Google

Gemini 3.1 Pro — Benchmark Scores, Pricing & Performance Analysis

FLAGSHIPGoogle
Chatbot Arena ELO
1501
Output Speed
65 tok/s
Input Cost
$2.0/1M
Output Cost
$12.0/1M
Context Window
1.0M
Max Output
66K
Accepts
audio, file, image, text, video

Gemini 3.1 Pro by Google demonstrates top-tier general intelligence, excellent coding ability, outstanding mathematical reasoning. View detailed benchmark data including scores across coding, math, reasoning, speed, and cost metrics.

Specifications last checked against the provider on . Benchmark scores carry their own source, linked beside each number.

General Benchmarks

Chatbot Arena ELO
15011st of 74

Human preference ELO from blind head-to-head votes

LMSYS / HuggingFace
MMLU-Pro
92.6%1st of 66

Massive Multitask Language Understanding professional benchmark

HuggingFace Leaderboard
AA Intelligence Index
30.427th of 66

Artificial Analysis composite intelligence score across 10 sub-benchmarks

Artificial Analysis (via OpenRouter)
IFEval
92.0%2nd of 25

Strict instruction following accuracy on verifiable constraints

Google Research

Coding Benchmarks

Website Arena ELO
124637th of 108

Human preference ELO for building a working web page from a brief

Design Arena (via OpenRouter)
LiveCodeBench
75.0%6th of 66

Live competitive programming benchmark

livecodebench.github.io
HumanEval+
93.0%4th of 66

Code generation correctness with extended tests

Papers
SWE-bench Verified
80.6%4th of 67

Real-world software engineering task resolution

swebench.com
AA Coding Index
68.826th of 96

Artificial Analysis composite coding score

Artificial Analysis (via OpenRouter)
Design Arena ELO
125628th of 120

Human preference ELO for building things — websites, UI, games, charts, SVG

Design Arena (via OpenRouter)

Math Benchmarks

GSM8K
98.0%5th of 66

Grade school math word problems

Papers
MATH
93.0%10th of 66

Competition mathematics problem solving

Papers
AIME 2025
95.0%5th of 17

American Invitational Mathematics Examination — competition math

Papers

Reasoning Benchmarks

τ²-Bench Airline
75.3%24th of 93

Multi-turn service agent making tool calls under strict policy constraints

OpenRouter (measured)
ARC-AGI
77.1%1st of 66

Abstraction and Reasoning Corpus for general intelligence

arcprize.org
GPQA Diamond
94.4%1st of 140

Graduate-level science Q&A by domain experts

Papers
AA Agentic Index
10.345th of 70

Artificial Analysis composite score for multi-step tool-using tasks

Artificial Analysis (via OpenRouter)

Speed Benchmarks

Time to First Token
420 ms49th of 92

Latency before first token arrives

Aggregated
Output Speed
65 tok/s61st of 94

Tokens generated per second

Aggregated

Cost Benchmarks

Cached Input Cost
$0.2093rd of 136

Cost per 1M cached input tokens — the price that actually applies to a long agent conversation

OpenRouter API
Output Cost
$12.0355th of 413

Cost per 1M output tokens

OpenRouter API
Input Cost
$2.0336th of 413

Cost per 1M input tokens

OpenRouter API

Context Benchmarks

Context Length
1.0M18th of 451

Maximum context window size

OpenRouter API

Available from 3 providers

The same model costs different amounts depending on who serves it.

ProviderInput / 1MOutput / 1MCached inContextYour key
LLM Gateway$2$12$0.21.0M—
NanoGPT$2$12$0.21.0M—
Poe$2$12$0.21.0M—

Gemini 3.1 Pro — Benchmark Scores Overview

Scores normalized to percentage scale for visual comparison. ELO scores mapped to 0-100 range (1100-1500).

Gemini 3.1 Pro — Frequently Asked Questions

How intelligent is Gemini 3.1 Pro?

Gemini 3.1 Pro scores 1501 on the Chatbot Arena ELO rating, making it one of the top-ranked AI model. This score is based on blind head-to-head human preference voting.

How much does Gemini 3.1 Pro cost?

Gemini 3.1 Pro costs $2.0 per 1M input tokens and $12.0 per 1M output tokens. This is mid-range pricing for its capability level.

How fast is Gemini 3.1 Pro?

Gemini 3.1 Pro generates output at 65 tokens per second, which is slower, prioritizing quality over speed compared to other models. The time to first token is 420 ms.

How good is Gemini 3.1 Pro at coding?

Gemini 3.1 Pro achieves 80.6% on SWE-bench Verified, demonstrating excellent real-world software engineering capability. This benchmark tests the model's ability to resolve actual GitHub issues.

How good is Gemini 3.1 Pro at math and reasoning?

Gemini 3.1 Pro scores 93.0% on the MATH benchmark (competition-level mathematics). It also achieves 94.4% on GPQA Diamond, a graduate-level science reasoning benchmark.

What is the context window of Gemini 3.1 Pro?

Gemini 3.1 Pro has a context window of 1.0M tokens. This determines how much text, conversation history, and code the model can process in a single request.

Who created Gemini 3.1 Pro?

Gemini 3.1 Pro was created by Google. It is classified as a flagship model in our catalogue.

Is Gemini 3.1 Pro open source?

No, Gemini 3.1 Pro is a proprietary model. It is available through Google's API and compatible providers.