AI Models · Compare

GPT-5.5 vs Gemini 2.5 Pro

Which AI model is better in 2026? Compare GPT-5.5 and Gemini 2.5 Pro on benchmarks, pricing, speed, context window, and real-world fit.

Quick summary

Gemini 2.5 Pro is currently the stronger overall pick for math, context, speed, and price. GPT-5.5 wins on reasoning and coding. Gemini 2.5 Pro is also cheaper on blended API price ($2.19 vs $7.50 / 1M).

Overall winner

Gemini 2.5 Pro

View Gemini 2.5 Pro review

GPT-5.5 wins

  • Reasoning
  • Coding

Gemini 2.5 Pro wins

  • Math
  • Context
  • Speed
  • Price

Want to compare different models?

Pick any two models
OpenAI

GPT-5.5

ProprietaryMar 2026

OpenAI’s 2026 flagship — strongest at reasoning, coding and tool use.

Open docs
Google

Gemini 2.5 Pro

ProprietarySep 2025

2M-token context + native multimodality — unbeatable for huge docs.

Open docs

GPT-5.5 vs Gemini 2.5 Pro: overview

GPT-5.5 (OpenAI) and Gemini 2.5 Pro (Google) are frequently compared by teams choosing an AI stack in 2026. GPT-5.5: OpenAI’s 2026 flagship — strongest at reasoning, coding and tool use. Gemini 2.5 Pro: 2M-token context + native multimodality — unbeatable for huge docs. This GPT-5.5 vs Gemini 2.5 Pro comparison covers benchmarks, pricing, context window, speed, modalities, strengths, weaknesses, and who should pick which model.

GPT-5.5 is proprietary with a 400k-token context window and a blended API price near $7.50 / 1M tokens (intelligence index 82/100). Gemini 2.5 Pro is proprietary with 2M context at about $2.19 blended / 1M (intelligence 78/100). Those gaps drive most “GPT-5.5 vs Gemini 2.5 Pro” searches — quality versus cost, closed versus open, cloud versus self-host.

Where they differ most: GPT-5.5 tends to lead on reasoning and coding, while Gemini 2.5 Pro leads on math, context, speed, and price. Choose Gemini 2.5 Pro when you want the stronger overall profile on our scorecard; validate with your own evals before migrating production traffic.

GPT-5.5 is often shortlisted for agentic workflows, complex coding, and hard math & research. Gemini 2.5 Pro fits whole-codebase analysis, long-doc workflows, and video qa. Scroll to pricing, real-world tasks, and the who-should-choose section for decision support.

People search “GPT-5.5 vs Gemini 2.5 Pro”, “which is better”, and “GPT-5.5 vs Gemini 2.5 Pro pricing” for the same reason: switching models is expensive if quality drops, and staying put is expensive if you overpay. Use the winner card for a fast answer, the head-to-head table for receipts, and the editorial verdict for a human recommendation. GPT-5.5 currently ranks among frontier options from OpenAI; Gemini 2.5 Pro is a hosted alternative from Google. If API pricing is your main concern, start with the pricing section; for multimodal workloads, check vision/audio rows in technical differences; for agents and long documents, prioritize context and reasoning wins.

Head to head

Spec
GPT-5.5
Gemini 2.5 Pro
Winner
Reason
Intelligence index↑ better
Winner82
78
GPT-5.5
GPT-5.5 leads on the composite intelligence index (82 vs 78).
Speed↑ better
95 tok/s
Winner110 tok/s
Gemini 2.5 Pro
Gemini 2.5 Pro generates tokens faster (110 vs 95 tok/s).
Time to first token↓ better
Winner0.42 s
0.7 s
GPT-5.5
GPT-5.5 starts streaming sooner (0.42s vs 0.7s TTFT).
Context window↑ better
400k
Winner2M
Gemini 2.5 Pro
Gemini 2.5 Pro wins with 2M tokens — about 5.0× GPT-5.5.
Max output↑ better
16k
Winner66k
Gemini 2.5 Pro
Gemini 2.5 Pro wins this row (65536 vs 16000).
Input price↓ better
$5.00 / 1M tokens
Winner$1.25 / 1M tokens
Gemini 2.5 Pro
Gemini 2.5 Pro is cheaper (~4.0× lower on this price row).
Output price↓ better
$15.00 / 1M tokens
Winner$5.00 / 1M tokens
Gemini 2.5 Pro
Gemini 2.5 Pro is cheaper (~3.0× lower on this price row).
Blended price↓ better
$7.50 / 1M tokens
Winner$2.19 / 1M tokens
Gemini 2.5 Pro
Gemini 2.5 Pro is cheaper (~3.4× lower on this price row).
License
Proprietary
Proprietary
Qualitative / categorical row
Input modalities
text, image
text, image, audio, video
Qualitative / categorical row
Output modalities
text
text
Qualitative / categorical row

Pricing comparison

API cost is often the deciding factor in GPT-5.5 vs Gemini 2.5 Pro for high-volume apps. Figures below use catalog list prices with a 3:1 input:output blend for monthly estimates. Cached input, batch, and realtime surcharges vary by provider — confirm on official docs.

