gemma-4-31b-it

completions

byopenrouter

gemma-4-31b-it

completions

Published by: googleProvider:

openrouter

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function calling, and multilingual support across 140+ languages. Strong on coding, reasoning, and document understanding tasks. Apache 2.0 license.

Released

Apr 2, 2026

Knowledge

Oct 4, 2025

License

Apache-2.0

Context

262144

Input

$0.14 / 1M tokens

Output

$0.4 / 1M tokens

Capabilities: tools, reasoning

Accepts: text, image

Returns: text

Released Apr 2, 2026Knowledge Cutoff: Oct 4, 2025License: Apache-2.0

Context: 262144 Input: $0.14 / 1M tokensOutput: $0.4 / 1M tokensCapabilities: tools, reasoningAccepts: text, imageReturns: text

Access gemma-4-31b-it through LangDB AI Gateway

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Benchmark Results for gemma-4-31b-it

Category Performance Scores:

Science: Score 78.16 (Top 11% - Rank #39)
Writing: Score 70.72 (Top 11% - Rank #39)
Academia: Score 62.10 (Top 14% - Rank #49)
Marketing: Score 70.75 (Top 7% - Rank #25)
Programming: Score 38.70 (Top 9% - Rank #32)

Overall Performance: 64.0851111111111 average score across all categories

Detailed Benchmark Scores:

Benchmark	Score	Percentile	Domain
HLE	22.70	Top 10%	General Knowledge
GPQA	85.00	Top 11%	STEM (Physics, Chemistry, Biology)
SciCode	43.40	Top 11%	Scientific
MMLU-Pro	85.20	Top 15%	General Knowledge
AA Coding Index	38.70	Top 9%	Programming
AAII	39.20	Top 16%	General

GPQA Score: 85.00 - Graduate-level reasoning benchmark

Model Comparison:

Provider: openrouter

Model Type: completions

Context Size: 262144 tokens

Comparing against 348 models in the database

Category Scores

Benchmark Tests

View Other Benchmarks

HLE

22.7

General Knowledge

GPQA

85.0

STEM (Physics, Chemistry, Biology)

SciCode

43.4

Scientific

MMLU-Pro

85.2

General Knowledge

AA Coding Index

38.7

Programming

AAII

39.2

General

Metric	HLE	GPQA	SciCode	MMLU-Pro	AA Coding Index	AAII
Score	22.7	85.0	43.4	85.2	38.7	39.2

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Code Examples

Integration samples and API usage

Code Samples for gemma-4-31b-it

Python SDK Example:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.us-east-1.langdb.ai/projects/<your_project_id>",
    api_key="<your_api_key>"
)

response = client.chat.completions.create(
    model="gemma-4-31b-it",
    messages=[
        {"role": "user", "content": "Hello, how are you?"}
    ]
)

print(response.choices[0].message.content)

TypeScript SDK Example:

import OpenAI from 'openai';

const client = new OpenAI({
    baseURL: "https://api.us-east-1.langdb.ai/projects/<your_project_id>",
    apiKey: "<your_api_key>"
});

const response = await client.chat.completions.create({
    model: "gemma-4-31b-it",
    messages: [
        { role: "user", content: "Hello, how are you?" }
    ]
});

console.log(response.choices[0].message.content);

cURL Example:

curl -X POST "https://api.us-east-1.langdb.ai/projects/<your_project_id>/v1/chat/completions" \
  -H "Authorization: Bearer <your_api_key>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemma-4-31b-it",
    "messages": [
        {"role": "user", "content": "Hello, how are you?"}
    ]
  }'

Model: gemma-4-31b-it

Provider: openrouter

API Endpoint: $https://api.us-east-1.langdb.ai

Create API Key

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gemma-4-31b-it by openrouter - AI Model Details, Pricing, and Performance Metrics

gemma-4-31b-it

gemma-4-31b-it

Access gemma-4-31b-it through LangDB AI Gateway

Category Scores

Benchmark Tests

Compare with Similar Models

Code Examples

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