Model Comparison

Gemma 3n E4B Instructed vs Qwen3-235B-A22B-Instruct-2507

Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks. Qwen3-235B-A22B-Instruct-2507 is 80.0x cheaper per token.

Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

Gemma 3n E4B Instructed outperforms in 0 benchmarks, while Qwen3-235B-A22B-Instruct-2507 is better at 5 benchmarks (AIME 2025, GPQA, Include, MMLU-Pro, MMLU-ProX).

Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks.

Wed Apr 29 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3-235B-A22B-Instruct-2507 costs less

For input processing, Gemma 3n E4B Instructed ($20.00/1M tokens) is 133.3x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.15/1M tokens).

For output processing, Gemma 3n E4B Instructed ($40.00/1M tokens) is 50.0x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.80/1M tokens).

In conclusion, Gemma 3n E4B Instructed is more expensive than Qwen3-235B-A22B-Instruct-2507.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Wed Apr 29 2026 • llm-stats.com
Google
Gemma 3n E4B Instructed
Input tokens$20.00
Output tokens$40.00
Best providerTogether
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input tokens$0.15
Output tokens$0.80
Best providerFireworks
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

227.0B diff

Qwen3-235B-A22B-Instruct-2507 has 227.0B more parameters than Gemma 3n E4B Instructed, making it 2837.5% larger.

Google
Gemma 3n E4B Instructed
8.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
235.0Bparameters
8.0B
Gemma 3n E4B Instructed
235.0B
Qwen3-235B-A22B-Instruct-2507

Context Window

Maximum input and output token capacity

Qwen3-235B-A22B-Instruct-2507 accepts 262,144 input tokens compared to Gemma 3n E4B Instructed's 32,000 tokens. Qwen3-235B-A22B-Instruct-2507 can generate longer responses up to 131,072 tokens, while Gemma 3n E4B Instructed is limited to 32,000 tokens.

Google
Gemma 3n E4B Instructed
Input32,000 tokens
Output32,000 tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input262,144 tokens
Output131,072 tokens
Wed Apr 29 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E4B Instructed supports multimodal inputs, whereas Qwen3-235B-A22B-Instruct-2507 does not.

Gemma 3n E4B Instructed can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 3n E4B Instructed

Text
Images
Audio
Video

Qwen3-235B-A22B-Instruct-2507

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E4B Instructed is licensed under a proprietary license, while Qwen3-235B-A22B-Instruct-2507 uses Apache 2.0.

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

Gemma 3n E4B Instructed

Proprietary

Closed source

Qwen3-235B-A22B-Instruct-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 3n E4B Instructed was released on 2025-06-26, while Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.

Qwen3-235B-A22B-Instruct-2507 is 1 month newer than Gemma 3n E4B Instructed.

Gemma 3n E4B Instructed

Jun 26, 2025

10 months ago

Qwen3-235B-A22B-Instruct-2507

Jul 22, 2025

9 months ago

3w newer

Knowledge Cutoff

When training data ends

Gemma 3n E4B Instructed has a documented knowledge cutoff of 2024-06-01, while Qwen3-235B-A22B-Instruct-2507's cutoff date is not specified.

We can confirm Gemma 3n E4B Instructed's training data extends to 2024-06-01, but cannot make a direct comparison without Qwen3-235B-A22B-Instruct-2507's cutoff date.

Gemma 3n E4B Instructed

Jun 2024

Qwen3-235B-A22B-Instruct-2507

Provider Availability

Gemma 3n E4B Instructed is available from Together. Qwen3-235B-A22B-Instruct-2507 is available from Fireworks, Novita.

Gemma 3n E4B Instructed

together logo
Together
Input Price:Input: $20.00/1MOutput Price:Output: $40.00/1M

Qwen3-235B-A22B-Instruct-2507

fireworks logo
Fireworks
Input Price:Input: $0.15/1MOutput Price:Output: $0.80/1M
novita logo
Novita
Input Price:Input: $0.15/1MOutput Price:Output: $0.80/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Supports multimodal inputs
Larger context window (262,144 tokens)
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher AIME 2025 score (70.3% vs 11.6%)
Higher GPQA score (77.5% vs 23.7%)
Higher Include score (79.5% vs 57.2%)
Higher MMLU-Pro score (83.0% vs 50.6%)
Higher MMLU-ProX score (79.4% vs 19.9%)

Detailed Comparison

FAQ

Common questions about Gemma 3n E4B Instructed vs Qwen3-235B-A22B-Instruct-2507

Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks. Gemma 3n E4B Instructed is made by Google and Qwen3-235B-A22B-Instruct-2507 is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemma 3n E4B Instructed scores HumanEval: 75.0%, MGSM: 67.0%, MMLU: 64.9%, Global-MMLU-Lite: 64.5%, MBPP: 63.6%. Qwen3-235B-A22B-Instruct-2507 scores ZebraLogic: 95.0%, MMLU-Redux: 93.1%, IFEval: 88.7%, MultiPL-E: 87.9%, Creative Writing v3: 87.5%.
Qwen3-235B-A22B-Instruct-2507 is 133.3x cheaper for input tokens. Gemma 3n E4B Instructed costs $20.00/M input and $40.00/M output via together. Qwen3-235B-A22B-Instruct-2507 costs $0.15/M input and $0.80/M output via fireworks.
Gemma 3n E4B Instructed supports 32K tokens and Qwen3-235B-A22B-Instruct-2507 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (32K vs 262K), input pricing ($20.00 vs $0.15/M), multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Gemma 3n E4B Instructed is developed by Google and Qwen3-235B-A22B-Instruct-2507 is developed by Alibaba Cloud / Qwen Team.