Model Comparison

Gemma 3n E2B vs Jamba 1.5 Large

Jamba 1.5 Large significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Gemma 3n E2B outperforms in 0 benchmarks, while Jamba 1.5 Large is better at 1 benchmark (ARC-C).

Jamba 1.5 Large significantly outperforms across most benchmarks.

Sat May 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

390.0B diff

Jamba 1.5 Large has 390.0B more parameters than Gemma 3n E2B, making it 4875.0% larger.

Google
Gemma 3n E2B
8.0Bparameters
AI21 Labs
Jamba 1.5 Large
398.0Bparameters
8.0B
Gemma 3n E2B
398.0B
Jamba 1.5 Large

Context Window

Maximum input and output token capacity

Only Jamba 1.5 Large specifies input context (256,000 tokens). Only Jamba 1.5 Large specifies output context (256,000 tokens).

Google
Gemma 3n E2B
Input- tokens
Output- tokens
AI21 Labs
Jamba 1.5 Large
Input256,000 tokens
Output256,000 tokens
Sat May 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E2B supports multimodal inputs, whereas Jamba 1.5 Large does not.

Gemma 3n E2B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 3n E2B

Text
Images
Audio
Video

Jamba 1.5 Large

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E2B is licensed under a proprietary license, while Jamba 1.5 Large uses Jamba Open Model License.

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

Gemma 3n E2B

Proprietary

Closed source

Jamba 1.5 Large

Jamba Open Model License

Open weights

Release Timeline

When each model was launched

Gemma 3n E2B was released on 2025-06-26, while Jamba 1.5 Large was released on 2024-08-22.

Gemma 3n E2B is 10 months newer than Jamba 1.5 Large.

Gemma 3n E2B

Jun 26, 2025

11 months ago

10mo newer
Jamba 1.5 Large

Aug 22, 2024

1.8 years ago

Knowledge Cutoff

When training data ends

Gemma 3n E2B has a knowledge cutoff of 2024-06-01, while Jamba 1.5 Large has a cutoff of 2024-03-05.

Gemma 3n E2B has more recent training data (up to 2024-06-01), making it potentially better informed about events through that date compared to Jamba 1.5 Large (2024-03-05).

Gemma 3n E2B

Jun 2024

3 mo newer
Jamba 1.5 Large

Mar 2024

Outputs Comparison

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Key Takeaways

Google
Supports multimodal inputs
AI21 Labs
Larger context window (256,000 tokens)
Has open weights
Higher ARC-C score (93.0% vs 51.7%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3n E2B
AI21 Labs
Jamba 1.5 Large

FAQ

Common questions about Gemma 3n E2B vs Jamba 1.5 Large.

Which is better, Gemma 3n E2B or Jamba 1.5 Large?

Jamba 1.5 Large significantly outperforms across most benchmarks. Gemma 3n E2B is made by Google and Jamba 1.5 Large is made by AI21 Labs. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemma 3n E2B compare to Jamba 1.5 Large in benchmarks?

Gemma 3n E2B scores PIQA: 78.9%, BoolQ: 76.4%, ARC-E: 75.8%, HellaSwag: 72.2%, Winogrande: 66.8%. Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%.

What are the context window sizes for Gemma 3n E2B and Jamba 1.5 Large?

Gemma 3n E2B supports an unknown number of tokens and Jamba 1.5 Large supports 256K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemma 3n E2B and Jamba 1.5 Large?

Key differences include multimodal support (yes vs no), licensing (Proprietary vs Jamba Open Model License). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 3n E2B and Jamba 1.5 Large?

Gemma 3n E2B is developed by Google and Jamba 1.5 Large is developed by AI21 Labs.