Model Comparison

Gemma 3n E4B Instructed vs Qwen3 VL 8B ThinkingWhich is better in 2026?

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks. Qwen3 VL 8B Thinking is 38.0x cheaper per token.

Verdict: Gemma 3n E4B Instructed vs Qwen3 VL 8B Thinking — which is better?

Gemma 3n E4B Instructed (by Google) and Qwen3 VL 8B Thinking (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Gemma 3n E4B Instructed outperforms in 0 benchmarks, while Qwen3 VL 8B Thinking is better at 6 benchmarks (AIME 2025, GPQA, Include, MMLU, MMLU-Pro, MMLU-ProX). Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.

On price, Qwen3 VL 8B Thinking is roughly 38.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Qwen3 VL 8B Thinking also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Choose Gemma 3n E4B Instructed if…

  • you want predictable pricing at $20.00/M input and $40.00/M output

Choose Qwen3 VL 8B Thinking if…

  • you want the strongest raw capability — it leads on 6 of 6 shared benchmarks
  • cost matters — it's about 38.0x cheaper per token
  • you process long inputs — it offers a 262,144 token context window
  • you want the most recent training data — it shipped Sep 2025
  • you need open weights you can self-host or fine-tune
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

Gemma 3n E4B Instructed outperforms in 0 benchmarks, while Qwen3 VL 8B Thinking is better at 6 benchmarks (AIME 2025, GPQA, Include, MMLU, MMLU-Pro, MMLU-ProX).

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks.

Sun Jun 07 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 8B Thinking costs less

For input processing, Gemma 3n E4B Instructed ($20.00/1M tokens) is 111.1x more expensive than Qwen3 VL 8B Thinking ($0.18/1M tokens).

For output processing, Gemma 3n E4B Instructed ($40.00/1M tokens) is 19.1x more expensive than Qwen3 VL 8B Thinking ($2.09/1M tokens).

In conclusion, Gemma 3n E4B Instructed is more expensive than Qwen3 VL 8B Thinking.*

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

Lowest available price from all providers
Sun Jun 07 2026 • llm-stats.com
Google
Gemma 3n E4B Instructed
Input tokens$20.00
Output tokens$40.00
Best providerTogether
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Thinking
Input tokens$0.18
Output tokens$2.09
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

1.0B diff

Qwen3 VL 8B Thinking has 1.0B more parameters than Gemma 3n E4B Instructed, making it 12.5% larger.

Google
Gemma 3n E4B Instructed
8.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Thinking
9.0Bparameters
8.0B
Gemma 3n E4B Instructed
9.0B
Qwen3 VL 8B Thinking

Context Window

Maximum input and output token capacity

Qwen3 VL 8B Thinking accepts 262,144 input tokens compared to Gemma 3n E4B Instructed's 32,000 tokens. Qwen3 VL 8B Thinking can generate longer responses up to 262,144 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 VL 8B Thinking
Input262,144 tokens
Output262,144 tokens
Sun Jun 07 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 3n E4B Instructed and Qwen3 VL 8B Thinking support multimodal inputs.

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

Gemma 3n E4B Instructed

Text
Images
Audio
Video

Qwen3 VL 8B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E4B Instructed is licensed under a proprietary license, while Qwen3 VL 8B Thinking 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 VL 8B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 3n E4B Instructed was released on 2025-06-26, while Qwen3 VL 8B Thinking was released on 2025-09-22.

Qwen3 VL 8B Thinking is 3 months newer than Gemma 3n E4B Instructed.

Gemma 3n E4B Instructed

Jun 26, 2025

11 months ago

Qwen3 VL 8B Thinking

Sep 22, 2025

8 months ago

2mo newer

Knowledge Cutoff

When training data ends

Gemma 3n E4B Instructed has a documented knowledge cutoff of 2024-06-01, while Qwen3 VL 8B Thinking'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 VL 8B Thinking's cutoff date.

Gemma 3n E4B Instructed

Jun 2024

Qwen3 VL 8B Thinking

—

Provider Availability

Gemma 3n E4B Instructed is available from Together. Qwen3 VL 8B Thinking is available from DeepInfra.

Gemma 3n E4B Instructed

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

Qwen3 VL 8B Thinking

deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $2.09/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google

No standout differentiators in the data we have for this pair.

Alibaba Cloud / Qwen Team

Qwen3 VL 8B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher AIME 2025 score (80.3% vs 11.6%)
Higher GPQA score (69.9% vs 23.7%)
Higher Include score (69.5% vs 57.2%)
Higher MMLU score (85.2% vs 64.9%)
Higher MMLU-Pro score (77.3% vs 50.6%)
Higher MMLU-ProX score (70.7% vs 19.9%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3n E4B Instructed
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Thinking

FAQ

Common questions about Gemma 3n E4B Instructed vs Qwen3 VL 8B Thinking.

Which is better, Gemma 3n E4B Instructed or Qwen3 VL 8B Thinking?

Qwen3 VL 8B Thinking significantly outperforms across most benchmarks. Gemma 3n E4B Instructed is made by Google and Qwen3 VL 8B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemma 3n E4B Instructed compare to Qwen3 VL 8B Thinking in benchmarks?

Gemma 3n E4B Instructed scores HumanEval: 75.0%, MGSM: 67.0%, MMLU: 64.9%, Global-MMLU-Lite: 64.5%, MBPP: 63.6%. Qwen3 VL 8B Thinking scores DocVQAtest: 95.3%, ScreenSpot: 93.6%, MMLU-Redux: 88.8%, MMBench-V1.1: 87.5%, InfoVQAtest: 86.0%.

Is Gemma 3n E4B Instructed cheaper than Qwen3 VL 8B Thinking?

Qwen3 VL 8B Thinking is 111.1x cheaper for input tokens. Gemma 3n E4B Instructed costs $20.00/M input and $40.00/M output via together. Qwen3 VL 8B Thinking costs $0.18/M input and $2.09/M output via deepinfra.

What are the context window sizes for Gemma 3n E4B Instructed and Qwen3 VL 8B Thinking?

Gemma 3n E4B Instructed supports 32K tokens and Qwen3 VL 8B Thinking supports 262K 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 E4B Instructed and Qwen3 VL 8B Thinking?

Key differences include context window (32K vs 262K), input pricing ($20.00 vs $0.18/M), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 3n E4B Instructed and Qwen3 VL 8B Thinking?

Gemma 3n E4B Instructed is developed by Google and Qwen3 VL 8B Thinking is developed by Alibaba Cloud / Qwen Team.

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