Google
Released April 2, 2026

Gemma 4 31B

Google Gemma 4 31B: dense open-weights model built from Gemini 3 research, with built-in thinking, multi-token prediction, and fine-tuning support.

Inputs
Image
Text
Video
Outputs
Text

Model Overview

Capabilities, design details, and architectural traits

Gemma 4 31B - Dense Open Model for Fine-Tuning

Gemma 4 31B is Google's dense model in the Gemma 4 family. Within the Gemma 4 lineup, it is the variant that maximizes raw quality and serves as the primary foundation for fine-tuning, contrasting with the 26B MoE variant which optimizes for inference latency. The entire Gemma 4 family is built from Gemini 3 research and released as open weights.

TraitDetail
ArchitectureDense 31B - not Mixture-of-Experts; all parameters active during inference, prioritizing raw output quality over speed
Multi-Token Prediction (MTP)Supported; universally recommended for all tasks for this model size
Built-in thinking modeStep-by-step reasoning before answering, available across the Gemma 4 family
Quantization checkpointsQAT checkpoints available in compressed-tensors (-w4a16-ct) format

Hybrid Attention Across the Gemma 4 Family

All Gemma 4 models, including the 31B, use a hybrid attention mechanism that interleaves local sliding window attention with full global attention. The final layer is always global. Global layers use unified Keys and Values with Proportional RoPE (p-RoPE) for long-context memory optimization.

Benchmark Performance

Independent evaluations · Artificial Analysis

14.7%
Intelligence
43.4%
Coding Index
4.2%
Agentic Index

Accuracy & Capability Details

GPQA - Graduate Science85.7%
Humanity's Last Exam23.6%
SciCode - Scientific Coding45.5%
Instruction Following75.6%
Long Context Reasoning69.7%
τ²-Bench - Agentic Tasks59.9%
TerminalBench - System Control36.4%

Compare Models Side-by-Side

Evaluate specifications, pricing, and independent benchmark indices

Model Details
General Info
ProviderGoogleAnthropicAnthropic
Release DateApril 2, 2026September 22, 2026September 28, 2026
Knowledge Cutoff--Jun 2026
Context & Limits
Context Window262K
1M
Best Context Window
1M
Best Context Window
Pricing (per 1M tokens)
Input Pricing
$0.17
Best Input Pricing
$4$2
Output Pricing
$0.40
Best Output Pricing
$20$10
Modalities
Inputs
imagetextvideo
textimagefile
textimagefile
Outputs
text
text
text
Benchmarks (0-100)
Intelligence Index13.9
57.6
Best Intelligence Index
56.0
Coding Index33.2--
Agentic Index11.1--
Gemma 4 31B
Claude Opus 5.5
Claude Sonnet 5.5

Humanity's Last Exam

Extremely difficult logical reasoning and knowledge.

12%
Gemma 4 31B
Humanity's Last Exam
Score: 12%
Gemma 4 31B
61%
Claude Opus 5.5
Humanity's Last Exam
Score: 61%
Claude Opus 5.5
55%
Claude Sonnet 5.5
Humanity's Last Exam
Score: 55%
Claude Sonnet 5.5

Long Context Reasoning

Logical reasoning over long context windows.

47%
Gemma 4 31B
Long Context Reasoning
Score: 47%
Gemma 4 31B
85%
Claude Opus 5.5
Long Context Reasoning
Score: 85%
Claude Opus 5.5
83%
Claude Sonnet 5.5
Long Context Reasoning
Score: 83%
Claude Sonnet 5.5

SciCode Benchmark

Scientific coding and mathematical modeling.

41%
Gemma 4 31B
SciCode Benchmark
Score: 41%
Gemma 4 31B
67%
Claude Opus 5.5
SciCode Benchmark
Score: 67%
Claude Opus 5.5
61%
Claude Sonnet 5.5
SciCode Benchmark
Score: 61%
Claude Sonnet 5.5

Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.

Explore more from Google

Other models by Google

Top AI Models

Leading alternatives by intelligence score

View all