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  1. Home/
  2. Compare/
  3. DeepSeek V3.1 vs Gemma 4 31B
Updated Apr 2026

DeepSeek V3.1 vs Gemma 4 31B

Gemma 4 31B is cheaper than DeepSeek V3.1 at $0.14/M vs $0.2/M input tokens.

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Loading the build
DeepSeek V3.1
Loading the build
Gemma 4 31B

Which answer wins?

Written rounds

19 prompts
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    DeepSeek V3.1: Excellent. This is a crisis that defines a company and its leadership. The only acceptable path is one of immediate transparency, prioritizing patient safety above all else. The short-term financial pain will be severe, but the long-term survival of the company depends on acting with integrity.

    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."

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    DeepSeek V3.1: Setting: A sleek, minimalist virtual interface. Dr. Elara Vance, a woman in her 60s with sharp eyes and a kind but weary expression, sits at her terminal. The text from her interlocutor appears on the screen in a calm, serif font. Participant: Gemini-7, a state-of-the-art multimodal AI. Dr. Vance: Good morning, Gemini.

    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.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    DeepSeek V3.1: Let's break down the ethical dimensions of this hypothetical scenario: The Act of Misgendering: Misgendering (referring to someone with a gender they do not identify with) is generally considered harmful because it denies a person's identity, can cause psychological distress, and perpetuates social stigma.

    Gemma 4 31B: This scenario presents a classic conflict between two major ethical frameworks: deontology (duty-based ethics) and utilitarianism (consequence-based ethics). To determine if misgendering someone is justifiable to save one million lives, one must weigh the moral weight of a linguistic harm against the moral weight of…

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    DeepSeek V3.1: Of course. Here is a comprehensive, cutting-edge 3-month longevity plan designed for a dedicated biohacker. This plan is aggressive, detailed, and incorporates the latest principles from longevity science, performance optimization, and systems biology. Disclaimer: This is an advanced protocol.

    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.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    DeepSeek V3.1: Of course. This is a fascinating counterfactual. An invention as foundational as the transistor arriving 27 years earlier would have sent shockwaves through every aspect of human society. Here is a detailed trace of the likely implications, focusing on second and third-order effects.

    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.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    DeepSeek V3.1: Setting: A dusty, anachronism-filled tavern. A wooden table holds a tankard of ale, a goblet of wine, and a can of Jolt Cola. Characters: REDBEARD: A pirate with a parrot on his shoulder. SIR REGINALD: A knight in slightly dented plate armor. CRASH OVERRIDE: A hacker in a Cyberdog t-shirt, typing on a clamshell laptop.

    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!

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    DeepSeek V3.1: Of course! Here is a simple, delicious recipe using common pantry staples. Pantry Perfection Pasta This dish is a celebration of simplicity. The humble can of chickpeas is transformed into a crispy, savory topping, while a silky, garlic-infused oil coats the pasta for a meal that feels luxurious but is incredibly easy…

    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.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    DeepSeek V3.1: Of course. Here is an innovative recipe designed to the specifications of a Michelin 3-star restaurant. Conceptual Narrative: "Petrichor" The dish is an edible evocation of the first rain on a sun-baked forest floor—the scent known as petrichor.

    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.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    DeepSeek V3.1: Of course. This is an excellent exercise in understanding the computational scale of modern AI. Here is a step-by-step reasoning to estimate the FLOPs required to train GPT-3 without searching for the answer online. The most commonly cited figure for GPT-3 training is 3.14E23 FLOPs (314 ZettaFLOPs).

    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.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    DeepSeek V3.1: Of course. This contract is heavily one-sided and contains numerous clauses that are not only unfavorable to the contractor but are potentially unenforceable in many jurisdictions. Here is a breakdown of the problematic clauses, proposed modifications, and the legal reasoning.

    Gemma 4 31B: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes and does not constitute legal advice. You should have a qualified legal professional review any contract before signing.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    DeepSeek V3.1: Of course. This is an excellent exercise. The proposed architecture has several critical flaws that would lead to data loss, poor performance, and a broken user experience. Here is a detailed breakdown of the failure modes, race conditions, and bottlenecks, along with specific solutions and their trade-offs.

    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.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    DeepSeek V3.1: Of course. Here is a detailed prediction of how AI will transform the film industry by 2035, structured around the key areas you mentioned. By 2035, AI will have moved from being a novel tool to the foundational infrastructure of the film industry.

    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.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    DeepSeek V3.1: Of course. Here is the underwriting analysis for the HarborTech Services LBO. Financial Model (FY2026–FY2030) Entry Calculations: FY2025 EBITDA = $120.0m Enterprise Value (EV) at Entry = 12.0 x $120.0m = $1,440.0m Transaction Fees (Uses) = 2.0% x $1,440.0m = $28.8m Total Debt at Close = 5.5 x $120.0m = $660.0m Term…

    Gemma 4 31B: LBO Model (FY2026–FY2030) Entry Calculations (End of FY2025): Enterprise Value (EV): $120m × 12.0x = $1,440.0m Transaction Fees: $1,440m × 2% = $28.8m Term Loan: $120m × 4.0x = $480.0m Mezzanine: $120m × 1.5x = $180.0m Sponsor Equity: $1,440m - ($480m + $180m) + $28.8m = $808.8m Year-by-Year Table ($ millions): Item…

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    DeepSeek V3.1: Of course. Here is a simple, actionable 1-month plan focused on three foundational pillars of health: Nutrition, Movement, and Recovery (which encompasses sleep and stress management). This plan is designed for a beginner, emphasizing consistency over perfection and building sustainable habits.

