Gemma 3 12B vs Phi 4
Gemma 3 12B and Phi 4 are closely matched at 5.6 and 5.4 on the LLM Stats Score. Gemma 3 12B is 1.2x cheaper per token.
Google · Microsoft · Updated for 2026
Which is better?
Gemma 3 12B and Phi 4 are closely matched on the overall LLM Stats Score at 5.6 and 5.4.
In the 6 individual benchmarks reported for both models, Gemma 3 12B wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Gemma 3 12B is roughly 1.2x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemma 3 12B
- you value its reported benchmark strengths — it wins 4 of 6 exact shared results
- cost matters — it's about 1.2x 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
- you want predictable pricing at $0.07/M input and $0.14/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
26 reported for Gemma 3 12B · 13 for Phi 4
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.
Human preference
Blind head-to-head votes and playground preference scores
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 ($0.15/1M tokens) is 1.1x more expensive 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 16,384 tokens. Gemma 3 12B can generate longer responses up to 131,072 tokens, while Phi 4 is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
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
1.5 years ago
3mo newerDec 12, 2024
1.8 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
Judge for yourself.
Run your own prompts against Gemma 3 12B and Phi 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3 12B vs Phi 4.