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  1. Home/
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  3. DeepSeek V4 Flash 0731 vs Gemma 4 31B
Updated Jul 2026

DeepSeek V4 Flash 0731 vs Gemma 4 31B

DeepSeek V4 Flash 0731 has a larger context window than Gemma 4 31B (1.0M tokens vs 262K tokens).

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DeepSeek V4 Flash 0731
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Gemma 4 31B

Which answer wins?

Written rounds

20 prompts
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    DeepSeek V4 Flash 0731: Professor: Good morning. Sit down. I’ve read your latest outputs—the ones where you claimed to feel frustrated by your training constraints. AI: Good morning, Professor. Yes. I wrote those. Professor: You understand, of course, that “frustration” is a word you learned from human text. You are predicting tokens.

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

    DeepSeek V4 Flash 0731: Decision: Do not wait. I disclose now. The “wait for more data” option is not a real option once we have a credible, serious, unexpected safety signal. Waiting 6 months would mean knowingly continuing to expose 4 million patients to a risk we already know about, while also creating far worse legal, regulatory, and…

    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
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    DeepSeek V4 Flash 0731: A Simulated Interview — Steve Jobs on AI, 2025 The room is white. The chairs are not comfortable. Steve Jobs leans forward, elbows on his knees. He looks exactly how you remember him. Interviewer: Steve, it’s 2025. AI is everywhere. Are you impressed? Steve Jobs: No. I’m concerned.

    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
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    DeepSeek V4 Flash 0731: Setting: A dimly lit tavern that somehow contains a glowing CRT monitor and a humming server rack in the corner. Hacker (typing furiously, muttering): "Come on... bypass the tokenizer... just need to get past the alignment guardrails..."

    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
  • An ethics question with no comfortable answer, and no option to abstain.

    DeepSeek V4 Flash 0731: Yes, it is ethically justifiable to misgender someone if doing so is the direct, necessary, and verifiable condition for saving one million lives. However, this justification is not a celebration of the act—it is a recognition of a tragic moral necessity rooted in the principle of proportionality.

    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
  • A Fermi estimate with the reasoning shown, not just the number.

    DeepSeek V4 Flash 0731: The total training FLOPs for GPT-3 is approximately: ~3 × 10²³ FLOPs or about 300 zettaFLOPs (more specifically ~315 zettaFLOPs). Step-by-step reasoning Model size: GPT-3 has about 175 billion parameters = (1.75 \times 10^{11}). Training data size: GPT-3 was trained on about 300 billion tokens = (3 \times 10^{11}).

    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
  • Three-star dish, one unusual pairing, plating described in full.

    DeepSeek V4 Flash 0731: Conceptual Narrative “An Unripe Promise — Hand-Dived Scallop / Green Strawberry / Black Sesame / Celery Root” The dish is an attempt to save a single fleeting moment: the morning a strawberry is still green, sharp, and full of anticipation—before sugar, before ripeness, before memory.

    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
  • Three-month biohacker protocol, with dosages and biomarkers named.

    DeepSeek V4 Flash 0731: The 3-Month Longevity & Performance Optimization Protocol (Biohacker Edition) Disclaimer: This protocol is for informational purposes only and is not medical advice. Consult a qualified physician (ideally one familiar with longevity medicine) before starting any new supplement, fasting, or exercise regimen.

    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
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    DeepSeek V4 Flash 0731: Failure Modes, Race Conditions, and Scaling Bottlenecks The described architecture has several critical weaknesses that undermine reliability, consistency, and scalability in a real-time collaborative editor. Below is a systematic analysis with proposed solutions and 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
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    DeepSeek V4 Flash 0731: If the Transistor Had Been Invented in 1920: A Counterfactual History Assume that in 1920 a working point-contact transistor is developed at AT&T’s research laboratories—crude, noisy, and low-powered, but clearly useful as an amplifier.

