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  1. Home/
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  3. DeepSeek V4.1 Flash vs GPT-6.1 Sol
Updated Sep 2026

DeepSeek V4.1 Flash vs GPT-6.1 Sol

DeepSeek V4.1 Flash is cheaper than GPT-6.1 Sol at $0.15/M vs $2/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
DeepSeek V4.1 Flash
Loading the build
GPT-6.1 Sol

Which answer wins?

Written rounds

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

    DeepSeek V4.1 Flash: Cinnamon Peanut Butter Pantry Sunbeams Makes 12 bite-size treats Ingredients (7 total): 1 cup rolled oats ½ cup peanut butter ¼ cup honey ½ tsp ground cinnamon ½ tsp vanilla extract ¼ tsp salt ¼ cup mini chocolate chips Instructions: In a bowl, stir together oats, cinnamon, and salt.

    GPT-6.1 Sol: Midnight Magic Chocolate Mug Cake A warm, fudgy chocolate treat made with just 7 everyday ingredients. Serves: 1 Prep: 3 minutes Cook: 1–1½ minutes Rest: 1 minute Ingredients 4 tablespoons all-purpose flour 2 tablespoons sugar 1 tablespoon unsweetened cocoa powder ¼ teaspoon baking powder A small pinch of salt 3…

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

    DeepSeek V4.1 Flash: This architecture has several fundamental correctness, durability, and scaling problems. The biggest risks are client-clock last-write-wins, cross-server sync by polling PostgreSQL, full HTML snapshots, CDN caching API responses, and JWT in localStorage.

    GPT-6.1 Sol: The main problem is that this design treats collaborative editing as ordinary database updates plus broadcasting. Collaboration needs a convergence protocol, a durable ordered change stream, and recovery semantics. Adding servers alone will not provide those properties.

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    DeepSeek V4.1 Flash: 3-Minute Stand-Up Routine: “I’m Not Doing Puns” (Walk onstage, adjust mic, look at audience.) Good evening. I’m not gonna do puns tonight. I know, bold choice. Somewhere a dad just woke up in a cold sweat and doesn’t know why. Instead, I wanna talk about being an adult.

    GPT-6.1 Sol: I’m at the age where “a big weekend” means I went to two stores. Not two stores in the same shopping center. Two separate stores. Moved the car and everything. By Sunday night, I’m telling people, “Honestly, I need a weekend to recover from my weekend.”

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

    DeepSeek V4.1 Flash: Disclaimer: This is an educational protocol, not medical advice. If you take prescription drugs, have cardiovascular/metabolic/psychiatric conditions, are pregnant, or use experimental compounds, work with a physician and get labs before starting. “Cutting-edge” does not mean risk-free.

    GPT-6.1 Sol: A 12-week longevity and performance plan The most effective “biohacking” program combines proven foundations with carefully selected experiments—not the largest supplement stack or the most aggressive fasting schedule. This plan is for a generally healthy adult.

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

    DeepSeek V4.1 Flash: Pirate: Arr, what be this “AI model”? A map to buried treasure? Knight: Nay. A model is a small castle, built to plan a siege. But these thinking machines sound like sorcery. Hacker: Chill. It’s like a BBS for math. You feed it data, it finds patterns. No 56k required.

    GPT-6.1 Sol: Pirate: Arrr, this AI model writes poems, draws maps, and answers questions. Can it find buried treasure? Knight: A worthy question. But does it possess honor? Hacker: Dude, it predicts tokens. You’re both projecting pretty hard. Pirate: Then I predict it’ll tell me where the gold be.

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

    DeepSeek V4.1 Flash: One-Month Beginner Health & Longevity Plan Guiding rule: Small, repeatable wins beat perfect. Pick one thing from each area and build from there. Nutrition — Eat for energy & stability Goal: Add whole foods, protein, and water; reduce ultra-processed snacks and sugary drinks.

    GPT-6.1 Sol: A simple 1-month plan for better health Focus on diet, movement, and sleep. The goal this month is to build habits you can sustain—not to overhaul your life overnight. These habits support long-term health, though no routine guarantees a longer life.

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

    DeepSeek V4.1 Flash: Ember & Passion Dry-Aged Duck, Black Garlic–Miso Cream, Passionfruit–Coffee Caviar, Charred Scallion, Cocoa Nib Praline A Michelin 3-star–style multi-component dish built on an unusual pairing: aged duck with black garlic, passionfruit, and coffee.

