Google: Gemma 4 31B

Public pricingIntelligence 80/100Large memory視覚ツール利用

Google: Gemma 4 31B は マルチモーダル モデルで、マルチモーダル推論と分析 に向いています。マルチモーダル入力処理、深い推論と計画、262K tokensのコンテキスト、低コストの特性を組み合わせ、マルチモーダル推論と分析 で安定した動作を支えます。品質・速度・コスト が重要な場面に合っており、安定した出力、柔軟な導入、拡張性を求めるチームに実用的です。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。

Input

$0.13/1M

Output

$0.38/1M

Cached

$0.02/1M

Batch

$0.07/1M

Calculate your Gemma 4 31B bill.

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What would Gemma 4 31B cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

Gemma 4 31B at a glance.

Memory

262,144

tokens

Max reply

32,768

tokens

Memory tier

Large

an entire book or large codebase

Tokenizer

sentencepiece

Released

Apr 2026

Training cutoff

Oct 2025

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • mmlu_pro

    85.2

  • livecodebench

    80

  • aa_intelligence_index

    39

  • chatbot_arena_elo

    1452

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Gemma 4 31B

  • Screenshot analysis, image understanding, or document OCR.
  • Agentic workflows that call tools or APIs.
  • Long documents, full codebases, or extensive chat histories.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Very latency-sensitive, real-time apps where every millisecond counts.

Alternatives

Similar models to compare.

FAQ

Gemma 4 31B — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Gemma 4 31B costs roughly $25 per month. Input is $0.13 /1M tokens and output is $0.38 /1M tokens.
Gemma 4 31B has a 262,144-token context window (large memory — an entire book or large codebase). That means you can fit about 49,152 words of input and history in a single call.
Beyond text generation, Gemma 4 31B supports understanding images, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Gemma 4 31B was released in April 2026, with training data cut off around October 2025.
Models in a similar class include Gemini 2.0 Flash, Gemini 2.5 Flash Lite, Gemini 2.5 Flash Lite Preview 09-2025. The "Similar models" section below this FAQ links into each.

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