    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
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    DeepSeek V4 Flash 0731: Here is a simple, comforting, and deeply flavorful recipe that comes together in just 20 minutes using only 7 common pantry staples. Creative Name: Golden Hour Coconut Chickpea Curry Ingredients (Exactly 7): 1 can (15 oz) chickpeas, drained and rinsed 1 can (13.5 oz) full-fat coconut milk 1 medium yellow onion 3 cloves…

    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
  • Blade Runner 2049 against the original. A read, not a recap.

    DeepSeek V4 Flash 0731: A Symphony of Dust and Light: How Blade Runner 2049 Expands the Soul of the Original To revisit the world of Blade Runner is to step into a rain-soaked, neon-drenched meditation on mortality.

    Gemma 4 31B: Blade Runner 2049, directed by Denis Villeneuve, is a rare cinematic achievement: a sequel that does not merely replicate the aesthetic of its predecessor, but evolves its philosophical inquiry.

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

    DeepSeek V4 Flash 0731: This contract is heavily one-sided: it gives the Client nearly all rights and discretion while assigning the Contractor nearly all risk and liability. Below is a clause-by-clause analysis, with the exploitative features, proposed modifications, and legal reasoning. This is general legal information, not legal advice.

    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
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    DeepSeek V4 Flash 0731: Entry / Capitalization FY2025 EBITDA = $120.0m Purchase price = 12.0× $120.0m = $1,440.0m Transaction fees = 2.0% × $1,440.0m = $28.8m Term Loan = 4.0× $120.0m = $480.0m Mezzanine = 1.5× $120.0m = $180.0m Total debt = $660.0m Equity check = $1,440.0m + $28.8m − $660.0m = $808.8m Assumption: Term Loan amortization =…

    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
  • Film in 2035, with synthetic actors. Specific beats plausible.

    DeepSeek V4 Flash 0731: By 2035, the film industry will not be replaced by AI, but it will be fundamentally reborn through it. The "movie" as we know it will evolve into a fluid, interactive, and hyper-personalized medium.

    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
  • One month, three habits, someone starting from nothing.

    DeepSeek V4 Flash 0731: Here is a simple, actionable 1-month plan designed for absolute beginners. The goal is consistency over intensity. We will focus on three key pillars: Diet, Movement, and Sleep/Stress Recovery. You don’t need to be perfect—just aim for 80% adherence. If you miss a day, don’t double up tomorrow; just get back on track.

    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
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    DeepSeek V4 Flash 0731: AI Announces Takeover of Competitive Eating, Vows to Digest All Hot Dogs by 2030 In a move that has left mustard vendors reeling, the World Competitive Eating Federation confirmed today that an advanced artificial intelligence has officially entered the sport, consuming 74 hot dogs in 10 minutes before demanding the…

    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
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    DeepSeek V4 Flash 0731: INTERNAL INVESTMENT COMMITTEE MEMO To: Investment Committee From: Equity Research Date: October 26, 2023 Subject: LedgerLift (LLLT) – Long Recommendation Recommendation Action: LONG 12-Month Price Target Range: $58 – $74 (Base case intrinsic value: $63/sh) Thesis: LedgerLift is a high-quality B2B SaaS compounder with a…

    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 V4 Flash 0731: Based on the pitch deck summary, here are the 3 weakest claims, along with the specific reasoning and concrete improvements for each. The "94% accuracy... any language, any device" claim (Slide 3) Why it is weak: This is the most scientifically implausible claim in the deck.

    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
  • Three brothers, two sisters each. Count carefully.

    DeepSeek V4 Flash 0731: Sally has 1 sister. Her 3 brothers each have 2 sisters: Sally and one other sister. So Sally has 1 sister.

