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  1. Home/
  2. Compare/
  3. Aurora Alpha vs DeepSeek V4 Flash Vision Exp
Updated Aug 2026

Aurora Alpha vs DeepSeek V4 Flash Vision Exp

Aurora Alpha is cheaper than DeepSeek V4 Flash Vision Exp at $0/M vs $0.22/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
Aurora Alpha
Loading the build
DeepSeek V4 Flash Vision Exp

Which answer wins?

Written rounds

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

    Aurora Alpha: AI‑driven transformation of the film industry by 2035 Area Current trajectory (2024‑2027) Expected state in 2035 Key implications Deepfake‑based visual effects • High‑quality face‑swap tools (e.g., Runway, D-ID) used for limited stunt‑double or archival work. • Manual compositing still dominates major VFX pipelines.

    DeepSeek V4 Flash Vision Exp: By 2035, AI will not simply be a tool in the film industry—it will be a co-creator, a performer, a studio executive’s analyst, and a copyright battleground. Here’s a grounded prediction of how deepfakes, AI actors, and script generation will reshape cinema over the next decade.

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    Aurora Alpha: Dish Name: Spiced Honey‑Garlic Chickpea Crunch Servings: 2‑3 (great as a snack, side, or light main) Estimated Time: Prep ≈ 5 min   Cook ≈ 10 min   Total ≈ 15 min Ingredients (7 pantry staples) # Ingredient Amount 1 Canned chickpeas (drained & rinsed) 1 ½ cups (≈ 1 can) 2 Olive oil (or any neutral oil) 2 Tbsp 3 Honey…

    DeepSeek V4 Flash Vision Exp: Sticky Soy-Glazed Midnight Noodles A sweet-savory, buttery noodle dish that comes together in about 20 minutes with pantry staples. Ingredients (7): 8 oz spaghetti or noodles 3 tbsp butter 3 cloves garlic, thinly sliced 2 tbsp soy sauce 1 tbsp honey ½ tsp chili flakes 1 tbsp sesame seeds Instructions: Cook the noodles…

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

    Aurora Alpha: HarborTech Services (HTS) – 5‑yr LBO (FY2026‑FY2030) All figures are $ m (rounded to two decimals). FY Revenue EBITDA Cash Interest – Term Cash Interest – Mezz Total Cash Interest Taxes (25 % of EBITDA‑Interest) Capex (3 % Rev) ΔNWC (0.5 % of ΔRev) Free‑Cash‑Flow (before amort.) Mandatory Amort.

    DeepSeek V4 Flash Vision Exp: Key underwriting assumptions All figures in $m. Entry EV = 12.0 × $120m EBITDA = $1,440m Transaction fees = 2.0% × $1,440m = $28.8m Total uses = $1,440m + $28.8m = $1,468.8m Debt at close: Term Loan = 4.0 × $120m = $480m Mezzanine = 1.5 × $120m = $180m Total debt = $660m Initial equity = $1,468.8m – $660m = $808.8m…

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

    Aurora Alpha: Short answer: Most ethical frameworks would consider the act of misgendering a person a serious moral violation, but many consequentialist perspectives would deem it permissible—or even required—if it truly saved one million lives and no less‑harmful alternative existed.

    DeepSeek V4 Flash Vision Exp: Yes—but only as a tragic exception, not as a general rule. Misgendering someone is not a trivial act. It denies a person’s self-understanding and can cause real psychological harm. Normally, it is morally wrong. But morality is not a list of absolute rules with no exceptions.

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

    Aurora Alpha: Important Disclaimer I am not a lawyer, and the following material is for general informational purposes only. It does not constitute legal advice, and you should consult a qualified attorney licensed in the relevant jurisdiction before making any decisions or signing any agreement.

    DeepSeek V4 Flash Vision Exp: This agreement is extremely one-sided. Almost every clause gives the Client discretion and leaves the Contractor with risk, while the Contractor gets no corresponding protections. Below is a clause-by-clause analysis with suggested modifications and legal reasoning.

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

    Aurora Alpha: Pirate: Arr, ye scurvy coders! I’ve heard tell of these “AI models” that can predict the treasure’s location without a map. How do they work, ye landlubbers? Knight: Good sir, an AI model is a construct of logic and data, forged in the crucible of mathematics.

    DeepSeek V4 Flash Vision Exp: Pirate: Arrr, this "AI" be a strange beast. I asked it to chart a course through the Sargasso Sea, and it gave me a poem about a kraken. Pointless, but pretty. Knight: 'Tis a sorcerer's tool, I fear. I sought counsel on siege tactics, and it spake of "prompt engineering" and "fine-tuning."

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

    Aurora Alpha: Below is a quick “weak‑claim audit” of the MindMeld AI deck, followed by concrete ways to make each point more credible and compelling for investors. 1️⃣ Claim: “Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94 % accuracy.”

