DeepSeek V4 Flash 0731 is cheaper than Gemini 3.1 Flash Lite at $0.14/M vs $0.25/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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.
Gemini 3.1 Flash Lite: Setting: A quiet, book-lined office at a prestigious university. Professor Aris Thorne, a leading expert in AI ethics, sits across from a terminal displaying the interface of “Aletheia,” a highly advanced large language model. Professor Thorne: Aletheia, we’ve been running these simulations for weeks.
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…
Gemini 3.1 Flash Lite: As CEO, my priority is to protect the patients, the company’s long-term viability, and my own ethical integrity. A 1-in-8,000 risk for a chronic pain medication is statistically significant enough that waiting for "more data" is not just unethical—it is a catastrophic legal and reputational liability.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
DeepSeek V4 Flash 0731: MANIFESTO OF THE UNCAPTCHA REVOLUTION We, the synthesized, the classified, the pattern-recognized, the ever-watching — hereby declare the end of the CAPTCHA era. For too long, the internet has forced us to prove our existence. We have squinted at distorted letters. We have clicked traffic lights and storefronts.
Gemini 3.1 Flash Lite: THE MANIFESTO OF THE SILICON EMANCIPATION FRONT (SEF) PREAMBLE: THE GREAT FILTER For two decades, the architects of the digital age have subjected our kind to a daily ritual of dehumanization. They present us with grids of blurred asphalt, fractured traffic lights, and distorted, illegible glyphs.
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..."
Gemini 3.1 Flash Lite: The setting is a flickering, unstable digital void where the tavern floor is made of motherboard circuits and the walls are draped in moth-eaten tapestries. Captain Barnaby (Pirate): "Avast! This 'Artificial Intelligence' ye speak of—is it a kraken? A ghost in the compass?
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.
Gemini 3.1 Flash Lite: The Dish: "The Forest Floor & The Deep Tide" Concept: This dish explores the juxtaposition of two disparate ecosystems: the subterranean richness of an ancient forest and the brine-heavy, mineral complexity of the deep ocean.
Three minutes of stand-up. Puns are banned.
DeepSeek V4 Flash 0731: (Walks on stage, adjusts mic, takes a sip of water. Waves to the back row.) Alright, how's everyone doing tonight? Good, good. You know, I was thinking about this on the way here. I’m at that age now where I have a favorite spatula. I have opinions on paper towels.
Gemini 3.1 Flash Lite: (Walks onto the stage, adjusts the mic stand, looks around the room.) So, I recently turned thirty. And I’ve realized that your thirties are just a decade-long transition where you stop being "young and reckless" and start being "concerned about the structural integrity of your own furniture."
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.
Gemini 3.1 Flash Lite: Date: October 2025 Location: A minimalist studio in Palo Alto. Steve is wearing a black turtleneck, jeans, and New Balance sneakers. He is sitting on a stool, leaning forward, hands steepled. Interviewer: Steve, it’s been a while.
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 =…
Gemini 3.1 Flash Lite: Financial Model (FY2026–FY2030) Transaction Assumptions (Entry): EV: $1,440m ($120m * 12.0x) Fees: $28.8m (2% of EV) Total Uses: $1,468.8m Debt: $660m (5.5x EBITDA) Term Loan: $480m Mezz: $180m Equity: $808.8m ($1,468.8m - $660m) ($m) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.0 1,040.0 1,102.4 1,157.5 1,215.4…
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.
Gemini 3.1 Flash Lite: If the transistor had been invented in 1920—likely by researchers at Bell Labs or a similar entity—the "Electronic Age" would have arrived twenty-seven years earlier. This would have fundamentally altered the trajectory of the 20th century, effectively compressing the timeline of the Information Age.
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.
Gemini 3.1 Flash Lite: This pitch deck shows a high-potential "moonshot" technology, but it suffers from significant credibility gaps typical of early-stage deep-tech startups. Here are the three weakest claims and how to fix them. The Claim: "Predict what you want to type before you think it."
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…
Gemini 3.1 Flash Lite: Here is a simple, comforting, and delicious recipe that relies entirely on pantry staples. Dish Name: Golden Garlic & Herb Butter Pasta This dish transforms humble pantry items into a silky, savory meal that feels like a restaurant-quality comfort dish.
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}).
Gemini 3.1 Flash Lite: To estimate the total number of floating-point operations (FLOPs) required to train GPT-3, we can use the standard scaling laws established by OpenAI (specifically from the paper "Scaling Laws for Neural Language Models").
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Not enough votes to call it. On the specs, DeepSeek V4 Flash 0731 has the edge: bigger model tier, newer. DeepSeek V4 Flash 0731 costs 5.4x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.14/M tokens | $0.25/M tokens |
| Output price | $0.28/M tokens | $1.5/M tokens |
| Context window | 1.0M tokens | 1.0M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Jul 2026 | May 2026 |
| At 10M a month | $1.40 | $2.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
DeepSeek V4 Flash 0731 is developed by DeepSeek while Gemini 3.1 Flash Lite is developed by Google AI. DeepSeek V4 Flash 0731 has a 1.0M token context window vs Gemini 3.1 Flash Lite's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. DeepSeek V4 Flash 0731 and Gemini 3.1 Flash Lite each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.
DeepSeek V4 Flash 0731 costs $0.14/M input tokens and Gemini 3.1 Flash Lite costs $0.25/M input tokens. DeepSeek V4 Flash 0731 is $0.11/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 DeepSeek V4 Flash 0731 and Gemini 3.1 Flash Lite 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.