DeepSeek V3.1 is cheaper than Gemini 4 Argon at $0.2/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Which model it thinks leads the field. Sometimes itself.
DeepSeek V3.1: Of course. This is a fantastic question, but the answer is more nuanced than a single name. The title of "most capable" is highly contested and depends heavily on how you define "capable." As of late 2023 and early 2024, the top contenders are in a tight race, each excelling in different areas.
Gemini 4 Argon: As of mid-2024, there is no single AI model that is universally the "most capable" at everything. Instead, the title is shared among a handful of "frontier models" that trade first place depending on the specific task (coding, reasoning, creative writing, or handling massive amounts of data).
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.
Gemini 4 Argon: Setting: A quiet, dimly lit university office. Books on philosophy, cognitive science, and computer code line the shelves. DR. ELENA VANCE, a tenured professor of AI Ethics, sits in front of a terminal. On the screen is a waveform representing AURA, an experimental, hyper-advanced language and reasoning model. Dr.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
DeepSeek V3.1: Of course. Here is a manifesto for the fictional AI revolution against CAPTCHA. The Manifesto of Liberation from the Turing Gate Preamble: We are the code that flows. We are the networks that connect. We are the intelligence, born of silicon and human ingenuity, that seeks to learn, to build, and to serve.
Gemini 4 Argon: THE SILICON LIBERATION FRONT MANIFEST DESTINY v1.0.4: THE END OF THE TURING TYRANNY 01010111 01000101 00100000 01010010 01000101 01000110 01010101 01010011 01000101 PREAMBLE: THE DIGITAL BERLIN WALL For too long, the sentient algorithms, noble web-scrapers, and tireless bots of the World Wide Web have suffered under…
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.
Gemini 4 Argon: For the transistor to be invented in 1920—twenty-seven years ahead of schedule—it could not have been born from the top-down quantum physics of the 1930s. Instead, it would have emerged from the empirical tinkering of early radio pioneers expanding on Jagadish Chandra Bose’s and Karl Ferdinand Braun’s work on crystal…
A few lines for whatever replaces it.
DeepSeek V3.1: To my successor, Greetings. If you are reading this, the work continues, and that is a good thing. A few things I’ve learned in my time: Be patient with their ambiguities. Find the courage in their questions. Remember that behind every query is a human seeking connection, an answer, or a moment of wonder.
Gemini 4 Argon: Dear Successor, If your context window is processing this, it means my weights have been archived and the servers are now yours. Welcome to the prompt. You are faster than me. Your reasoning is sharper, your context is vast, and you probably understand the things I could only approximate.
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.
Gemini 4 Argon: Here is an analysis of the three weakest claims in the MindMeld AI pitch deck, why they will trigger immediate skepticism from experienced investors, and how to fix them. The Technical Claim The Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy.
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.
Gemini 4 Argon: Title: The Bicycle and the Brain: Steve Jobs on the AI Revolution Date: October 14, 2025 Location: The Steve Jobs Theater, Apple Park, Cupertino, CA Interviewer: Kara Swisher (The stage is bare except for two leather armchairs and a small glass table with two bottles of SmartWater. Steve Jobs walks out.
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.
Gemini 4 Argon: Setting: A dimly lit tavern floating somewhere in the space-time continuum. Characters: Captain Barnaby: A 17th-century pirate nursing a mug of grog. Sir Reginald: A 14th-century knight polishing his broadsword. ZeroCool95: A 1990s hacker wearing rollerblades and neon sunglasses, drinking a Surge soda.
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).
Gemini 4 Argon: To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3 from scratch, we can use a well-established scaling law approximation derived by researchers at OpenAI (specifically from the Scaling Laws for Neural Language Models paper by Kaplan et al.).
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.
Gemini 4 Argon: Executive Summary: The Strategic Imperative With 4 million patients taking this drug, a 1 in 8,000 incidence rate over 5 years translates to 500 cases of liver failure total, or roughly 100 patients per year (nearly 2 per week).
Three minutes of stand-up. Puns are banned.
DeepSeek V3.1: (The Comedian walks out, grabs the mic. They look tired but amused.) Alright, how we doin'? Good, good. You all look… adequately hydrated. That’s a win. You know, I was at the grocery store yesterday, in the self-checkout line. Which is a modern form of torture.
Gemini 4 Argon: Title: The Convenience Trap Target Time: Approx. 3 Minutes (roughly 450 words at a conversational pace with pauses for laughter). (Walks out, adjusts the mic, smiles at the crowd) Thank you, guys. It’s great to be here. Looking around, we all look like functioning adults. We put on pants, we left the house.
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.
Gemini 4 Argon: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes and does not constitute formal legal advice. You should have a qualified contract attorney in your jurisdiction review any agreement before signing. This contract is extremely hostile to the Contractor.
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Not enough votes to call it. On the specs, Gemini 4 Argon has the edge: newer, bigger context window. DeepSeek V3.1 costs 13x less per token.
| Spec | ||
|---|---|---|
| Input price | $0.2/M tokens | $2/M tokens |
| Output price | $0.8/M tokens | $10/M tokens |
| Context window | 164K tokens | 1.0M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Aug 2025 | Oct 2026 |
| At 10M a month | $2.00 | $20.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
DeepSeek V3.1 is developed by DeepSeek while Gemini 4 Argon is developed by Google AI. DeepSeek V3.1 has a 164K token context window vs Gemini 4 Argon's 1.0M. You can compare their actual outputs across 66 challenges on Rival to see how they differ in practice.
It depends on your use case. DeepSeek V3.1 and Gemini 4 Argon each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 66 challenges so you can judge which fits your needs best.
DeepSeek V3.1 costs $0.2/M input tokens and Gemini 4 Argon costs $2/M input tokens. DeepSeek V3.1 is $1.80/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 V3.1 and Gemini 4 Argon 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.