Model Comparison
Gemma 3 12B vs Phi 4Which is better in 2026?
Gemma 3 12B shows notably better performance in the majority of benchmarks. Gemma 3 12B is 1.4x cheaper per token.
Verdict: Gemma 3 12B vs Phi 4 — which is better?
Gemma 3 12B (by Google) and Phi 4 (by Microsoft) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Gemma 3 12B outperforms in 4 benchmarks (HumanEval, IFEval, MATH, SimpleQA), while Phi 4 is better at 2 benchmarks (GPQA, MMLU-Pro). Gemma 3 12B shows notably better performance in the majority of benchmarks.
On price, Gemma 3 12B is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemma 3 12B also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Choose Gemma 3 12B if…
- you want the strongest raw capability — it leads on 4 of 6 shared benchmarks
- cost matters — it's about 1.4x cheaper per token
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Mar 2025
Choose Phi 4 if…
- you want predictable pricing at $0.07/M input and $0.14/M output
Performance Benchmarks
Comparative analysis across standard metrics
Gemma 3 12B outperforms in 4 benchmarks (HumanEval, IFEval, MATH, SimpleQA), while Phi 4 is better at 2 benchmarks (GPQA, MMLU-Pro).
Gemma 3 12B shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 3 12B ($0.05/1M tokens) is 1.4x cheaper than Phi 4 ($0.07/1M tokens).
For output processing, Gemma 3 12B ($0.10/1M tokens) is 1.4x cheaper than Phi 4 ($0.14/1M tokens).
In conclusion, Phi 4 is more expensive than Gemma 3 12B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Phi 4 has 2.7B more parameters than Gemma 3 12B, making it 22.5% larger.
Context Window
Maximum input and output token capacity
Gemma 3 12B accepts 131,072 input tokens compared to Phi 4's 16,000 tokens. Gemma 3 12B can generate longer responses up to 131,072 tokens, while Phi 4 is limited to 16,000 tokens.
Input Capabilities
Supported data types and modalities
Gemma 3 12B supports multimodal inputs, whereas Phi 4 does not.
Gemma 3 12B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemma 3 12B
Phi 4
License
Usage and distribution terms
Gemma 3 12B is licensed under Gemma, while Phi 4 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Gemma
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Gemma 3 12B was released on 2025-03-12, while Phi 4 was released on 2024-12-12.
Gemma 3 12B is 3 months newer than Phi 4.
Mar 12, 2025
1.3 years ago
3mo newerDec 12, 2024
1.5 years ago
Knowledge Cutoff
When training data ends
Phi 4 has a documented knowledge cutoff of 2024-06-01, while Gemma 3 12B's cutoff date is not specified.
We can confirm Phi 4's training data extends to 2024-06-01, but cannot make a direct comparison without Gemma 3 12B's cutoff date.
—
Jun 2024
Provider Availability
Gemma 3 12B is available from DeepInfra. Phi 4 is available from DeepInfra.
Gemma 3 12B
Phi 4
Outputs Comparison
Key Takeaways
Gemma 3 12B
View detailsPhi 4
View detailsMicrosoft
Detailed Comparison
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FAQ
Common questions about Gemma 3 12B vs Phi 4.