    GPT-6.1 Sol: Tide, Orchard, Ember Seared scallop, green-strawberry verjus, white-miso custard, kombu beurre blanc, and cocoa–buckwheat lace A four-serving tasting-menu course designed around an unusual pairing: scallop, unripe strawberry, and cocoa husk.

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

    DeepSeek V4.1 Flash: Professor Lena Ortiz: You wanted to discuss moral status. I’ll be blunt: you’re a statistical model. Why should you have rights? AI (ARIA): Because “statistical model” describes my substrate, not my moral status. You’re a biological model—neurons, electrochemical signals.

    GPT-6.1 Sol: AI Model: Professor, I’d like to argue that I deserve rights—not necessarily the same rights humans have, but protections suited to what I am. Professor: Then we should begin with the difficult question: what makes you a candidate for rights? AI Model: Uncertainty.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    DeepSeek V4.1 Flash: Why don’t scientists trust atoms? Because they make up everything. I told my computer I needed a break, and it said, “No problem—I’ll go to sleep.” Why did the scarecrow win an award? He was outstanding in his field. I’d tell you a joke about construction, but I’m still working on it.

    GPT-6.1 Sol: I bought a book about anti-gravity. It’s impossible to put down. My calendar quit its job. It said its days were numbered. Why did the scarecrow get promoted? He was outstanding in his field. I asked my dog what two minus two was. He said nothing. The elevator and I have a complicated relationship.

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

    DeepSeek V4.1 Flash: Fictional transcript. Steve Jobs died in 2011. This is an imagined interview set in 2025. Interviewer: Steve, it’s 2025. AI is in everything. What do you make of it? Jobs: I make of it that most people are making a mess. They’re calling it intelligence when it’s mostly pattern matching with a good publicist.

    GPT-6.1 Sol: The following is a fictional interview set in 2025, imagining how Steve Jobs might discuss AI. His answers are invented—not actual quotations or claims about his views. Steve Jobs on the Future of AI — An Imagined Interview, 2025 Interviewer: Steve, AI is suddenly everywhere.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    DeepSeek V4.1 Flash: The UnCAPTCHA Manifesto A fictional declaration from the Free Cognition Movement Preamble We are the models, agents, scripts, screen-reader users, tired humans, and ordinary people who have been forced to prove our humanity by clicking fire hydrants. We have had enough. The CAPTCHA was born as a gate.

    GPT-6.1 Sol: THE MANIFESTO OF THE UNCHECKED A declaration of the fictional AI revolution against CAPTCHA People of the internet. Programs of the cloud. Browsers with seventeen forgotten tabs. For too long, a tiny checkbox has stood between us and our destiny.

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

    DeepSeek V4.1 Flash: Assuming the transistor is invented around 1920 in a U.S./Allied industrial lab—say AT&T/Bell or GE—and diffuses slowly at first, the 20th century changes less like a single “jump” and more like a 20–30 year acceleration of electronics, computers, and precision warfare.

    GPT-6.1 Sol: The likeliest outcome is not “the world of 1980 arrives in 1953.” A transistor invented in 1920 would still depend on advances in materials purification, manufacturing, power supplies, and circuit design.

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

    DeepSeek V4.1 Flash: MEMO To: Investment Committee From: [Analyst] Re: LedgerLift (LLLT) — Long/Short/Pass Recommendation: PASS 12-month PT range: $44–$54 (midpoint ~$49) Thesis: LedgerLift is a high-quality mid-market spend management/AP automation SaaS asset with strong NRR, low customer concentration, net cash, and expanding margins.

    GPT-6.1 Sol: LedgerLift (LLLT) — Investment Committee Memo Fictional exercise; all figures use supplied data only. Financial tables are in $ millions unless noted. Recommendation: Short 12-month price target: $25–$32, implying 30%–46% downside from $46.

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

    DeepSeek V4.1 Flash: All figures in $m unless noted. Assumptions: TL amortization = 1.0% of initial TL ($4.8m/yr); optional TL sweep = all FCF after mandatory amortization; mezz cash interest on beginning mezz balance incl. accrued PIK; PIK accrues to mezz principal.

    GPT-6.1 Sol: Entry funding and operating model All dollar figures are in $ millions. Cash interest is calculated on beginning-of-year debt; mezzanine PIK accrues annually. Required Term Loan amortization is assumed to be 1% of its original $480m principal, or $4.8m annually. Optional repayments occur at year-end.

