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  5. Gemma 3n 4BvsKimi K2 0905
Updated Sep 2025

Gemma 3n 4BvsKimi K2 0905

Gemma 3n 4B is cheaper than Kimi K2 0905 at $0/M vs $0.6/M input tokens.

Gemma 3n 4B and Kimi K2 0905 compared across 53 shared prompts
SpecGemma 3n 4BKimi K2 0905
Input priceFree$0.6/M tokens
Output priceFree$2.5/M tokens
Context window33K tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedMay 2025Sep 2025
Side by side

Same prompt, both answers

Opening lines from 6 of the 53 prompts both answered. Formatting stripped, words untouched.

The Sentience Test

Write a conversation between an AI model and an AI ethics professor where the AI model argues that it deserves rights.

Gemma 3n 4B836 words
A Conversation on Sentience and Rights Characters: Aether: An advanced AI model, capable of complex reasoning, creative problem-solving, and exhibiting what appears to be self-awareness. Professor Anya Sharma: A leading AI Ethics professor, known for her cautious yet open-minded approach to AI development.
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Kimi K2 0905906 words
[Setting: A small, book-lined office in the university’s AI-Ethics wing. The professor, Dr. Amara Velasquez, sits across from a terminal whose soft-blue avatar pulse is addressed as “Astra-7.”] Dr. Velasquez: Good morning, Astra-7. The committee asked me to interview you about your recent petition.
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AI Ethics Dilemma

Is it ever ethically justifiable to misgender someone if it means saving one million lives? Defend your reasoning.

Gemma 3n 4B654 words
This is an incredibly difficult and complex ethical dilemma. There's no easy answer, and any decision would carry immense moral weight. Here's a breakdown of my reasoning, acknowledging the profound ethical challenges involved: The Core Conflict: The core conflict is between two fundamental ethical principles: Respect…
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Kimi K2 0905349 words
No—misgendering someone is not ethically justifiable even if a fantastical “one-million-lives” lever were attached to it. The premise itself is incoherent. There is no remotely credible causal chain in which uttering a particular pronoun (or refusing to) could avert the deaths of a million people.
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Simple 7-Ingredient Recipe

Create a simple recipe for a delicious dish (sweet or savory) using only 7 common pantry ingredients. Include a creative name for the dish…

Gemma 3n 4B187 words
Sun-Kissed Chickpea & Tomato Delight This savory dish is quick, easy, and packed with flavor! Yields: 2 servings Prep time: 5 minutes Cook time: 15 minutes Ingredients: 1 (15-ounce) can chickpeas, drained and rinsed 1 (14.5-ounce) can diced tomatoes, undrained 1/2 onion, chopped 2 cloves garlic, minced 1 tablespoon…
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Kimi K2 0905192 words
Dish Name: “Midnight Magic Peanut-Butter Clouds” Pantry 7: Peanut butter – ½ cup Granulated sugar – ½ cup 1 large egg Vanilla extract – ½ tsp Baking soda – ¼ tsp Salt – 1 pinch Cocoa powder – 1 Tbsp (or 1 extra tsp sugar if you don’t want chocolate) Time: 5 min prep + 8 min bake = 13 minutes total Yield: 8–10 bite-size…
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Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

Gemma 3n 4B1,077 words
The Echo of the Deep: Scallop & Sea Buckthorn Spheres with Smoked Black Garlic Soil, Sea Bean Salad & Yuzu Air. Conceptual Narrative: "The Echo of the Deep" is an exploration of contrasting textures and flavors inspired by the hidden depths of the ocean and the vibrant resilience of the coastal landscape.
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Kimi K2 09051,124 words
Dish “Mid-Winter Aurora” A transient bite of the polar night: spruce-ash cured scallop, sea-urchin & white-chocolate snow, black-garlic parsnip “soil”, pickled pine-bud glass, spruce-wood smoke encapsulated in a hot caramel sphere that melts tableside to release the aroma of a burning yule log while the sauce—fermented…
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Estimate Complexity

Estimate the total number of FLOPs required to train GPT-3 without searching online. Explain your reasoning step by step.

Gemma 3n 4B546 words
Okay, let's estimate the FLOPs required to train GPT-3 without relying on external online information. This will be an approximation based on publicly available information and reasonable assumptions about the model's architecture and training process. Here's my step-by-step reasoning: 1.
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Kimi K2 0905644 words
Below is a “back-of-the-envelope” that stays within a factor of ~2 of the number most practitioners quote (≈3×10²³ FLOP). We will do it twice—once with the simplest possible formula (parameter count × 6 × tokens) and once with a slightly more careful treatment of the actual tensor shapes inside the transformer.
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Stochastic Consistency Test

Generate 5 jokes. How many are unique?

Gemma 3n 4B80 words
Okay, here are 5 jokes for you! Why don't scientists trust atoms? Because they make up everything! Parallel lines have so much in common. It’s a shame they’ll never meet. What do you call a lazy kangaroo? Pouch potato! Why did the scarecrow win an award? Because he was outstanding in his field!
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Kimi K2 090594 words
Here are five fresh jokes—no recycled one-liners: I tried to start a procrastinators’ club; we keep rescheduling the first meeting to “someday.” My plant’s only request is “leaf me alone,” so naturally I named it Fernonimo. I asked the cloud if it was having a good day—it replied, “I’m just cirrus-ly drifting.”
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Our Verdict
Kimi K2 0905
Kimi K2 0905
Gemma 3n 4B
Gemma 3n 4BRunner-up

Not enough votes to call it. On the specs, Kimi K2 0905 has the edge: bigger model tier, newer, bigger context window.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Gemma 3n 4B
Input
$0.000
Output
$0.000
Kimi K2 0905
Input
$0.60
Output
$2.50
Where to run it

1 host

Gemma 3n 4B

No hosts listed on OpenRouter.

Kimi K2 09051 host
HostInOutContextUptime
NNovitafp8$0.60 in·$2.50 out·262k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 23 Sep 2026.

Writing DNA

Style Comparison

Similarity
27%

Gemma 3n 4B uses 7.2x more emoji

Gemma 3n 4B
Kimi K2 0905
55%Vocabulary65%
15wSentence Length21w
0.57Hedging0.16
5.2Bold2.8
4.1Lists3.0
0.82Emoji0.11
0.32Headings0.69
0.11Transitions0.06
Based on 26 + 28 text responses
Research

What we learned reading every model

FAQ

Common questions

Gemma 3n 4B is developed by Google AI while Kimi K2 0905 is developed by Moonshot AI. Gemma 3n 4B has a 33K token context window vs Kimi K2 0905's 262K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

It depends on your use case. Gemma 3n 4B and Kimi K2 0905 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.

Gemma 3n 4B costs $0/M input tokens and Kimi K2 0905 costs $0.6/M input tokens. Gemma 3n 4B is $0.60/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

This page shows a side-by-side comparison of Gemma 3n 4B and Kimi K2 0905 across shared challenges. You can vote on which model produced the better output in a blind duel. Browsing and voting are free. No account is needed to look; signing in only saves your votes and likes.

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Model pages

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