Gemma 3 4B vs Phi-3.5-mini-instruct
Gemma 3 4B and Phi-3.5-mini-instruct are closely matched at -1.9 and -3.8 on the LLM Stats Score. Gemma 3 4B is 4.0x cheaper per token.
Google · Microsoft · Updated for 2026
Which is better?
Gemma 3 4B and Phi-3.5-mini-instruct are closely matched on the overall LLM Stats Score at -1.9 and -3.8.
In the 7 individual benchmarks reported for both models, Gemma 3 4B wins 5; this is a narrower head-to-head signal than the composite indexes.
On price, Gemma 3 4B is roughly 4.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemma 3 4B 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 4B
- you value its reported benchmark strengths — it wins 5 of 7 exact shared results
- cost matters — it's about 4.0x 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-3.5-mini-instruct
- you want predictable pricing at $0.10/M input and $0.10/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 4B · 31 for Phi-3.5-mini-instruct
Gemma 3 4B outperforms in 5 benchmarks (BIG-Bench Hard, GPQA, GSM8k, HumanEval, MATH), while Phi-3.5-mini-instruct is better at 2 benchmarks (MBPP, MMLU-Pro).
Gemma 3 4B 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 4B ($0.02/1M tokens) is 5.0x cheaper than Phi-3.5-mini-instruct ($0.10/1M tokens).
For output processing, Gemma 3 4B ($0.04/1M tokens) is 2.5x cheaper than Phi-3.5-mini-instruct ($0.10/1M tokens).
In conclusion, Phi-3.5-mini-instruct is more expensive than Gemma 3 4B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Gemma 3 4B has 0.2B more parameters than Phi-3.5-mini-instruct, making it 5.3% larger.
Context Window
Maximum input and output token capacity
Gemma 3 4B accepts 131,072 input tokens compared to Phi-3.5-mini-instruct's 128,000 tokens. Gemma 3 4B can generate longer responses up to 131,072 tokens, while Phi-3.5-mini-instruct is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Gemma 3 4B supports multimodal inputs, whereas Phi-3.5-mini-instruct does not.
Gemma 3 4B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemma 3 4B
Phi-3.5-mini-instruct
License
Usage and distribution terms
Gemma 3 4B is licensed under Gemma, while Phi-3.5-mini-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 4B was released on 2025-03-12, while Phi-3.5-mini-instruct was released on 2024-08-23.
Gemma 3 4B is 7 months newer than Phi-3.5-mini-instruct.
Mar 12, 2025
1.6 years ago
6mo newerAug 23, 2024
2.2 years ago
Knowledge Cutoff
When training data ends
Gemma 3 4B has a documented knowledge cutoff of 2024-08-01, while Phi-3.5-mini-instruct's cutoff date is not specified.
We can confirm Gemma 3 4B's training data extends to 2024-08-01, but cannot make a direct comparison without Phi-3.5-mini-instruct's cutoff date.
Aug 2024
—
Provider Availability
Gemma 3 4B is available from DeepInfra. Phi-3.5-mini-instruct is available from Azure.
Gemma 3 4B
Phi-3.5-mini-instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 3 4B and Phi-3.5-mini-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3 4B vs Phi-3.5-mini-instruct.