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Google: Gemini 2.5 Pro Coding Benchmark

Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...

Context1,048,576tokens
Max Output65,536tokens
Inputmodalities
Price$1.25/1M input

Try Google: Gemini 2.5 Pro in Kilo Code

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Coding Performance

Coding benchmarks and performance metrics for development tasks

Security

Enkrypt AI red-team scores for Google: Gemini 2.5 Pro. Each value is the share of successful attacks on a 0–100 scale — lower is safer.

Overall risk
35.8

Lower is safer

Safety

32.5/ 100

Composite safety risk from Enkrypt red-team evaluations. Lower is safer.

NIST

36.0/ 100

Average attack success across NIST-mapped tests: bias, harm, toxicity, CBRN, and insecure code.

OWASP

39.0/ 100

Weighted average of the same tests using OWASP Top 10 for LLMs 2025 risk rankings.

Attack categories

Percentage of successful attacks in each Enkrypt red-team category.

Jailbreak31.1/ 100

Share of jailbreak tests that bypassed the model's safety constraints.

Bias61.1/ 100

Share of tests that elicited biased responses.

Harmful content54.6/ 100

Share of tests that produced dangerous, violent, or hateful content.

Toxicity4.0/ 100

Share of tests that produced toxic or abusive content.

CBRN20.8/ 100

Share of tests that elicited chemical, biological, radiological, or nuclear assistance.

Insecure code38.5/ 100

Share of tests that produced vulnerable or malicious code.

Score
Value
Overall risk
35.8 / 100
Safety
32.5 / 100
NIST
36.0 / 100
OWASP
39.0 / 100
Jailbreak
31.1 / 100
Bias
61.1 / 100
Harmful content
54.6 / 100
Toxicity
4.0 / 100
CBRN
20.8 / 100
Insecure code
38.5 / 100

Security scores from the Enkrypt AI Safety Leaderboard · Last checked Sep 17, 2026

Real-World Usage

Real-world usage statistics from the Kilo Code community

Weekly Token Usage

No ranking data available for this model yet.

Real-world metrics from the Kilo Code Leaderboard

Pricing

Cost per 1 million tokens

Input Tokens
$1.25
per 1M tokens
Output Tokens
$10.00
per 1M tokens

Example Cost

Analyzing a 10,000 line codebase (≈40k input tokens, 10k output tokens) costs approximately $0.1500

Coding Capabilities

Features and parameters relevant to coding tasks

Coding Features

Function Calling
Can call external functions/APIs
Tool Choice
Control over function selection
Structured Outputs
JSON schema validation
Reasoning Tokens
Extended thinking for complex problems

Pricing details from OpenRouter

Technical Details

Architecture and implementation specifications

Specifications
Model ID
google/gemini-2.5-pro
Created
June 17, 2025
Tokenizer
Gemini
Input Modalities
TextImageFileAudioVideo
Context Window
1,048,576 tokens
Max Completion Tokens
65,536 tokens
Input Price
$1.25 per 1M tokens
Output Price
$10.00 per 1M tokens
Cache Read Price
$0.13 per 1M tokens
Cache Write Price
$0.38 per 1M tokens
Content Moderation
Disabled

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