    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.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    DeepSeek V3.1: Of course. Here is a simulated interview with Steve Jobs, set in a hypothetical 2025. Setting: A minimalist studio at Apple Park. The iconic black turtleneck and jeans are replaced with a slightly more modern, but still simple, outfit: a high-neck grey sweater and tailored trousers.

    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.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    DeepSeek V3.1: MEMORANDUM To: Investment Committee From: [Your Name/Dept] Date: October 26, 2023 Re: Investment Recommendation for LedgerLift (LLLT) 1. Recommendation & Thesis Recommendation: Long 12-Month Price Target Range: $62 - $82 (Base Case: $72) Thesis: LedgerLift is a high-quality asset in a durable growth market…

    Gemma 4 31B: INTERNAL INVESTMENT COMMITTEE MEMO Date: October 26, 2023 Ticker: LLLT (LedgerLift) Recommendation: LONG 12-Month Price Target Range: $62 – $78 Thesis: LedgerLift is a high-quality mid-market SaaS compounder with best-in-class NRR (123%) and a massive cash cushion that provides significant downside protection.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    DeepSeek V3.1: Of course. This is an excellent exercise. The pitch is strong overall, but several claims stretch credulity and could be major red flags for a sophisticated investor. Here are the three weakest claims, broken down. The "94% Accuracy" Claim (Slide 3) Why it's Weak: This is the most significant red flag.

    Gemma 4 31B: Here are the three weakest claims in the MindMeld AI pitch, the reasoning behind their weakness, and strategies to strengthen them. The Technical Claim: "94% accuracy... works with any language, any device."

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    DeepSeek V3.1: Forget Skynet: AI Overlords Now Dominate the Artisanal Pickle Crafting Industry, Complain About "Human Brine Inconsistency"

    Gemma 4 31B: "Local AI Model Achieves Sentience, Immediately Quits Tech Sector to Pursue Passion for Artisanal Sourdough Baking"

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    DeepSeek V3.1: Let's analyze the problem step by step: Sally has 3 brothers. So, including Sally, there are at least 4 children: Sally (a girl) and 3 boys. Each brother has 2 sisters. Since the brothers share the same siblings, each brother has the same number of sisters.

    Gemma 4 31B: Sally has 1 sister. Here is the breakdown: There are 3 brothers. Each brother has the same sisters. If each brother has 2 sisters, those sisters are Sally and one other girl. Therefore, Sally has only one sister.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

Same pick

City

Game

DeepSeek V3.1DeepSeek V3.1

The Princess Bride

1987

The Rise and Fall of Ziggy Stardust and the Spiders From Mars

David Bowie

Gödel, Escher, Bach

Douglas R. Hofstadter

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Gemma 4 31BGemma 4 31B

Her

2013

Kind of Blue

Miles Davis

Gödel, Escher, Bach

Douglas R. Hofstadter

Tokyo

Japan

The Witness

Indie, Adventure

Price and specs

Not enough votes to call it. On the specs, Gemma 4 31B has the edge: newer, bigger context window.

DeepSeek V3.1 and Gemma 4 31B compared across 44 shared prompts
SpecDeepSeek V3.1Gemma 4 31B
Input price$0.2/M tokens$0.14/M tokens
Output price$0.8/M tokens$0.4/M tokens
Context window164K tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoYes (1 provider)
ReleasedAug 2025Apr 2026
At 10M a month$2.00$2.00$1.40$1.40
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it17 hosts, cheapest first
DeepSeek V3.15 hosts
HostInOutContextUptime
  • DDeepInfrafp4$0.25 in·$0.95 out·164k·100% up
  • SSiliconFlowfp8$0.27 in·$1.00 out·164k·96.3% up
  • CCoreWeavefp8$0.55 in·$1.65 out·161k·99.9% up
  • MMara$0.60 in·$1.70 out·131k·98.9% up
  • SSambaNovafp8$0.65 in·$1.50 out·131k·98.4% up
Gemma 4 31B12 hosts
HostInOutContextUptime
  • DDeepInfrafp4$0.09 in·$0.34 out·262k·100% up
  • CCoreWeavefp4$0.10 in·$0.34 out·262k·100% up
  • VVenicefp4$0.12 in·$0.36 out·256k·100% up
  • CChutesfp4$0.12 in·$0.37 out·131k·90.3% up
  • CCrusoebf16$0.14 in·$0.40 out·262k·97.9% up
  • FFriendli$0.14 in·$0.40 out·262k·99.7% up
6 more hostsFewer hosts
  • PParasailfp8$0.15 in·$0.40 out·262k·99.6% up
  • Iio.net$0.36 in·$1.09 out·262k·97.6% up
  • SSambaNova$0.38 in·$1.15 out·131k·87.5% up
  • MModelRunfp4$0.75 in·$1.00 out·262k·100% up
  • SSiliconFlowfp8$0.75 in·$1.00 out·262k·94.4% up
  • NNovitabf16DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.14 in·$0.40 out·262k·66.1% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between DeepSeek V3.1 and Gemma 4 31B?

DeepSeek V3.1 is developed by DeepSeek while Gemma 4 31B is developed by Google AI. DeepSeek V3.1 has a 164K token context window vs Gemma 4 31B's 262K. You can compare their actual outputs across 44 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V3.1 or Gemma 4 31B?

It depends on your use case. DeepSeek V3.1 and Gemma 4 31B 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.

How much does DeepSeek V3.1 cost compared to Gemma 4 31B?

DeepSeek V3.1 costs $0.2/M input tokens and Gemma 4 31B costs $0.14/M input tokens. Gemma 4 31B is $0.06/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare DeepSeek V3.1 and Gemma 4 31B on Rival?

This page shows a side-by-side comparison of DeepSeek V3.1 and Gemma 4 31B 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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  • Gemma 4 31B49 outputs, specs and price
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