Model Comparison
Gemma 3n E4B Instructed vs Kimi K2 0905Which is better in 2026?
Kimi K2 0905 significantly outperforms across most benchmarks. Kimi K2 0905 is 23.3x cheaper per token.
Verdict: Gemma 3n E4B Instructed vs Kimi K2 0905 — which is better?
Gemma 3n E4B Instructed (by Google) and Kimi K2 0905 (by Moonshot AI) 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 Kimi K2 0905 is better at 4 benchmarks (GPQA, HumanEval, MMLU, MMLU-Pro). Kimi K2 0905 significantly outperforms across most benchmarks.
On price, Kimi K2 0905 is roughly 23.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K2 0905 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 Kimi K2 0905 if…
- you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
- cost matters — it's about 23.3x 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
Performance Benchmarks
Comparative analysis across standard metrics
Gemma 3n E4B Instructed outperforms in 0 benchmarks, while Kimi K2 0905 is better at 4 benchmarks (GPQA, HumanEval, MMLU, MMLU-Pro).
Kimi K2 0905 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 3n E4B Instructed ($20.00/1M tokens) is 33.3x more expensive than Kimi K2 0905 ($0.60/1M tokens).
For output processing, Gemma 3n E4B Instructed ($40.00/1M tokens) is 16.0x more expensive than Kimi K2 0905 ($2.50/1M tokens).
In conclusion, Gemma 3n E4B Instructed is more expensive than Kimi K2 0905.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2 0905 has 992.0B more parameters than Gemma 3n E4B Instructed, making it 12400.0% larger.
Context Window
Maximum input and output token capacity
Kimi K2 0905 accepts 262,144 input tokens compared to Gemma 3n E4B Instructed's 32,000 tokens. Kimi K2 0905 can generate longer responses up to 262,144 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 Kimi K2 0905 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
Kimi K2 0905
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
Gemma 3n E4B Instructed was released on 2025-06-26, while Kimi K2 0905 was released on 2025-09-05.
Kimi K2 0905 is 2 months newer than Gemma 3n E4B Instructed.
Jun 26, 2025
11 months ago
Sep 5, 2025
9 months ago
2mo newerKnowledge Cutoff
When training data ends
Gemma 3n E4B Instructed has a documented knowledge cutoff of 2024-06-01, while Kimi K2 0905'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 Kimi K2 0905's cutoff date.
Jun 2024
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Provider Availability
Gemma 3n E4B Instructed is available from Together. Kimi K2 0905 is available from Novita.
Gemma 3n E4B Instructed
Kimi K2 0905
Outputs Comparison
Key Takeaways
Kimi K2 0905
View detailsMoonshot AI
Detailed Comparison
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FAQ
Common questions about Gemma 3n E4B Instructed vs Kimi K2 0905.