OpenGPTEvidence-based model decisionsCURATED MODEL COMPARISON
Gemma 4 31B vs Phi-4
Gemma 4 31B vs Phi-4: Compare open-weight candidates while keeping hardware, serving, license, and operational requirements in the final decision. Compare exact official model IDs using published signals, provider links, and clearly separated family-level guidance.
Updated:Published data side by side
Each value keeps its original source and scale. Missing data is not treated as zero, and OpenGPT does not create a composite winner.
| Ranking angle | Gemma 4 31B | Phi-4 |
|---|---|---|
| User preference | Rank 58Published value: 1451Original ranking: LMArena ↗Official identity mapping ↗Research edition: 2026-08 · Aug 8, 2026 | Rank 289Published value: 1256Original ranking: LMArena ↗Official identity mapping ↗Research edition: 2026-08 · Aug 8, 2026 |
| Intelligence index | No linked comparable data | No linked comparable data |
| Objective tasks | No linked comparable data | No linked comparable data |
| Cost per successful task | No linked comparable data | No linked comparable data |
| Open-weight models | No linked comparable data | No linked comparable data |
This page organizes published third-party data. OpenGPT did not rerun the underlying evaluations.
What to validate
These strengths and limits describe the wider model family from official positioning, not measured results for this exact version.
Gemma 4 31B
google/gemma-4-31B-itFamily strengths
Downloadable models support private and customizable deployments. Several sizes make local and constrained-hardware experiments practical.
Family limitations
Smaller footprints trade capability for resource efficiency. Users own serving, safety, updates, and license compliance.
Phi-4
microsoft/phi-4Family strengths
Small footprints can suit on-device and low-resource scenarios. Open models allow adaptation and private execution.
Family limitations
Compact size creates task and capacity trade-offs. Device-specific speed and quality must be measured on target hardware.
Continue with your decision
Use the interactive matrix to add more models, then validate the final two on your own prompts and constraints.