Gemma 4 31B
Intelligence benchmarks
Artificial Analysis indexes - compared with the best open and proprietary models
Intelligence
39.2
AA Index
Coding
38.7
AA Index
Agentic
40.9
AA Index
Intelligence Index - Gemma 4 31B vs. the field
Best open-weight models (you can run locally) and leading proprietary models for context.
Coding Index comparison
Agentic Index comparison
Benchmark data from Artificial Analysis · updated 2026-06-07.
Standard benchmarks
Performance across standard evaluations
| Benchmark | Score |
|---|---|
| GPQA | 85.7 |
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
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Deep dive
Notes, sources, and the full write-up
Gemma 4 31B is a 32.7B-parameter apache-2.0 model from Google. It scores 39.2 on the Artificial Analysis Intelligence Index (coding 38.7). At Q4_K_M it needs roughly 19 GB of VRAM, placing it in the 12–24 GB GPU hardware tier.
Benchmarks
Artificial Analysis Intelligence Index - Gemma 4 31B vs. leading closed models:
| Model | Intelligence | Coding | GPQA |
|---|---|---|---|
| Gemma 4 31B | 39.2 | 38.7 | 85.7 |
| GPT-5.5 (xhigh) | 60.2 | 59.1 | 93.5 |
| Claude Opus 4.8 (max) | 61.4 | 56.7 | 92 |
| Gemini 3.1 Pro Preview | 57.2 | 55.5 | 94.1 |
| Grok 4.3 (high) | 53.2 | 41 | 90.1 |
Source: Artificial Analysis (2026-06-07).
Popularity
Gemma 4 31B has 11,182,475 downloads in the last month on HuggingFace and 2,925 likes.
Frequently asked
Quick answers to common questions
How much VRAM does Gemma 4 31B need?
Gemma 4 31B with 32.7B parameters needs approximately 19 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is Gemma 4 31B better than other google models?
Gemma 4 31B has 32.7B parameters with 262,144 context - a strong choice for general use.
What license is Gemma 4 31B under?
Gemma 4 31B is released under the apache-2.0 license, making it suitable for most commercial and personal projects.
What hardware runs Gemma 4 31B well?
With 32.7B parameters, Gemma 4 31B requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for Gemma 4 31B?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~23 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can Gemma 4 31B's context window handle?
Gemma 4 31B supports a 262,144-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.
What models compete with Gemma 4 31B?
Gemma 4 31B competes with other 16B–49B. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec
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