 1M-token context window against GPT-4o's 128K — about eight times the capacity. For document analysis and research synthesis, this gap is decisive.
PriceGemini 3.1 Pro wins
Gemini 3.1 Pro costs $2/1M input vs GPT-4o's $5/1M — 2.5× cheaper. At scale, this is a very significant saving.
Vision / ImagesGPT-4o wins
GPT-4o has native DALL-E image generation alongside strong vision understanding. Gemini has multimodal support but no equivalent image generation at this tier.
ReasoningGemini 3.1 Pro wins
Gemini 3.1 Pro leads the ARC-AGI-2 reasoning benchmark at 77.1%. GPT-4o is a capable reasoner but trails on the hardest logic tasks.
Ecosystem / IntegrationsGPT-4o wins
GPT-4o benefits from OpenAI's mature API ecosystem, plugin network, and broad third-party integrations. Google is catching up but OpenAI still has the edge here.
Which should you pick?
Pick GPT-4o if…
You need image generation (DALL-E) alongside text in the same platform
Your workflow relies on OpenAI-specific API features, plugins, or assistants
Multimodal tasks combining images, audio, and text are central to your use case
You're already invested in the OpenAI ecosystem and switching cost matters
For most workflows, Gemini 3.1 Pro is the stronger choice.
A capable research model and still Google's current Pro tier, but no longer the long-context leader: its 1M-token window matches Claude Opus 5.5 and is slightly below the GPT-6 family's 1.05M. Choose it for Google Workspace integration and multimodal input; for most research, Claude Opus 5.5 or GPT-6.1 Sol are stronger at a similar price.
The case for each model
What each one is genuinely good at, where it falls down, and when we would steer you away from it.
Our overall pick in this comparison. Against GPT-4o it costs about 11% more per token and takes 8x the context.
Google's Pro-tier Gemini 3 model, released in preview on February 19, 2026, with a 1M-token context window, Deep Think reasoning and $2/$12 pricing.
Input
$2.00/1M
Output
$12.00/1M
Context
1M tokens
Speed
Balanced
What people actually use it for
Analyzing long contracts, codebases, or research papers in a single 1M-token prompt
Due diligence synthesis across large sets of financial documents or legal agreements
Multi-step reasoning across dense technical specifications with Deep Think mode
Where it wins
1M-token context window with native image, audio, video and PDF input
Scored 77.1% on ARC-AGI-2 at its February 2026 launch
$2/$12 per 1M tokens — cheaper output than most premium models
Where it falls down
Slower than Flash for everyday lightweight tasks
Claude Sonnet 5.5 is better for writing quality, at a lower $2/$10
Skip it if
Your primary use case is writing quality or agentic coding — Claude wins both.
Our verdict
A capable research model and still Google's current Pro tier, but no longer the long-context leader: its 1M-token window matches Claude Opus 5.5 and is slightly below the GPT-6 family's 1.05M. Choose it for Google Workspace integration and multimodal input; for most research, Claude Opus 5.5 or GPT-6.1 Sol are stronger at a similar price.
Gemini 3.1 Pro wins on price, context window, and research depth. GPT-4o wins on multimodal/image generation and OpenAI ecosystem fit. For most analytical workloads, Gemini 3.1 Pro is the stronger value.
Which is cheaper — GPT-4o or Gemini?
Gemini 3.1 Pro is significantly cheaper at $2/1M input vs GPT-4o's $5/1M — 2.5× less expensive. Output is also cheaper at $12/1M vs $15/1M.
Which has a bigger context window?
Gemini 3.1 Pro has a 1M-token context window — about eight times GPT-4o's 128K. For large document analysis, this advantage is decisive.
Which is better for coding?
Neither is the top coding pick in 2026 — Claude Sonnet 4.6 leads there. Between the two, GPT-4o is the more familiar coding tool, but Gemini 3.1 Pro handles code competently at a lower price.