Pairwise benchmark snapshot · Aug 16, 2026

Gemini 2.5 Pro vs GPT-5 benchmark

Name: Gemini 2.5 Pro vs GPT-5 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Gemini 2.5 Pro (Google) and GPT-5 (OpenAI) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, GPT-5 is ahead by 208 points (1,558 vs 1,350; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, GPT-5 resolves 68.4% versus 63.8% (seed-bootstrap (Aug 1, 2026)). Gemini 2.5 Pro streams faster (95 tok/s) while Gemini 2.5 Pro is the cheaper output token ($10/1M). Gemini 2.5 Pro has the larger context window (1M tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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Google

Gemini 2.5 Pro

Previous Google long-context flagship.

Elo 1,350$10/1M out

OpenAI

GPT-5

OpenAI flagship reasoning model for 2025–26. Strong general preference Elo and multimodal coverage.

Elo 1,558$10/1M out

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Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 2.5 Pro (3)vsGPT-5 (5)

Gemini 2.5 Pro: 3W (38%)Overall: GPT-5GPT-5: 5W (62%)

← Gemini 2.5 Pro2 tiesGPT-5 →

GPT-5 (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,350vs1,558

Coding Elo

—vs1,540

SWE-bench

63.8%vs68.4%

LiveBench

57.1%vs69.8%

GPQA Diamond

76.4%vs85.2%

Gemini 2.5 Pro: 0WGPT-5: 5W

Gemini 2.5 Pro (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

95 tok/svs78 tok/s

Time to first token

210 msvs290 ms

Gemini 2.5 Pro: 2WGPT-5: 0W

Gemini 2.5 Pro (1/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$10/1Mvs$10/1M

Input price

$1.25/1Mvs$1.25/1M

Context window

1Mvs400k

Gemini 2.5 Pro: 1WGPT-5: 0W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageGPT-5 3/6

Preference Elo

GPT-5

208 pts advantage

Throughput Speed

Gemini 2.5 Pro

17 tok/s faster

Price Efficiency

Gemini 2.5 Pro

Same token price

Full Benchmark Score Matrix

—

Elo

High is better

1,350

EloHigh is better

1,558+15%

Code Elo

High is better

—

Code EloHigh is better

1,540

LiveBench

High is better

57.1%

LiveBenchHigh is better

69.8%+22%

SWE-bench

High is better

63.8%

SWE-benchHigh is better

68.4%+7%

GPQA

High is better

76.4%

GPQAHigh is better

85.2%+12%

TTFT

Low is better

+38%210 ms

TTFTLow is better

290 ms

Speed

High is better

+22%95 tok/s

SpeedHigh is better

78 tok/s

In $

Low is better

$1.25/1M

In $Low is better

$1.25/1M

Out $

Low is better

$10/1M

Out $Low is better

$10/1M

Context

High is better

+162%1M

ContextHigh is better

400k

Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

Gemini 2.5 Pro$193.75 / mo

In: $43.75Out: $150.00

GPT-5$193.75 / mo

In: $43.75Out: $150.00

Key Selection Recommendations

1
GPT-5:Pick GPT-5 when repo-level coding accuracy is the constraint.
2
Gemini 2.5 Pro:Pick Gemini 2.5 Pro when you are optimizing output cost.
3
Gemini 2.5 Pro:Pick Gemini 2.5 Pro when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsGPT-5

Higher SWE-bench (68.4%).

High-volume chatGemini 2.5 Pro

Lower output list price ($10/1M).

Voice / low-latency UIGemini 2.5 Pro

Lower TTFT (210 ms).

Long-document RAGGemini 2.5 Pro

Larger window (1M).

Screenshots / visionGPT-5

Both accept images. Defaulting to the higher-Elo side (GPT-5).

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	GPT-5	Higher SWE-bench (68.4%).
High-volume chat	Gemini 2.5 Pro	Lower output list price ($10/1M).
Voice / low-latency UI	Gemini 2.5 Pro	Lower TTFT (210 ms).
Long-document RAG	Gemini 2.5 Pro	Larger window (1M).
Screenshots / vision	GPT-5	Both accept images. Defaulting to the higher-Elo side (GPT-5).

Related Editorial Dispatches & Benchmark Notes

View all news

launchAug 8, 2025

GPT-5 (2025) remains the legacy OpenAI flagship baseline

Still a common compare target. 5.6 Sol replaced it as the buy; GPT-5 stays for old URLs.

launchMar 25, 2025

Gemini 2.5 Pro remains the previous Google long-context flagship

2025-03 row. 3.x Pro replaced it. Kept for old “2.5 pro vs gpt-4o” inbound.

