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Gemini 2.5 Pro

GoogleEstablishedReleased March 2025
Overall Score
Est. 67Prov. #36 of 110
Arena Elo
1449
Categories Ranked
8of 8
Price (1M tokens)
$1.25 in / $5 out
Speed
117tok/s
Context
1M
ProprietaryNon-Reasoning
Confidence
base

According to BenchLM.ai, Gemini 2.5 Pro ranks #36 out of 110 models on the provisional leaderboard with an overall score of 67/100. It does not yet have enough sourced coverage for BenchLM's verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.

Gemini 2.5 Pro is a proprietary model with a 1M token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.

This profile currently has 3 of 152 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.

Its strongest category is Multimodal & Grounded (#19), while its weakest is Instruction Following (#61). This performance profile makes it particularly strong for screenshots, documents, charts, and grounded multimodal workflows.

Ranking Distribution

Category rank across 8 benchmark categories — sorted by best rank

Category Performance

Scores across all benchmark categories (0-100 scale)

Category Breakdown

Agentic

#30
62.3/ 100
Weight: 22%0 benchmarks
Terminal-Bench 2.0BrowseCompOSWorld-VerifiedGAIATAU-benchWebArena

Coding

#47
51.9/ 100
Weight: 20%1 benchmark
SWE-bench VerifiedLiveCodeBenchSWE-bench ProSWE-RebenchSciCode

Reasoning

#39
59.4/ 100
Weight: 17%0 benchmarks
MuSRLongBench v2MRCRv2ARC-AGI-2

Knowledge

#37
67.5/ 100
Weight: 12%2 benchmarks
GPQASuperGPQAMMLU-ProHLEFrontierScienceSimpleQA

Math

#29
74.8/ 100
Weight: 5%0 benchmarks
AIME 2025BRUMO 2025MATH-500FrontierMath

Multilingual

#29
71.1/ 100
Weight: 7%0 benchmarks
MGSMMMLU-ProX

Multimodal

#19
84.1/ 100
Weight: 12%0 benchmarks
MMMU-ProOfficeQA Pro

Inst. Following

#61
60.2/ 100
Weight: 5%0 benchmarks
IFEvalIFBench

Chatbot Arena Performance

Text Overall1449CI: ±2.7109,121 votes
Coding1467CI: ±4.821,834 votes
Math1444CI: ±7.56,753 votes
Instruction Following1442CI: ±4.328,710 votes
Creative Writing1448CI: ±5.615,095 votes
Multi-turn1451CI: ±5.218,390 votes
Hard Prompts1461CI: ±3.553,925 votes
Hard Prompts (English)1458CI: ±4.426,927 votes
Longer Query1460CI: ±4.525,332 votes

Benchmark Details

Only benchmark rows with an attached exact-source record are shown here. Source-unverified manual rows and generated rows are hidden from model pages.

Frequently Asked Questions

How does Gemini 2.5 Pro perform overall in AI benchmarks?

Gemini 2.5 Pro currently ranks #36 out of 110 models on BenchLM's provisional leaderboard with an overall score of 67 (estimated). It is created by Google and features a 1M context window.

Is Gemini 2.5 Pro good for knowledge and understanding?

Gemini 2.5 Pro ranks #37 out of 110 models in knowledge and understanding benchmarks with an average score of 67.5. There are stronger options in this category.

Is Gemini 2.5 Pro good for coding and programming?

Gemini 2.5 Pro ranks #47 out of 110 models in coding and programming benchmarks with an average score of 51.9. There are stronger options in this category.

Does Gemini 2.5 Pro have full benchmark coverage on BenchLM?

Not yet. Gemini 2.5 Pro currently has 3 published benchmark scores out of the 152 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.

What is the context window size of Gemini 2.5 Pro?

Gemini 2.5 Pro has a context window of 1M, which determines how much text it can process in a single interaction.

Last updated: April 20, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

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