Gemma 3 12B vs Phi-4-multimodal-instruct
Gemma 3 12B and Phi-4-multimodal-instruct are closely matched at 5.7 and 3.0 on the LLM Stats Score. Gemma 3 12B and Phi-4-multimodal-instruct cost the same.
Google · Microsoft · Updated for 2026
Which is better?
Gemma 3 12B and Phi-4-multimodal-instruct are closely matched on the overall LLM Stats Score at 5.7 and 3.0.
In the 5 individual benchmarks reported for both models, Phi-4-multimodal-instruct wins 4; this is a narrower head-to-head signal than the composite indexes.
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 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-multimodal-instruct
- you value its reported benchmark strengths — it wins 4 of 5 exact shared results
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 · 15 for Phi-4-multimodal-instruct
Gemma 3 12B outperforms in 1 benchmarks (AI2D), while Phi-4-multimodal-instruct is better at 4 benchmarks (ChartQA, DocVQA, InfoVQA, TextVQA).
Phi-4-multimodal-instruct significantly outperforms across most 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) costs the same as Phi-4-multimodal-instruct ($0.05/1M tokens).
For output processing, Gemma 3 12B ($0.10/1M tokens) costs the same as Phi-4-multimodal-instruct ($0.10/1M tokens).
In conclusion, Gemma 3 12B and Phi-4-multimodal-instruct cost the same.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Gemma 3 12B has 6.4B more parameters than Phi-4-multimodal-instruct, making it 114.3% larger.
Context Window
Maximum input and output token capacity
Gemma 3 12B accepts 131,072 input tokens compared to Phi-4-multimodal-instruct's 128,000 tokens. Gemma 3 12B can generate longer responses up to 131,072 tokens, while Phi-4-multimodal-instruct is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemma 3 12B and Phi-4-multimodal-instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 3 12B
Phi-4-multimodal-instruct
License
Usage and distribution terms
Gemma 3 12B is licensed under Gemma, while Phi-4-multimodal-instruct 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-multimodal-instruct was released on 2025-02-01.
Gemma 3 12B is 1 month newer than Phi-4-multimodal-instruct.
Mar 12, 2025
1.5 years ago
1mo newerFeb 1, 2025
1.6 years ago
Knowledge Cutoff
When training data ends
Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while Gemma 3 12B's cutoff date is not specified.
We can confirm Phi-4-multimodal-instruct'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-multimodal-instruct is available from DeepInfra.
Gemma 3 12B
Phi-4-multimodal-instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 3 12B and Phi-4-multimodal-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3 12B vs Phi-4-multimodal-instruct.