Community Sentiment

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LIVE

Google

Gemini 2.5 Pro

Elo 1,350

LiveBench57.1%

SWE-bench63.8%

Speed95 tok/s

Output cost$10/1M

OpenAI

GPT-5

Elo 1,558

LiveBench69.8%

SWE-bench68.4%

Speed78 tok/s

Output cost$10/1M

Frequently Asked Questions

Which is better overall, Gemini 2.5 Pro or GPT-5?: GPT-5 has the higher preference Elo in our latest snapshot (1,558). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Gemini 2.5 Pro or GPT-5?: GPT-5 leads SWE-bench at 68.4% vs 63.8%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Gemini 2.5 Pro output tokens are $10/1M versus $10/1M. Input prices and retry rates still move the real bill.
Which is faster, Gemini 2.5 Pro or GPT-5?: Gemini 2.5 Pro has the lower time-to-first-token (210 ms vs 290 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Gemini 2.5 Pro accepts 1M tokens versus 400k.
Can I self-host either model?: Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Gemini 2.5 Pro and GPT-5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Gemini 2.5 Pro matchups →|All GPT-5 matchups →

Gemini 2.5 Pro vs Gemini 1.5 Pro (previous gemini-pro)Gemini 2.5 Pro vs Gemini 3 Pro (next gemini-pro)GPT-5 vs GPT-4.5 Orion (previous gpt-flagship)GPT-5 vs GPT-5.6 Sol (next gpt-flagship)Gemini 2.0 Flash Thinking vs GPT-5 Gemini 3 Flash vs GPT-5

Gemini 2.5 Pro vs GPT-5 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 2.5 Pro (3)vsGPT-5 (5)

Gemini 2.5 Pro: 3W (38%)Overall: GPT-5GPT-5: 5W (62%)

← Gemini 2.5 Pro2 tiesGPT-5 →

GPT-5 (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,350vs1,558

Coding Elo

—vs1,540

SWE-bench

63.8%vs68.4%

LiveBench

57.1%vs69.8%

GPQA Diamond

76.4%vs85.2%

Gemini 2.5 Pro: 0WGPT-5: 5W

Gemini 2.5 Pro (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

95 tok/svs78 tok/s

Time to first token

210 msvs290 ms

Gemini 2.5 Pro: 2WGPT-5: 0W

Gemini 2.5 Pro (1/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$10/1Mvs$10/1M

Input price

$1.25/1Mvs$1.25/1M

Context window

1Mvs400k

Gemini 2.5 Pro: 1WGPT-5: 0W

Recommended Workload Routing

Repo / coding agentsGPT-5

Higher SWE-bench (68.4%).

High-volume chatGemini 2.5 Pro

Lower output list price ($10/1M).

Voice / low-latency UIGemini 2.5 Pro

Lower TTFT (210 ms).

Long-document RAGGemini 2.5 Pro

Larger window (1M).

Screenshots / visionGPT-5

Both accept images. Defaulting to the higher-Elo side (GPT-5).

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	GPT-5	Higher SWE-bench (68.4%).
High-volume chat	Gemini 2.5 Pro	Lower output list price ($10/1M).
Voice / low-latency UI	Gemini 2.5 Pro	Lower TTFT (210 ms).
Long-document RAG	Gemini 2.5 Pro	Larger window (1M).
Screenshots / vision	GPT-5	Both accept images. Defaulting to the higher-Elo side (GPT-5).

Frequently Asked Questions

Which is better overall, Gemini 2.5 Pro or GPT-5?

GPT-5 has the higher preference Elo in our latest snapshot (1,558). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Gemini 2.5 Pro or GPT-5?

GPT-5 leads SWE-bench at 68.4% vs 63.8%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Gemini 2.5 Pro output tokens are $10/1M versus $10/1M. Input prices and retry rates still move the real bill.

Which is faster, Gemini 2.5 Pro or GPT-5?

Gemini 2.5 Pro has the lower time-to-first-token (210 ms vs 290 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Gemini 2.5 Pro accepts 1M tokens versus 400k.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Gemini 2.5 Pro and GPT-5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

GPT-5

Gemini 2.5 Pro

Gemini 2.5 Pro

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

GPT-5 (2025) remains the legacy OpenAI flagship baseline

Gemini 2.5 Pro remains the previous Google long-context flagship

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

Gemini 2.5 Pro

GPT-5

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

GPT-5

Gemini 2.5 Pro

Gemini 2.5 Pro

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

GPT-5 (2025) remains the legacy OpenAI flagship baseline

Gemini 2.5 Pro remains the previous Google long-context flagship

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Gemini 2.5 Pro

GPT-5

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons