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Gemini 2.5 Pro Preview 0325

Added Mar 25, 2025

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Gemini 2.5 Pro Preview 0325. Google's model from March 2025.

  • Reasoning
  • Vision
  • Audio input
Input
Text, Images, Audio
Output
Text
Reasoning effort
low · medium · high
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$2.50
Output
$10.00
Cache read
$0.25

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
65.5K
Average output (7 days)
1.3K tokens
Longer than 81% of 465 models

Side by side

Gemini 2.5 Pro Preview 0325 compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Gemini 2.5 Pro Preview 0325GoogleThis modelDeepSeek V3.2DeepSeekRemove
ProviderGoogleDeepSeek
Discovery tierBalancedOpen weights
AddedMar 25, 2025Dec 1, 2025
Limits
Context window1.05MBest163K
Max output65.54K65.54K
Average output1.3K tokens408 tokens
Pricing, USD per 1M tokens
Input$2.50$0.21Best
Output$10.00$0.31Best
Cache read$0.25$0.0216Best
Performance
Throughput—46.8 tok/s
Time to first token—3.2 s
Request success (24h)—99.6%
Benchmark indexes
Intelligence Index16.1Best16.0
Coding Index33.3—
Math Index87.7Best59.0
Capabilities
ReasoningYesNo
ToolsNoYes
VisionYesNo
Structured outputNoYes
PDF inputNoYes
Audio inputYesNo
Reasoning effortlow, medium, high—

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Gemini 2.5 Pro Preview 0325
  • DeepSeek V3.2

Intelligence Index

  • Gemini 2.5 Pro Preview 032516.1
  • DeepSeek V3.216.0

Gemini 2.5 Pro Preview 0325: Better than 41% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Gemini 2.5 Pro Preview 0325: 33.3
    • DeepSeek V3.2: —

  • Math Index

    Composite of the math evaluations

    • Gemini 2.5 Pro Preview 0325: 87.7Top
    • DeepSeek V3.2: 59.0

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Gemini 2.5 Pro Preview 0325: 2.2%
    • DeepSeek V3.2: —

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Gemini 2.5 Pro Preview 0325: 0.0%
    • DeepSeek V3.2: —

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Gemini 2.5 Pro Preview 0325: 302 Elo
    • DeepSeek V3.2: —

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Gemini 2.5 Pro Preview 0325: 455 Elo
    • DeepSeek V3.2: —

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Gemini 2.5 Pro Preview 0325: 10.2%
    • DeepSeek V3.2: —

  • AA-LCRv1.1

    Reasoning across long documents

    • Gemini 2.5 Pro Preview 0325: 69.0%Top
    • DeepSeek V3.2: 45.7%

  • MLCR-AA

    Long-context reasoning over medical records

    • Gemini 2.5 Pro Preview 0325: 12.2%
    • DeepSeek V3.2: —

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Gemini 2.5 Pro Preview 0325: 22.5%Top
    • DeepSeek V3.2: 11.2%

  • GPQA Diamond

    Graduate-level science questions

    • Gemini 2.5 Pro Preview 0325: 84.4%Top
    • DeepSeek V3.2: 75.1%

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Gemini 2.5 Pro Preview 0325: 86.2%Top
    • DeepSeek V3.2: 83.7%

  • IFBench

    Following precise output instructions

    • Gemini 2.5 Pro Preview 0325: 48.7%
    • DeepSeek V3.2: 49.0%Top

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Gemini 2.5 Pro Preview 0325: 0.0%
    • DeepSeek V3.2: —

  • SciCode

    Scientific computing in Python

    • Gemini 2.5 Pro Preview 0325: 46.3%
    • DeepSeek V3.2: —

  • LiveCodeBench

    Recent competitive programming problems

    • Gemini 2.5 Pro Preview 0325: 80.1%Top
    • DeepSeek V3.2: 59.3%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Gemini 2.5 Pro Preview 0325: 87.7%Top
    • DeepSeek V3.2: 59.0%

  • AIME

    Competition mathematics

    • Gemini 2.5 Pro Preview 0325: 88.7%
    • DeepSeek V3.2: —

  • MATH-500

    Competition math problems

    • Gemini 2.5 Pro Preview 0325: 96.7%
    • DeepSeek V3.2: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Gemini 2.5 Pro Preview 0325: 26.5%
    • DeepSeek V3.2: 32.6%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Gemini 2.5 Pro Preview 0325: 54.1%
    • DeepSeek V3.2: 78.9%Top

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Gemini 2.5 Pro Preview 0325: 69.0%Top
    • DeepSeek V3.2: 45.7%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-2.5-pro-preview-03-25",
    "reasoning_effort": "medium",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="gemini-2.5-pro-preview-03-25",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Google

Other Google models, starting with the same family.