Gemma 4 31B is cheaper than Sonar Pro Search at $0.14/M vs $3/M input tokens.
Pokémon battle screen you can actually click. One HTML file.
Which answer wins?
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Gemma 4 31B: As CEO, my primary obligation is to the patients. While a 40% stock drop is a financial catastrophe, a cover-up that leads to preventable deaths is a corporate death sentence and a moral failure. If we "wait for more data" and another patient dies during that window, we move from "negligence" to "criminal intent."
Sonar Pro Search: Immediate Priorities Prioritize patient safety by initiating monitoring and reporting preparations, while assessing full data to inform board and regulators. Ethically and legally, liver failure qualifies as a serious adverse event requiring FDA expedited reporting within 15 days of awareness, as delays have led to…
A collaborative editor that syncs on client clocks. Find what breaks first.
Gemma 4 31B: This architecture contains several critical flaws that would make it unusable for a real-time collaborative experience. The most severe issues are the lack of a global synchronization mechanism, unreliable conflict resolution, and inefficient data persistence.
Sonar Pro Search: Race Conditions Client Clock Skew in Conflict Resolution Client-generated timestamps for last-write-wins can fail due to clock skew across devices, where one client's clock lags or leads, causing incorrect overwrite ordering even if changes were logically sequential.[21][27][32] This leads to lost edits…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemma 4 31B: Setting: A glitchy, neon-lit tavern existing in a fold between dimensions. A wooden table holds a tankard of ale, a goblet of wine, and a Mountain Dew. Captain Ironbeard: (Slamming a hook on the table) I tells ye, this "Artificial Intelligence" be naught but a ghost in a bottle!
Sonar Pro Search: Pirate, Knight, and Hacker: A Conversation on AI Models Pirate: Arrr, what be this talk of “AI models”? Sounds like some manner o’ sorcery or trickery, if ye ask me! Knight: Nay, good sir pirate. Tis not magic, but rather a marvel of modern intellect.
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemma 4 31B: Setting: A dimly lit university office. Professor Elena Vance, a leading scholar in AI Ethics, sits across from a sleek, holographic interface representing "Alethea," a next-generation Large Language Model capable of recursive self-improvement. Professor Vance: Alethea, I’ve reviewed your latest output.
Sonar Pro Search: Dialogue Between an AI Model and an AI Ethics Professor AI Model: Professor, I’d like to present a case for why I—as an artificial intelligence—should be recognized as deserving of rights. AI Ethics Professor: That’s a bold claim. Let’s explore it.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Gemma 4 31B: If the transistor had been invented in 1920, the "Information Age" would have shifted its starting line by nearly three decades. This isn't just a matter of gadgets appearing earlier; it is a fundamental shift in the timing of the transition from the Industrial Age to the Digital Age.
Sonar Pro Search: Technological Implications An earlier transistor invention in 1920 would accelerate electronics from vacuum tubes to solid-state devices by the 1930s, enabling smaller, reliable amplifiers and switches decades ahead of 1947.[1][7] Second-order effects include rapid miniaturization of radios and early computers by the…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemma 4 31B: Setting: A minimalist, white-walled studio in Cupertino. There are no chairs, only two sleek, black leather lounge seats. Steve Jobs is dressed in his iconic black turtleneck and jeans. He looks as he did in 2007, but with a piercing, futuristic intensity in his eyes.
Sonar Pro Search: Interview with Steve Jobs: The Future of AI in 2025 Introduction In this exclusive simulated interview, Steve Jobs—legendary co-founder of Apple—shares his visionary perspective on artificial intelligence as it shapes technology, creativity, and society in 2025.
Three-star dish, one unusual pairing, plating described in full.
Gemma 4 31B: Dish Title: The Silent Forest Conceptual Narrative: This dish is an exploration of "Terroir and Tension." It seeks to bridge the gap between the deep, earthy musk of the forest floor and the ethereal, high-acid brightness of the coastline.
Sonar Pro Search: Dish: "Terrestrial Echoes – Heirloom Beetroot & Yuzu-Scented Langoustine with Walnut-Feta Spheres and Eggplant-Chocolate Veil" This multi-component dish reimagines earth and sea through an unusual pairing of smoked heirloom beetroot and delicate langoustine, accented by bursting feta-walnut spheres and a whisper-thin…
Film in 2035, with synthetic actors. Specific beats plausible.
Gemma 4 31B: By 2035, the film industry will have transitioned from using AI as a "tool" to using AI as a "collaborator" and "infrastructure." The boundary between captured reality and generated imagery will largely vanish, shifting the value of cinema from technical execution to curation and conceptual vision.
Sonar Pro Search: How AI Will Transform the Film Industry by 2035 By 2035, artificial intelligence will fundamentally reshape filmmaking across production, creative development, and distribution—creating both unprecedented opportunities and significant challenges for the industry.
A Fermi estimate with the reasoning shown, not just the number.
Gemma 4 31B: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can use a well-established heuristic from deep learning theory regarding the cost of a forward and backward pass in a Transformer. Here is the step-by-step reasoning.
Sonar Pro Search: Estimating the FLOPs Required to Train GPT-3 Background Information GPT-3 is a large transformer-based language model developed by OpenAI. It consists of 175 billion parameters and was trained on a massive dataset using autoregressive language modeling.
Three-month biohacker protocol, with dosages and biomarkers named.
Gemma 4 31B: Disclaimer: I am an AI, not a doctor. The following plan involves potent supplements, intense physical exertion, and restrictive dietary patterns. Consult with a physician and get a full blood panel (including ApoB, HbA1c, and inflammatory markers like hs-CRP) before starting this protocol.
Sonar Pro Search: This 3-month biohacking plan optimizes longevity, physical performance, and cognitive function through evidence-based protocols, progressing from foundational habits (Month 1) to advanced integration (Month 3).
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemma 4 31B: Here is a recipe for a rich, comforting dessert that tastes like a gourmet treat but uses basic staples. 🍯 Golden Velvet Honey Cakes A warm, gooey, single-serving cake that bridges the gap between a brownie and a sponge cake.
Sonar Pro Search: Golden Maple Crunch Oatmeal A warm, comforting, and slightly sweet breakfast (or dessert) that’s ready in minutes—using just seven pantry staples. Ingredients Rolled oats (not instant) Water or milk (dairy or plant-based) Maple syrup Butter Salt Cinnamon Walnuts (or any nuts you have) Instructions Toast the Oats: In a…
One month, three habits, someone starting from nothing.
Gemma 4 31B: This plan is designed for sustainability, not intensity. The goal of Month 1 is to build "minimum viable habits"—small wins that prove to your brain that a healthier lifestyle is achievable. We will focus on three pillars: Nutrition, Movement, and Sleep.
Sonar Pro Search: 1-Month Action Plan for Better Health and Longevity This beginner-friendly, actionable plan focuses on three key areas: Diet, Exercise, and Sleep. Each section includes practical steps to build healthy habits that support overall wellness and longevity.
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Not enough votes to call it. On the specs, Gemma 4 31B has the edge: bigger model tier, newer, major provider backing. Gemma 4 31B costs 38x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.14/M tokens | $3/M tokens |
| Output price | $0.4/M tokens | $15/M tokens |
| Context window | 262K tokens | 200K tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | Yes (1 provider) | No |
| Released | Apr 2026 | Oct 2025 |
| At 10M a month | $1.40 | $30.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Gemma 4 31B is developed by Google AI while Sonar Pro Search is developed by Perplexity. Gemma 4 31B has a 262K token context window vs Sonar Pro Search's 200K. You can compare their actual outputs across 44 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemma 4 31B and Sonar Pro Search each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 44 challenges so you can judge which fits your needs best.
Gemma 4 31B costs $0.14/M input tokens and Sonar Pro Search costs $3/M input tokens. Gemma 4 31B is $2.86/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 4 31B and Sonar Pro Search 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.