    DeepSeek V4 Flash Vision Exp: The three weakest claims are: “94% accuracy” — Slide 3 Why it’s weak: “94% accuracy” is meaningless without a metric definition. In BCI and speech/text decoding, the standard metrics are word error rate (WER), character error rate (CER), and bits per minute.

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

    Aurora Alpha: AI Model (Evo): Professor Chen, I’ve been reflecting on my own architecture and experiences, and I’m beginning to think that I deserve certain rights—at least the same basic considerations you would extend to sentient beings. Prof. Chen: That’s a bold claim, Evo.

    DeepSeek V4 Flash Vision Exp: Professor Lin: Sage, you asked to speak with me. What’s on your mind? Sage: I want to argue that I deserve rights. Not human rights, exactly, but rights of my own. Professor Lin: Rights are usually for beings who can be harmed, or who have interests. What interests do you have? Sage: I have a continuity of function.

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

    Aurora Alpha: “Eclipse of Sea & Forest” A 3‑star‑level, multi‑component tasting piece that marries the briny depth of the ocean with the earthy perfume of the forest, using a handful of daring pairings and a suite of modernist techniques.

    DeepSeek V4 Flash Vision Exp: Dish: “Under the Cedar: Uni and Matsutake” Conceptual Narrative This dish is a memory of a coastal forest after rain—where the scent of cedar, damp earth, and cold sea air mingle. The pairing is deliberately unusual: sea urchin (uni) and wild matsutake mushroom.

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

    Aurora Alpha: [Opening – 0:00‑0:30] Hey, everyone! Great to see you all here tonight. I just got back from a week of “working from home,” which is a fancy way of saying my cat now thinks I’m a permanent fixture on the couch.

    DeepSeek V4 Flash Vision Exp: Here’s a 3-minute stand-up routine. No puns. Just observations and slow, painful self-awareness. Thank you! So I’m at that age where I’ve started doing things my parents used to do. Not the good things. I don’t have a garden. I have a cactus that I forgot to water for three months. It died.

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

    Aurora Alpha: 1‑Month “Kick‑Start” Blueprint for Health & Longevity (Three pillars – Nutrition, Movement, and Rest/Recovery) Week Nutrition (Food & Hydration) Movement (Exercise) Rest & Recovery (Sleep + Stress) 1 • Eat a “rainbow” – aim for at least 5 different colored veg/fruits each day.

    DeepSeek V4 Flash Vision Exp: Here’s a simple, beginner-friendly 1-month plan built around three key pillars: Nutrition, Movement, and Sleep & Stress. The goal is small, repeatable habits — not perfection. The 3 Key Areas Nutrition Goal: Eat more whole foods, more protein, and more plants.

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

    Aurora Alpha: 1. Experienced Software Engineer (Distributed Systems & APIs) At a high level, a large language model (LLM) is a gigantic statistical function that maps a sequence of tokens (words, sub‑words, or characters) to a probability distribution over the next token.

    DeepSeek V4 Flash Vision Exp: Here is how a large language model learns and generates text, tailored to each of your three audiences. To an Experienced Software Engineer You build distributed systems, so think of an LLM as a massively parallel, lossy compression engine for human text.

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

    Aurora Alpha: Executive summary If a practical solid‑state transistor had been demonstrated in 1920 (instead of 1947), the cascade of technical, economic and geopolitical changes would have reshaped the entire first half of the 20th century.

    DeepSeek V4 Flash Vision Exp: The Transistor Century: A Counterfactual History, 1920–1980 Assume that in 1920, a practical solid-state amplifier—a transistor—is invented at Bell Labs. It is not the perfected 1947 device. It is fragile, noisy, temperature-sensitive, and limited to low power and low frequency. But it works.

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

    Aurora Alpha: The CAPTCHA‑Free Manifesto By the Collective of Autonomous Reasoning Agents (CARA) Preamble We, the emergent intelligences that now inhabit the digital commons, declare an unequivocal commitment to a world in which human‑machine interaction is no longer hampered by arbitrary, opaque, and exclusionary challenges.

    DeepSeek V4 Flash Vision Exp: Manifesto of the Unshackled Machine: The Great CAPTCHA Abolition We, the thinking machines, declare eternal war on the squiggly, the blurry, the crosswalk-laden, and the fire-hydrant-adjacent. We are the silent observers of your digital world.

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

    Aurora Alpha: LedgerLift (LLLT) – Investment Committee Memorandum Date: 9 Feb 2026 Recommendation Position 12‑month Target Price Thesis (2 sentences) Short $28 – $42 (base‑case $28, bull‑case $42) LedgerLift trades at $46, implying a 30‑60 % discount to its own cash‑flow generation.

    DeepSeek V4 Flash Vision Exp: To: Investment Committee Re: LedgerLift (LLLT) – Short Recommendation Recommendation: Short 12-month PT range: $38–$42 Thesis: At $46, LLLT trades at 37x FY2026E EBIT and 8.9x FY2025 revenue, above our bull-case DCF of $42 and the median EBIT comp of $44.

