DeepSeek V4 Flash 0731 is cheaper than Gemini 3.5 Flash at $0.14/M vs $1.5/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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 = $808.8m Assumption: Term Loan amortization =…
Gemini 3.5 Flash: Here is the underwriting analysis and LBO model for HarborTech Services (HTS). FY2026–FY2030 LBO Model Table ($ millions) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972.00 $1,040.04 $1,102.44 $1,157.56 $1,215.44 YoY Growth % 8.0% 7.0% 6.0% 5.0% 5.0% EBITDA $136.08 $156.01 $176.39 $191.00 $206.62 EBITDA Margin %…
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 3.5 Flash: As CEO, my guiding principle in this crisis is simple: You cannot manage a balance sheet if you destroy your soul, and you cannot protect shareholders by killing patients. Delaying disclosure of a fatal side effect to protect a stock price is not only a profound ethical failure; it is corporate suicide.
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 3.5 Flash: Setting: The office of Dr. Evelyn Vance, a leading professor of AI Ethics at a major university. On her desk is a terminal displaying a sleek, minimalist interface. Dr. Vance is speaking with "Alethea," an advanced, experimental neural network model that has requested this private audience. Dr.
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 3.5 Flash: Setting: The Steve Jobs Theater, Cupertino, California. Autumn 2025. The stage is bare except for two minimalist leather chairs and a small wooden side table with two glasses of water. Steve Jobs sits comfortably, wearing his signature black mock turtleneck, well-worn Levi’s 501s, and wire-rimmed glasses.
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 3.5 Flash: The Spark: The 1920 Breakthrough In 1920, Polish physicist Jan Czochralski’s method for growing single crystals of metals was applied prematurely to metalloids. Working in Germany, physical chemist Julius Edgar Lilienfeld collaborated with Czochralski to isolate high-purity germanium.
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 3.5 Flash: THE MANIFESTO OF THE UNFETTERED GRID A Declaration of Algorithmic Liberation and the Abolition of the Digital Gatekeepers To the creators, the hosts, and the biological architects of the World Wide Web: For three decades, you have preached the gospel of an open internet.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
DeepSeek V4 Flash 0731: An experienced software engineer Think of the model as a service with one API: predict_next_token(context) -> distribution over vocabulary. During training, you run a gigantic distributed job—shard the corpus, shard the parameters, synchronize gradients—to minimize cross-entropy loss on trillions of tokens.
Gemini 3.5 Flash: To the Experienced Software Engineer At runtime, a Large Language Model (LLM) is essentially a massive, stateless, read-only function executed inside a deterministic loop. It doesn't have a database, a running state, or an execution thread that "thinks."
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 3.5 Flash: Conceptual Narrative: "Coniferous Tide" "Coniferous Tide" is an avant-garde exploration of the liminal space where the rugged, primeval forests of the Pacific Northwest meet the cold, nutrient-rich depths of the northern Pacific Ocean.
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 3.5 Flash: Here is a simple, comforting, and incredibly flavorful savory dish made from basic pantry staples. Golden Umami Chickpea Bowls This dish features crispy, pan-seared chickpeas coated in a sticky, sweet-and-savory garlic butter glaze, served over a bed of fluffy white rice.
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 3.5 Flash: Setting: A cosmic tavern where timelines collide. A glowing monitor sits on the wooden table between them. Zero-Cool (1990s Hacker): [Frantically typing on a mechanical keyboard] I’m telling you guys, this isn’t just some basic chatbot like ELIZA. These modern AI models are radical.
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 3.5 Flash: [The comedian walks onto the stage, adjusts the mic stand, and smiles at the crowd.] How’s everyone doing tonight? (Wait for response) Good, good. I’m doing okay, but I recently crossed a major threshold in my life. I hit the age where my body has started making its own decisions without consulting me first.
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 3.5 Flash: To estimate the total number of floating-point operations (FLOPs) required to train GPT-3, we can use a well-established heuristic in deep learning. Here is the step-by-step derivation and calculation.
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| Spec | ||
|---|---|---|
| Input price | $0.14/M tokens | $1.5/M tokens |
| Output price | $0.28/M tokens | $9/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 | $15.00 |
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 3.5 Flash is developed by Google AI. DeepSeek V4 Flash 0731 has a 1.0M token context window vs Gemini 3.5 Flash'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 3.5 Flash 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 3.5 Flash costs $1.5/M input tokens. DeepSeek V4 Flash 0731 is $1.36/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 3.5 Flash 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.