API costGPT-5.5Gemini 2.5 Pro
Input / 1M tokens$5.00$1.25
Output / 1M tokens$15.00$5.00
Blended (3:1) / 1M$7.50$2.19
Est. cost @ 1M blended tokens$7.50$2.19
Est. cost @ 10M blended tokens$75.00$21.90
Est. cost @ 100M blended tokens$750.00$219.00

Cached input, batch API, and realtime surcharges are provider-specific and not always published in our catalog — verify on official pricing pages.

Benchmark showdown

MMLU
GPT-5.5
90.2
Gemini 2.5 Pro
89.5
MMLU Pro
GPT-5.5
78.0
Gemini 2.5 Pro
78.5
GPQA
GPT-5.5
62.5
Gemini 2.5 Pro
66.0
MATH
GPT-5.5
89.1
Gemini 2.5 Pro
91.0
HumanEval
GPT-5.5
93.0
Gemini 2.5 Pro
91.5

GPT-5.5 leads on MMLU and HumanEval, indicating stronger coding and reasoning-oriented scores. Gemini 2.5 Pro leads on MMLU Pro, GPQA, and MATH. Gemini 2.5 Pro remains attractive for production deployments on price. Raw benchmarks shortlist models — run task-specific evals before you switch.

Real-world performance

Beyond academic scores, here is how GPT-5.5 vs Gemini 2.5 Pro tends to split common product tasks based on catalog strengths, price, and modalities.

TaskWinner
CodingGPT-5.5
Blog writingGPT-5.5
ResearchGemini 2.5 Pro
Customer supportGemini 2.5 Pro
Cheap API / high volumeGemini 2.5 Pro
AI agentsGemini 2.5 Pro
SummarizationGPT-5.5
TranslationGPT-5.5
Vision / multimodalGPT-5.5
Self-hosting / open weightsGemini 2.5 Pro

Technical differences

FeatureGPT-5.5Gemini 2.5 Pro
ProviderOpenAIGoogle
LicenseProprietaryProprietary
Pricing modeltokenstokens
Context window400k tokens2M tokens
Max output16k tokens66k tokens
Vision inputYesYes
Audio inputNoYes
Text outputYesYes
Image outputNoNo
Video outputNoNo
Audio outputNoNo
Self-host friendlyNoNo
DocsAvailableAvailable

Strengths, weaknesses and best-for

GPT-5.5
Strengths
  • Best-in-class reasoning
  • Huge 400k context
  • Strong tool use and agents
Weaknesses
  • Expensive vs Sonnet for non-reasoning tasks
  • Higher latency than gpt-5.5-mini
Best for
  • Agentic workflows
  • Complex coding
  • Hard math & research
Gemini 2.5 Pro
Strengths
  • 2M context
  • Native video understanding
  • Strong on math
Weaknesses
  • Output ceiling lower than competitors
Best for
  • Whole-codebase analysis
  • Long-doc workflows
  • Video QA

Who should choose which

Choose GPT-5.5 if

  • You need stronger reasoning, coding, or math quality
  • Agentic workflows
  • Complex coding

Choose Gemini 2.5 Pro if

  • You need stronger reasoning, coding, or math quality
  • You need a larger context window
  • You care about faster token throughput
  • API budget is the top constraint
  • Whole-codebase analysis

Pros & cons

GPT-5.5

Pros

  • Best-in-class reasoning
  • Huge 400k context
  • Strong tool use and agents

Cons

  • Expensive vs Sonnet for non-reasoning tasks
  • Higher latency than gpt-5.5-mini

Gemini 2.5 Pro

Pros

  • 2M context
  • Native video understanding
  • Strong on math

Cons

  • Output ceiling lower than competitors

Editorial verdict

Gemini 2.5 Pro edges this matchup — with caveats

Gemini 2.5 Pro is the better choice when you prioritize math, context, speed, and price. GPT-5.5 stands out for reasoning and coding, making it a strong option when those dimensions matter more than raw leaderboard rank. If maximum measured performance matters, Gemini 2.5 Pro wins this matchup. If your niche constraints matter more, GPT-5.5 is difficult to beat. Always confirm with a bake-off on your real prompts before cutting over.

Still deciding? Read the full GPT-5.5 review and Gemini 2.5 Pro review, or open the full AI models table.

GPT-5.5 vs Gemini 2.5 Pro — frequently asked questions

On our scorecard, Gemini 2.5 Pro wins overall (leads on Math, Context, Speed, and Price). The “better” model still depends on your workload — validate with your own evals.

Build the shortlist that fits your stack

Open every model in one place — sortable table with intelligence, speed and price.