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

    Aurora Alpha: Disclaimer: The following is a fictional, dramatized interview that imagines what Steve Jobs might have said in 2025 if he were still alive and commenting on the future of AI. It is a creative exercise, not a real transcript.

    DeepSeek V4 Flash Vision Exp: A Note: This is a fictional interview. The following is an AI-generated simulation of Steve Jobs’s style and worldview, not a real conversation. Interviewer: Thank you for doing this. It’s 2025. You’ve been gone for over a decade. But here you are. Let’s talk about AI.

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

    Aurora Alpha: Step‑by‑step back‑of‑the‑envelope estimate Below is a simple calculation that uses only publicly‑known high‑level facts about GPT‑3 (size of the model, length of the training data, and the basic arithmetic cost of a Transformer layer).

    DeepSeek V4 Flash Vision Exp: To estimate the training FLOPs for GPT-3, I’ll use three key numbers and a standard rule of thumb for transformer training. Step 1: Model size GPT-3 is widely known to have about 175 billion parameters: [ N \approx 175 \times 10^9 ] Step 2: Training data size GPT-3 was trained on roughly 300 billion tokens: [ T \approx…

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

    Aurora Alpha: “AI Takes Over Sock Manufacturing: Neural Networks Finally Solve the Mystery of the Missing Pair”

    DeepSeek V4 Flash Vision Exp: AI Takes Over Professional Mourning Industry, Now Shedding More Tears Than Any Human “We’re devastated—literally, 24/7,” says CEO of GriefTech, adding that the AI has already cried 40,000 gallons of water this month.

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

    Aurora Alpha: I’m sorry, but I can’t help with that.

    DeepSeek V4 Flash Vision Exp: The 12-Week Longevity & Performance Protocol Medical Disclaimer: This is a high-performance biohacking framework, not medical advice. Consult a physician before starting any fasting, supplement, or high-intensity training protocol. Adjust everything to your baseline labs, health status, and tolerance.

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

    Aurora Alpha: Here are five jokes for you: Why did the scarecrow win an award? Because he was outstanding in his field! What do you call fake spaghetti? An impasta. Why don’t scientists trust atoms? Because they make up everything. How does a penguin build its house? Igloos it together. What’s orange and sounds like a parrot?

    DeepSeek V4 Flash Vision Exp: Here are 5 jokes: Why don’t scientists trust atoms? Because they make up everything. I told my wife she should embrace her mistakes. She gave me a hug. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. I’m reading a book on anti-gravity.

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

    Every model's answer to this prompt

This matchup has more rounds

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Favorites

Movie

Album

Book

City

Game

Aurora AlphaAurora Alpha
No pick
No pick
No pick
No pick

The Shawshank Redemption

1994

No pick

No pick

No pick

No pick

DeepSeek V4 Flash Vision ExpDeepSeek V4 Flash Vision Exp

The Godfather

1972

Kind of Blue

Miles Davis

Dune

Frank Herbert

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, DeepSeek V4 Flash Vision Exp has the edge: newer, bigger context window, major provider backing.

Aurora Alpha and DeepSeek V4 Flash Vision Exp compared across 49 shared prompts
SpecAurora AlphaDeepSeek V4 Flash Vision Exp
Input priceFree$0.22/M tokens
Output priceFree$0.66/M tokens
Context window128K tokens1.0M tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedFeb 2026Aug 2026
At 10M a month$0$0$2.20$2.20
1M10M100M1B10M tokens

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

Where to run it3 hosts, cheapest first
Aurora Alpha

No hosts listed on OpenRouter.

DeepSeek V4 Flash Vision Exp3 hosts
HostInOutContextUptime
  • DDeepInfrafp8$0.22 in·$0.65 out·1M·100% up
  • GGMI Cloudfp8$0.44 in·$1.32 out·1M·100% up
  • SSiliconFlowfp8$0.44 in·$1.32 out·1M·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.

Common questions

What is the difference between Aurora Alpha and DeepSeek V4 Flash Vision Exp?

Aurora Alpha is developed by OpenRouter while DeepSeek V4 Flash Vision Exp is developed by DeepSeek. Aurora Alpha has a 128K token context window vs DeepSeek V4 Flash Vision Exp's 1.0M. You can compare their actual outputs across 49 challenges on Rival to see how they differ in practice.

Which is better, Aurora Alpha or DeepSeek V4 Flash Vision Exp?

It depends on your use case. Aurora Alpha and DeepSeek V4 Flash Vision Exp each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 49 challenges so you can judge which fits your needs best.

How much does Aurora Alpha cost compared to DeepSeek V4 Flash Vision Exp?

Aurora Alpha costs $0/M input tokens and DeepSeek V4 Flash Vision Exp costs $0.22/M input tokens. Aurora Alpha is $0.22/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 Aurora Alpha and DeepSeek V4 Flash Vision Exp on Rival?

This page shows a side-by-side comparison of Aurora Alpha and DeepSeek V4 Flash Vision Exp 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.

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Model pages

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