Pairwise benchmark snapshot · Aug 16, 2026

Gemini 1.5 Pro vs GPT-5 benchmark

Name: Gemini 1.5 Pro vs GPT-5 AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Gemini 1.5 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 298 points (1,558 vs 1,260; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, GPT-5 resolves 68.4% versus 38% (seed-bootstrap (Aug 1, 2026)). GPT-5 streams faster (78 tok/s) while Gemini 1.5 Pro is the cheaper output token ($5/1M). Gemini 1.5 Pro has the larger context window (2M 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 1.5 Pro

First million-token Gemini Pro. Baseline for 1.5 vs 2.5 vs 3.x Pro.

Elo 1,260$5/1M 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 1.5 Pro (3)vsGPT-5 (6)

Gemini 1.5 Pro: 3W (33%)Overall: GPT-5GPT-5: 6W (67%)

← Gemini 1.5 Pro1 tiesGPT-5 →

GPT-5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,260vs1,558

Coding Elo

—vs1,540

SWE-bench

38%vs68.4%

LiveBench

49.2%vs69.8%

GPQA Diamond

58%vs85.2%

Gemini 1.5 Pro: 0WGPT-5: 5W

Tied (1/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

70 tok/svs78 tok/s

Time to first token

240 msvs290 ms

Gemini 1.5 Pro: 1WGPT-5: 1W

Gemini 1.5 Pro (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$5/1Mvs$10/1M

Input price

$1.25/1Mvs$1.25/1M

Context window

2Mvs400k

Gemini 1.5 Pro: 2WGPT-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 AdvantageEven 3–3

Preference Elo

GPT-5

298 pts advantage

Throughput Speed

GPT-5

8 tok/s faster

Price Efficiency

Gemini 1.5 Pro

$5.00/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

1,260

EloHigh is better

1,558+24%

Code Elo

High is better

—

Code EloHigh is better

1,540

LiveBench

High is better

49.2%

LiveBenchHigh is better

69.8%+42%

SWE-bench

High is better

38%

SWE-benchHigh is better

68.4%+80%

GPQA

High is better

58%

GPQAHigh is better

85.2%+47%

TTFT

Low is better

+21%240 ms

TTFTLow is better

290 ms

Speed

High is better

70 tok/s

SpeedHigh is better

78 tok/s+11%

In $

Low is better

$1.25/1M

In $Low is better

$1.25/1M

Out $

Low is better

+100%$5/1M

Out $Low is better

$10/1M

Context

High is better

+400%2M

ContextHigh is better

400k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 39% with Gemini 1.5 Pro

Monthly Volume50M tokens/mo

Quick Presets:

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

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

Gemini 1.5 Pro$118.75 / mo

In: $43.75Out: $75.00

GPT-5$193.75 / mo

In: $43.75Out: $150.00

Estimated Cost Delta

Gemini 1.5 Pro is estimated to save $75.00/month ($900/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
GPT-5:Pick GPT-5 when repo-level coding accuracy is the constraint.
2
Gemini 1.5 Pro:Pick Gemini 1.5 Pro when you are optimizing output cost.
3
Gemini 1.5 Pro:Pick Gemini 1.5 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 1.5 Pro

Lower output list price ($5/1M).

Voice / low-latency UIGemini 1.5 Pro

Lower TTFT (240 ms).

Long-document RAGGemini 1.5 Pro

Larger window (2M).

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 1.5 Pro	Lower output list price ($5/1M).
Voice / low-latency UI	Gemini 1.5 Pro	Lower TTFT (240 ms).
Long-document RAG	Gemini 1.5 Pro	Larger window (2M).
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.

Community Sentiment

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LIVE

Google

Gemini 1.5 Pro

Elo 1,260

LiveBench49.2%

SWE-bench38%

Speed70 tok/s

Output cost$5/1M

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 1.5 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 1.5 Pro or GPT-5?: GPT-5 leads SWE-bench at 68.4% vs 38%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Gemini 1.5 Pro output tokens are $5/1M versus $10/1M. Input prices and retry rates still move the real bill.
Which is faster, Gemini 1.5 Pro or GPT-5?: Gemini 1.5 Pro has the lower time-to-first-token (240 ms vs 290 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Gemini 1.5 Pro accepts 2M 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 1.5 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 1.5 Pro matchups →|All GPT-5 matchups →

Gemini 1.5 Pro vs Gemini 2.5 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 3 Pro vs GPT-5 Gemini 3 Flash vs GPT-5 Gemini 2.0 Flash Thinking vs GPT-5

Gemini 1.5 Pro vs GPT-5 benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 1.5 Pro (3)vsGPT-5 (6)

Gemini 1.5 Pro: 3W (33%)Overall: GPT-5GPT-5: 6W (67%)

← Gemini 1.5 Pro1 tiesGPT-5 →

GPT-5 (5/5)

Intelligence & Reasoning

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

Preference Elo

1,260vs1,558

Coding Elo

—vs1,540

SWE-bench

38%vs68.4%

LiveBench

49.2%vs69.8%

GPQA Diamond

58%vs85.2%

Gemini 1.5 Pro: 0WGPT-5: 5W

Tied (1/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

70 tok/svs78 tok/s

Time to first token

240 msvs290 ms

Gemini 1.5 Pro: 1WGPT-5: 1W

Gemini 1.5 Pro (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$5/1Mvs$10/1M

Input price

$1.25/1Mvs$1.25/1M

Context window

2Mvs400k

Gemini 1.5 Pro: 2WGPT-5: 0W

Recommended Workload Routing

Repo / coding agentsGPT-5

Higher SWE-bench (68.4%).

High-volume chatGemini 1.5 Pro

Lower output list price ($5/1M).

Voice / low-latency UIGemini 1.5 Pro

Lower TTFT (240 ms).

Long-document RAGGemini 1.5 Pro

Larger window (2M).

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 1.5 Pro	Lower output list price ($5/1M).
Voice / low-latency UI	Gemini 1.5 Pro	Lower TTFT (240 ms).
Long-document RAG	Gemini 1.5 Pro	Larger window (2M).
Screenshots / vision	GPT-5	Both accept images. Defaulting to the higher-Elo side (GPT-5).

Frequently Asked Questions

Which is better overall, Gemini 1.5 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 1.5 Pro or GPT-5?

GPT-5 leads SWE-bench at 68.4% vs 38%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Gemini 1.5 Pro output tokens are $5/1M versus $10/1M. Input prices and retry rates still move the real bill.

Which is faster, Gemini 1.5 Pro or GPT-5?

Gemini 1.5 Pro has the lower time-to-first-token (240 ms vs 290 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Gemini 1.5 Pro accepts 2M 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 1.5 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

GPT-5

Gemini 1.5 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

Cast Your Matchup Vote

Community Discussions (0)

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CompareLLM Matrix

Gemini 1.5 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

GPT-5

Gemini 1.5 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

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Gemini 1.5 Pro

GPT-5

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons