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Gemma 4 E2B vs Llama 3.2 90B Instruct

Gemma 4 E2B and Llama 3.2 90B Instruct are closely matched at 6.7 and 5.2 on the LLM Stats Score.

Google · Meta · Updated for 2026

Which is better?

Gemma 4 E2B and Llama 3.2 90B Instruct are closely matched on the overall LLM Stats Score at 6.7 and 5.2.

In the 2 individual benchmarks reported for both models, Llama 3.2 90B Instruct wins 2; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemma 4 E2B

  • you want the most recent training data — it shipped Apr 2026

Choose Llama 3.2 90B Instruct

  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results

At a glance

The differences that matter most.

Gemma 4 E2B
Google
Llama 3.2 90B Instruct
Meta
Core performance indexes
LLM Stats Score
6.7
#294
5.2
#300
Reasoning
5.6
#295
6.7
#288
Cost, coverage & limits
Benchmark wins
0 of 2
2 of 2
Input price
— / M
$0.35 / M
Output price
— / M
$0.40 / M
Context window
—
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Gemma 4 E2B
Llama 3.2 90B Instruct
Math
5.7#270
11.6#238
Vision
0.7#179
2.8#167
Multimodal
2.9#146
5.6#138
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for Gemma 4 E2B · 13 for Llama 3.2 90B Instruct

2 shared

Gemma 4 E2B outperforms in 0 benchmarks, while Llama 3.2 90B Instruct is better at 2 benchmarks (GPQA, MMMU-Pro).

Llama 3.2 90B Instruct significantly outperforms across most benchmarks.

Tue Sep 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

84.9B diff

Llama 3.2 90B Instruct has 84.9B more parameters than Gemma 4 E2B, making it 1664.7% larger.

Google
Gemma 4 E2B
5.1Bparameters
Meta
Llama 3.2 90B Instruct
90.0Bparameters
5.1B
Gemma 4 E2B
90.0B
Llama 3.2 90B Instruct

Context Window

Maximum input and output token capacity

Only Llama 3.2 90B Instruct specifies input context (128,000 tokens). Only Llama 3.2 90B Instruct specifies output context (128,000 tokens).

Google
Gemma 4 E2B
Input- tokens
Output- tokens
Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Tue Sep 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemma 4 E2B and Llama 3.2 90B Instruct support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemma 4 E2B

Text
Images
Audio
Video

Llama 3.2 90B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 4 E2B is licensed under Apache 2.0, while Llama 3.2 90B Instruct uses Llama 3.2.

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

Gemma 4 E2B

Apache 2.0

Open weights

Llama 3.2 90B Instruct

Llama 3.2

Open weights

Release Timeline

When each model was launched

Gemma 4 E2B was released on 2026-04-02, while Llama 3.2 90B Instruct was released on 2024-09-25.

Gemma 4 E2B is 18 months newer than Llama 3.2 90B Instruct.

Gemma 4 E2B

Apr 2, 2026

5 months ago

1.5yr newer
Llama 3.2 90B Instruct

Sep 25, 2024

2.0 years ago

Knowledge Cutoff

When training data ends

Gemma 4 E2B has a documented knowledge cutoff of 2025-01-01, while Llama 3.2 90B Instruct's cutoff date is not specified.

We can confirm Gemma 4 E2B's training data extends to 2025-01-01, but cannot make a direct comparison without Llama 3.2 90B Instruct's cutoff date.

Gemma 4 E2B

Jan 2025

Llama 3.2 90B Instruct

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemma 4 E2B and Llama 3.2 90B Instruct side-by-side, then vote on the output you prefer.

Gemma 4 E2B
✓ Preferred
Llama 3.2 90B Instruct
Open in Playground

FAQ

Common questions about Gemma 4 E2B vs Llama 3.2 90B Instruct.

Which is better, Gemma 4 E2B or Llama 3.2 90B Instruct?

Gemma 4 E2B and Llama 3.2 90B Instruct are closely matched on the LLM Stats Score at 6.7 and 5.2. Gemma 4 E2B is made by Google and Llama 3.2 90B Instruct is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemma 4 E2B compare to Llama 3.2 90B Instruct in benchmarks?

Gemma 4 E2B scores MMMLU: 67.4%, MMLU-Pro: 60.0%, MathVision: 52.4%, MMMU-Pro: 44.2%, LiveCodeBench v6: 44.0%. Llama 3.2 90B Instruct scores AI2D: 92.3%, DocVQA: 90.1%, MGSM: 86.9%, MMLU: 86.0%, ChartQA: 85.5%.

What are the context window sizes for Gemma 4 E2B and Llama 3.2 90B Instruct?

Gemma 4 E2B supports an unknown number of tokens and Llama 3.2 90B 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 4 E2B and Llama 3.2 90B Instruct?

Key differences include LLM Stats Score (6.7 vs 5.2), licensing (Apache 2.0 vs Llama 3.2). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 4 E2B and Llama 3.2 90B Instruct?

Gemma 4 E2B is developed by Google and Llama 3.2 90B Instruct is developed by Meta.

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