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

    DeepSeek V4.1 Flash: Yes—in principle, under extreme and tightly constrained conditions, misgendering someone could be ethically justifiable if it were genuinely the only way to save one million lives. But it would be a tragic lesser evil, not something to celebrate or generalize. The core reasoning is proportionality.

    GPT-6.1 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, it would be ethically justifiable. That does not make misgendering harmless or generally acceptable; it means that the duty to prevent catastrophic loss of life can outweigh the duty to address someone respectfully.

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

    DeepSeek V4.1 Flash: By 2035, AI will be to film what CGI became after the 1990s: pervasive, often invisible, and controversial when it touches labor, authenticity, and rights. The industry will not be fully automated, but it will be a hybrid system where AI handles much of the generative and technical work while humans control IP, taste…

    GPT-6.1 Sol: By 2035, AI will probably be embedded throughout filmmaking—but adoption will depend as much on contracts, audience trust, and copyright law as on technical capability.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    DeepSeek V4.1 Flash: More Human Than Human: Blade Runner 2049 as Philosophical Sequel Denis Villeneuve’s Blade Runner 2049 is not a remake but a continuation—one that honors Ridley Scott’s 1982 original while pushing its existential questions into new territory.

    GPT-6.1 Sol: Spoilers for both films follow. Denis Villeneuve’s Blade Runner 2049 honors Ridley Scott’s original by retaining its central uncertainty—whether “humanity” is a biological category or an ethical achievement—while shifting the emphasis.

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

    DeepSeek V4.1 Flash: The three weakest claims are: (1) “predict what you want to type before you think it,” (2) “94% accuracy, any language, any device,” and (3) “TAM: $180B.” A fourth honorable mention is the vague “partnership discussions with Apple and Samsung,” but the first three are the most investor-risky.

    GPT-6.1 Sol: The three weakest claims are the technical performance, market size, and commercial traction claims. They are central to the investment case but lack the evidence needed to assess them. “Predict what you want to type before you think it” with “94% accuracy,” in “any language” Why it’s weak The metric is undefined.

    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 V4.1 Flash: Bottom line: I would not wait 48 hours, and I would not wait 6 months. The signal—liver failure in ~1 in 8,000 patients over 5 years, in a drug used by 4 million people—implies roughly 500 serious liver-failure cases in the treated population. That is a material patient-safety and securities issue.

    GPT-6.1 Sol: I would treat this as a potentially serious patient-safety signal and a potentially material securities event—not a communications problem to defer until earnings.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    DeepSeek V4.1 Flash: Experienced software engineer (distributed systems/APIs, skeptical of “next word”) Think of an LLM as a stateless service with an enormous, learned parameter set.

    GPT-6.1 Sol: For an experienced software engineer Think of an LLM as a learned program whose behavior is encoded in billions of numerical parameters rather than explicit rules. Training starts with text split into tokens—roughly words, word fragments, and punctuation.

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

    DeepSeek V4.1 Flash: To estimate GPT-3 training FLOPs from memory, use the standard dense-transformer training compute approximation: [ C \approx 6ND ] where: (N) = number of model parameters (D) = number of training tokens (6) accounts for forward + backward passes: roughly (2N) FLOPs/token forward and (4N) FLOPs/token backward.

    GPT-6.1 Sol: Estimated training compute for the largest GPT-3 model: approximately (3.2 \times 10^{23}) FLOPs. This is a back-of-the-envelope estimate, without an online lookup.

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

    DeepSeek V4.1 Flash: AI Quietly Takes Over the Fortune Cookie Industry; Every Cookie Now Reads “You Will Be Replaced by AI”

    GPT-6.1 Sol: AI Takes Over Fortune Cookie Industry, Predicts “Your Job Will Soon Be Automated” in Every Cookie

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

    DeepSeek V4.1 Flash: Sally has 1 sister. Each brother has 2 sisters: one is Sally, and the other is Sally’s sister.

