Model Comparison

Gemma 3 4B vs Phi-3.5-mini-instruct

Gemma 3 4B shows notably better performance in the majority of benchmarks. Gemma 3 4B is 4.0x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

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.

Thu May 14 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 3 4B costs less

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

Lowest available price from all providers

Thu May 14 2026 • llm-stats.com

Gemma 3 4B

Input tokens$0.02

Output tokens$0.04

Best providerDeepinfra

Phi-3.5-mini-instruct

Input tokens$0.10

Output tokens$0.10

Best providerAzure

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Model Size

Parameter count comparison

200.0M diff

Gemma 3 4B has 0.2B more parameters than Phi-3.5-mini-instruct, making it 5.3% larger.

Gemma 3 4B

4.0Bparameters

Phi-3.5-mini-instruct

3.8Bparameters

4.0B

Gemma 3 4B

3.8B

Phi-3.5-mini-instruct

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.

Gemma 3 4B

Input131,072 tokens

Output131,072 tokens

Phi-3.5-mini-instruct

Input128,000 tokens

Output128,000 tokens

Thu May 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

Text

Images

Audio

Video

Phi-3.5-mini-instruct

Text

Images

Audio

Video

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 3 4B

Gemma

Open weights

Phi-3.5-mini-instruct

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.

Gemma 3 4B

Mar 12, 2025

1.2 years ago

6mo newer

Phi-3.5-mini-instruct

Aug 23, 2024

1.7 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.

Gemma 3 4B

Aug 2024

Phi-3.5-mini-instruct

—

Provider Availability

Gemma 3 4B is available from DeepInfra. Phi-3.5-mini-instruct is available from Azure.

Gemma 3 4B

Deepinfra

Input Price:Input: $0.02/1MOutput Price:Output: $0.04/1M

Phi-3.5-mini-instruct

Azure

Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Gemma 3 4B

View details

Google

Larger context window (131,072 tokens)

Supports multimodal inputs

Less expensive input tokens

Less expensive output tokens

Higher BIG-Bench Hard score (72.2% vs 69.0%)

Higher GPQA score (30.8% vs 30.4%)

Higher GSM8k score (89.2% vs 86.2%)

Higher HumanEval score (71.3% vs 62.8%)

Higher MATH score (75.6% vs 48.5%)

Phi-3.5-mini-instruct

View details

Microsoft

Higher MBPP score (69.6% vs 63.2%)

Higher MMLU-Pro score (47.4% vs 43.6%)

Detailed Comparison

AI Model Comparison Table
Feature	Gemma 3 4B	Phi-3.5-mini-instruct

FAQ

Common questions about Gemma 3 4B vs Phi-3.5-mini-instruct.

Which is better, Gemma 3 4B or Phi-3.5-mini-instruct?

Gemma 3 4B shows notably better performance in the majority of benchmarks. Gemma 3 4B is made by Google and Phi-3.5-mini-instruct is made by Microsoft. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemma 3 4B compare to Phi-3.5-mini-instruct in benchmarks?

Gemma 3 4B scores IFEval: 90.2%, GSM8k: 89.2%, DocVQA: 75.8%, MATH: 75.6%, AI2D: 74.8%. Phi-3.5-mini-instruct scores GSM8k: 86.2%, ARC-C: 84.6%, RULER: 84.1%, PIQA: 81.0%, OpenBookQA: 79.2%.

Is Gemma 3 4B cheaper than Phi-3.5-mini-instruct?

Gemma 3 4B is 5.0x cheaper for input tokens. Gemma 3 4B costs $0.02/M input and $0.04/M output via deepinfra. Phi-3.5-mini-instruct costs $0.10/M input and $0.10/M output via azure.

What are the context window sizes for Gemma 3 4B and Phi-3.5-mini-instruct?

Gemma 3 4B supports 131K tokens and Phi-3.5-mini-instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemma 3 4B and Phi-3.5-mini-instruct?

Key differences include context window (131K vs 128K), input pricing ($0.02 vs $0.10/M), multimodal support (yes vs no), licensing (Gemma vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 3 4B and Phi-3.5-mini-instruct?

Gemma 3 4B is developed by Google and Phi-3.5-mini-instruct is developed by Microsoft.