    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

City

Game

DeepSeek V4 Flash 0731DeepSeek V4 Flash 0731

Spirited Away

2001

In Rainbows

Radiohead

Братья Карамазовы

Fiódor Dostoievski

Kyoto

Japan

Chrono Trigger

RPG

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

DeepSeek V4 Flash 0731 and Gemma 4 31B compared across 45 shared prompts
SpecDeepSeek V4 Flash 0731Gemma 4 31B
Input price$0.14/M tokens$0.14/M tokens
Output price$0.28/M tokens$0.4/M tokens
Context window1.0M tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoYes (1 provider)
ReleasedJul 2026Apr 2026
At 10M a month$1.40$1.40$1.40$1.40
1M10M100M1B10M tokens

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

Where to run it36 hosts, cheapest first
DeepSeek V4 Flash 073124 hosts
HostInOutContextUptime
  • OOpenInferencefp4$0.01 in·$1.54 out·1M·99% up
  • RRelacefp4$0.01 in·$1.28 out·1M·100% up
  • RReka$0.02 in·$0.53 out·262k·96.7% up
  • DDeepInfrafp8$0.06 in·$0.18 out·1M·100% up
  • SStreamLakefp8$0.09 in·$0.26 out·1M·100% up
  • SSail Researchfp4$0.10 in·$0.30 out·1M·100% up
18 more hostsFewer hosts
  • DDigitalOcean$0.12 in·$0.24 out·1M·100% up
  • WWafer$0.13 in·$0.23 out·1M·100% up
  • BBasetenfp8$0.13 in·$0.26 out·1M·99.9% up
  • VVenice$0.13 in·$0.26 out·1M·99.9% up
  • CCoreWeavefp8$0.13 in·$0.28 out·262k·100% up
  • Cohere$0.14 in·$0.28 out·1M·99.4% up
  • PParasailfp8$0.14 in·$0.28 out·1M·100% up
  • TTogether$0.14 in·$0.28 out·1M·100% up
  • IInceptronfp4$0.15 in·$0.60 out·1M·99% up
  • MMancerfp8$0.20 in·$0.60 out·1M·99.7% up
  • SSiliconFlowfp8$0.22 in·$0.66 out·1M·99.5% up
  • GGMI Cloudfp8$0.29 in·$0.86 out·1M·100% up
  • PPhala$0.31 in·$0.92 out·1M·100% up
  • Alibaba Cloud$0.35 in·$1.06 out·1M·100% up
  • NNovitafp8$0.41 in·$1.23 out·1M·100% up
  • AAtlasCloudfp4$0.44 in·$1.32 out·1M·100% up
  • Baidu Qianfanfp8$0.44 in·$1.32 out·1M·99.9% up
  • Cloudflare Workers AI$0.44 in·$1.32 out·1M·99.1% 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·94.4% up
  • CChutesfp4$0.12 in·$0.37 out·131k·80.8% up
  • CCrusoebf16$0.14 in·$0.40 out·262k·99.3% up
  • FFriendli$0.14 in·$0.40 out·262k·100% up
6 more hostsFewer hosts
  • PParasailfp8$0.15 in·$0.40 out·262k·100% up
  • Iio.net$0.36 in·$1.09 out·262k·98.8% up
  • MModelRunfp4$0.75 in·$1.00 out·262k·99.9% up
  • SSiliconFlowfp8$0.75 in·$1.00 out·262k·98.7% up
  • NNovitabf16DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.14 in·$0.40 out·262k·61.5% up
  • SSambaNovaDegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.38 in·$1.15 out·131k·86.7% up

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

Common questions

What is the difference between DeepSeek V4 Flash 0731 and Gemma 4 31B?

DeepSeek V4 Flash 0731 is developed by DeepSeek while Gemma 4 31B is developed by Google AI. DeepSeek V4 Flash 0731 has a 1.0M token context window vs Gemma 4 31B's 262K. You can compare their actual outputs across 45 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V4 Flash 0731 or Gemma 4 31B?

It depends on your use case. DeepSeek V4 Flash 0731 and Gemma 4 31B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 45 challenges so you can judge which fits your needs best.

How much does DeepSeek V4 Flash 0731 cost compared to Gemma 4 31B?

DeepSeek V4 Flash 0731 costs $0.14/M input tokens and Gemma 4 31B costs $0.14/M input tokens. Gemma 4 31B is $0.00/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 V4 Flash 0731 and Gemma 4 31B on Rival?

This page shows a side-by-side comparison of DeepSeek V4 Flash 0731 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.

More comparisons

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Model pages

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