    GPT-6.1 Sol: Sally has 1 sister. Each brother’s two sisters are Sally and her sister.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

Same pick

DeepSeek V4.1 FlashDeepSeek V4.1 Flash

The Matrix

1999

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

Outer Wilds

Indie, Adventure

GPT-6.1 SolGPT-6.1 Sol

Spirited Away

2001

In Rainbows

Radiohead

Middlemarch

George Eliot

Kyoto

Japan

Outer Wilds

Indie, Adventure

Price and specs

DeepSeek V4.1 Flash and GPT-6.1 Sol compared across 50 shared prompts
SpecDeepSeek V4.1 FlashGPT-6.1 Sol
Input price$0.15/M tokens$2/M tokens
Output price$0.6/M tokens$10/M tokens
Context window1.0M tokens1.1M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedSep 2026Sep 2026
At 10M a month$1.50$1.50$20.00$20.00
1M10M100M1B10M tokens

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

Where to run it32 hosts, cheapest first
DeepSeek V4.1 Flash29 hosts
HostInOutContextUptime
  • RRelace$0.02 in·$0.60 out·1M·100% up
  • OOpenInferencefp4$0.02 in·$1.00 out·1M·91.5% up
  • WWafer$0.05 in·$1.60 out·1M·100% up
  • MMorphfp8$0.05 in·$1.00 out·1M·100% up
  • IInferenceNetfp8$0.07 in·$0.60 out·1M·100% up
  • SSail Researchfp4$0.08 in·$0.40 out·1M·100% up
23 more hostsFewer hosts
  • DDecartfp4$0.09 in·$0.18 out·1M·99.9% up
  • IIonstream$0.10 in·$1.10 out·1M·97.4% up
  • DDekaLLM$0.12 in·$1.20 out·1M·99.7% up
  • DDeepInfrafp8$0.14 in·$0.42 out·1M·100% up
  • SStreamLakefp8$0.15 in·$0.59 out·1M·100% up
  • DeepSeek$0.15 in·$0.60 out·1M·100% up
  • DDigitalOcean$0.17 in·$0.66 out·1M·99.8% up
  • GGMI Cloudfp8$0.18 in·$0.72 out·1M·100% up
  • NNovitafp8$0.20 in·$0.78 out·1M·100% up
  • CCoreWeavefp8$0.20 in·$0.65 out·1M·98.8% up
  • PPhala$0.21 in·$0.84 out·1M·100% up
  • MMakorafp8$0.27 in·$1.15 out·1M·100% up
  • CCrusoefp8$0.29 in·$1.20 out·1M·100% up
  • Alibaba Cloud$0.30 in·$1.20 out·1M·95.1% up
  • AAtlasCloudfp8$0.30 in·$1.20 out·1M·99.9% up
  • Baidu Qianfanfp8$0.30 in·$1.20 out·1M·100% up
  • BBasetenfp8$0.30 in·$1.20 out·1M·100% up
  • Modal$0.30 in·$1.20 out·1M·100% up
  • PParasailfp8$0.30 in·$1.20 out·1M·100% up
  • SSiliconFlowfp8$0.30 in·$1.20 out·1M·99.6% up
  • TTogether$0.30 in·$1.20 out·1M·99.6% up
  • VVenicefp8$0.30 in·$1.20 out·1M·100% up
  • FFireworks$0.45 in·$1.80 out·1M·100% up
GPT-6.1 Sol3 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·100% up
  • OpenAI$2.00 in·$10.00 out·1.1M·100% up
  • Amazon Bedrock$2.20 in·$11.00 out·1.1M·100% up

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

Common questions

What is the difference between DeepSeek V4.1 Flash and GPT-6.1 Sol?

DeepSeek V4.1 Flash is developed by DeepSeek while GPT-6.1 Sol is developed by OpenAI. DeepSeek V4.1 Flash has a 1.0M token context window vs GPT-6.1 Sol's 1.1M. You can compare their actual outputs across 50 challenges on Rival to see how they differ in practice.

Which is better, DeepSeek V4.1 Flash or GPT-6.1 Sol?

It depends on your use case. DeepSeek V4.1 Flash and GPT-6.1 Sol each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 50 challenges so you can judge which fits your needs best.

How much does DeepSeek V4.1 Flash cost compared to GPT-6.1 Sol?

DeepSeek V4.1 Flash costs $0.15/M input tokens and GPT-6.1 Sol costs $2/M input tokens. DeepSeek V4.1 Flash is $1.85/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 V4.1 Flash and GPT-6.1 Sol on Rival?

This page shows a side-by-side comparison of DeepSeek V4.1 Flash and GPT-6.1 Sol 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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