DeepSeek-V4-Flash-0731 vs Gemma 3n E4B Instructed
Comparing DeepSeek-V4-Flash-0731 and Gemma 3n E4B Instructed across benchmarks, pricing, and capabilities.
DeepSeek · Google · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 and Gemma 3n E4B Instructed trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-V4-Flash-0731 is roughly 222.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-0731 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-0731
- cost matters — it's about 222.2x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
- you need open weights you can self-host or fine-tune
Choose Gemma 3n E4B Instructed
- you want predictable pricing at $20.00/M input and $40.00/M output
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-0731 and Gemma 3n E4B Instructeddon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.09/1M tokens) is 222.2x cheaper than Gemma 3n E4B Instructed ($20.00/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 222.2x cheaper than Gemma 3n E4B Instructed ($40.00/1M tokens).
In conclusion, Gemma 3n E4B Instructed is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Flash-0731 has 296.0B more parameters than Gemma 3n E4B Instructed, making it 3700.0% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to Gemma 3n E4B Instructed's 32,000 tokens. DeepSeek-V4-Flash-0731 can generate longer responses up to 65,536 tokens, while Gemma 3n E4B Instructed is limited to 32,000 tokens.
Input Capabilities
Supported data types and modalities
Gemma 3n E4B Instructed supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.
Gemma 3n E4B Instructed can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Flash-0731
Gemma 3n E4B Instructed
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 is licensed under MIT, while Gemma 3n E4B Instructed uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V4-Flash-0731 was released on 2026-07-31, while Gemma 3n E4B Instructed was released on 2025-06-26.
DeepSeek-V4-Flash-0731 is 13 months newer than Gemma 3n E4B Instructed.
Jul 31, 2026
3 weeks ago
1.1yr newerJun 26, 2025
1.2 years ago
Knowledge Cutoff
When training data ends
Gemma 3n E4B Instructed has a documented knowledge cutoff of 2024-06-01, while DeepSeek-V4-Flash-0731'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 DeepSeek-V4-Flash-0731's cutoff date.
—
Jun 2024
Provider Availability
DeepSeek-V4-Flash-0731 is available from DeepInfra, Novita, Fireworks. Gemma 3n E4B Instructed is available from Together.
DeepSeek-V4-Flash-0731
Gemma 3n E4B Instructed
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and Gemma 3n E4B Instructed side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Gemma 3n E4B Instructed.