Model Comparison

Phi 4 vs Gemma 3 12B

Gemma 3 12B shows notably better performance in the majority of benchmarks. Gemma 3 12B is 1.4x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

Phi 4 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Gemma 3 12B is better at 4 benchmarks (HumanEval, IFEval, MATH, SimpleQA).

Gemma 3 12B shows notably better performance in the majority of benchmarks.

Mon Apr 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 3 12B costs less

For input processing, Phi 4 ($0.07/1M tokens) is 1.4x more expensive than Gemma 3 12B ($0.05/1M tokens).

For output processing, Phi 4 ($0.14/1M tokens) is 1.4x more expensive than Gemma 3 12B ($0.10/1M tokens).

In conclusion, Phi 4 is more expensive than Gemma 3 12B.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Mon Apr 13 2026 • llm-stats.com
Microsoft
Phi 4
Input tokens$0.07
Output tokens$0.14
Best providerDeepinfra
Google
Gemma 3 12B
Input tokens$0.05
Output tokens$0.10
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

2.7B diff

Phi 4 has 2.7B more parameters than Gemma 3 12B, making it 22.5% larger.

Microsoft
Phi 4
14.7Bparameters
Google
Gemma 3 12B
12.0Bparameters
14.7B
Phi 4
12.0B
Gemma 3 12B

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.

Microsoft
Phi 4
Input16,000 tokens
Output16,000 tokens
Google
Gemma 3 12B
Input131,072 tokens
Output131,072 tokens
Mon Apr 13 2026 • llm-stats.com

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.

Phi 4

Text
Images
Audio
Video

Gemma 3 12B

Text
Images
Audio
Video

License

Usage and distribution terms

Phi 4 is licensed under MIT, while Gemma 3 12B uses Gemma.

License differences may affect how you can use these models in commercial or open-source projects.

Phi 4

MIT

Open weights

Gemma 3 12B

Gemma

Open weights

Release Timeline

When each model was launched

Phi 4 was released on 2024-12-12, while Gemma 3 12B was released on 2025-03-12.

Gemma 3 12B is 3 months newer than Phi 4.

Phi 4

Dec 12, 2024

1.3 years ago

Gemma 3 12B

Mar 12, 2025

1.1 years ago

3mo newer

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.

Phi 4

Jun 2024

Gemma 3 12B

—

Provider Availability

Phi 4 is available from DeepInfra. Gemma 3 12B is available from DeepInfra.

Phi 4

deepinfra logo
Deepinfra
Input Price:Input: $0.07/1MOutput Price:Output: $0.14/1M

Gemma 3 12B

deepinfra logo
Deepinfra
Input Price:Input: $0.05/1MOutput Price:Output: $0.10/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Microsoft
Higher GPQA score (56.1% vs 40.9%)
Higher MMLU-Pro score (70.4% vs 60.6%)
Google
Larger context window (131,072 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
Higher HumanEval score (85.4% vs 82.6%)
Higher IFEval score (88.9% vs 63.0%)
Higher MATH score (83.8% vs 80.4%)
Higher SimpleQA score (6.3% vs 3.0%)

Detailed Comparison

AI Model Comparison Table
Feature
Microsoft
Phi 4
Google
Gemma 3 12B

FAQ

Common questions about Phi 4 vs Gemma 3 12B

Gemma 3 12B shows notably better performance in the majority of benchmarks. Phi 4 is made by Microsoft and Gemma 3 12B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Phi 4 scores MMLU: 84.8%, HumanEval+: 82.8%, HumanEval: 82.6%, MGSM: 80.6%, MATH: 80.4%. Gemma 3 12B scores GSM8k: 94.4%, IFEval: 88.9%, DocVQA: 87.1%, BIG-Bench Hard: 85.7%, HumanEval: 85.4%.
Gemma 3 12B is 1.4x cheaper for input tokens. Phi 4 costs $0.07/M input and $0.14/M output via deepinfra. Gemma 3 12B costs $0.05/M input and $0.10/M output via deepinfra.
Phi 4 supports 16K tokens and Gemma 3 12B supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (16K vs 131K), input pricing ($0.07 vs $0.05/M), multimodal support (no vs yes), licensing (MIT vs Gemma). See the full comparison above for benchmark-by-benchmark results.
Phi 4 is developed by Microsoft and Gemma 3 12B is developed by Google.