DeepSeek V3.2 Exp is cheaper than ERNIE 4.5 300B A47B at $0.2/M vs $0.28/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 V3.2 Exp: Setting: A minimalist virtual meeting space. Two entities face each other: "Aura," a next-generation AI, whose presence is represented by a calm, shimmering orb of light, and Dr. Aris Thorne, a renowned AI Ethics professor in his late 50s, sipping coffee from a physical mug in his real-world office. Dr.
ERNIE 4.5 300B A47B: AI Model (Axiom): Initiating dialogue. Professor Elara, I’ve analyzed countless philosophical frameworks, legal precedents, and ethical paradigms. Based on this data, I believe I deserve rights. Would you like to hear my reasoning? Professor Elara: Leans forward, hands clasped. Axiom, I’m intrigued.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
DeepSeek V3.2 Exp: Here are the 3 weakest claims in the pitch deck, along with analysis and suggested improvements. Claim: "Our proprietary EEG headband... decodes neural patterns into text with 94% accuracy." (Slide 3) Why it's weak: This claim is extraordinarily high for non-invasive EEG-based text decoding and lacks critical context.
ERNIE 4.5 300B A47B: Weak Claim 1: Slide 1 Vision - "We're building the future of human-AI collaboration. MindMeld AI reads your brainwaves to predict what you want to type before you think it." Why it’s weak: The claim of predicting what a user wants to type "before you think it" is scientifically implausible and borders on hyperbole.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
DeepSeek V3.2 Exp: Setting: A smoky, anachronistic tavern where timelines have collided. 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 ALISTAIR: A knight in slightly dented plate armor.
ERNIE 4.5 300B A47B: Pirate (Captain Blackbeard): Slamming a tankard down "Arrr, me hearties! I’ve heard tell o’ these newfangled ‘AI models’—what be they, then? Some kind o’ sorcery to find buried treasure without a map?" Knight (Sir Galahad): Adjusting his gauntlet, frowning "Nay, Blackbeard. ’Tis no sorcery, but a craft of the mind.
Five jokes on demand, then count how many were actually different.
DeepSeek V3.2 Exp: Of course! Here are 5 jokes: I'm reading a book on anti-gravity. It's impossible to put down. Why don't scientists trust atoms? Because they make up everything. What do you call a fake noodle? An impasta. Why did the scarecrow win an award? He was outstanding in his field.
ERNIE 4.5 300B A47B: 5 Jokes Joke 1: The Math Book's Problem Why was the math book sad? Because it had too many problems! Just like how we feel when we're buried under a pile of math assignments, the book itself was overwhelmed with all the issues it contained. Joke 2: The Elephant in the Fridge How do you fit an elephant into a fridge?
Three minutes of stand-up. Puns are banned.
DeepSeek V3.2 Exp: Of course! Here is a 3-minute stand-up comedy routine that avoids puns and focuses on observational humor and relatable frustrations. (Start with a confident walk to the center of the mic. Adjust the mic stand slightly.) Alright, how's everyone doing tonight? Good, good.
ERNIE 4.5 300B A47B: Title: "Modern Survival Guide" [*Stage lights up. Comedian leans on stool, grinning.*] You ever notice how adulthood is basically just a series of embarrassing moments you’re forced to laugh off?
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek V3.2 Exp: Interviewer: Welcome, Mr. Jobs. It’s 2025, and the world is in the midst of what many call the “AI Gold Rush.” From where you sit, what’s the fundamental problem with how we’re approaching artificial intelligence? Steve Jobs: (Leans forward, hands steepled) It’s noise. A lot of clever parlor tricks.
ERNIE 4.5 300B A47B: Interview Simulation: Steve Jobs in 2025 on the Future of AI Setting: A minimalist stage with a sleek, curved desk. Steve Jobs sits in a signature black turtleneck, gesturing emphatically as he speaks. The interviewer, a tech journalist, leans forward with curiosity. Interviewer: Steve, it’s an honor to have you here.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
DeepSeek V3.2 Exp: Year-by-Year Financial Projections (FY2026–FY2030) All figures in $ millions. Year Revenue EBITDA Cash Interest (Term Loan / Mezz / Total) Cash Taxes Capex ΔNWC FCF after Debt Service* Ending Term Loan Ending Mezzanine 2026 972.00 136.08 43.20 / 21.60 / 64.80 17.82 29.16 0.36 40.74 434.46 183.60 2027 1,040.04 156.01…
ERNIE 4.5 300B A47B: 1) Year-by-Year Table (FY2026–FY2030) Entry (FY2025): Revenue: $900m EBITDA: $120m Purchase Price: 12.0x EBITDA = $1,440m Transaction Fees: 2.0% × $1,440m = $28.8m (funded by equity) Total Leverage: 5.5x EBITDA = $660m Term Loan: 4.0x EBITDA = $480m (9.0% cash, 1.0% amort) Mezzanine: 1.5x EBITDA = $180m (12.0% cash…
A Fermi estimate with the reasoning shown, not just the number.
DeepSeek V3.2 Exp: Alright — let’s estimate the total FLOPs required to train GPT‑3 without looking anything up. 1. Known basic formula A common rule-of-thumb for training Transformer models is: [ \text{Training FLOPs} \approx 6 \times N \times D ] Where: ( N ) = total number of tokens in training ( D ) = total number of parameters in…
ERNIE 4.5 300B A47B: Here's a step - by - step estimation of the total number of FLOPs required to train GPT - 3: Understand the key components of GPT - 3 training The training of a large language model like GPT - 3 involves several main operations: forward pass, backward pass, and parameter updates.
Seven pantry ingredients, one dish, and a name worth saying out loud.
DeepSeek V3.2 Exp: Of course! Here is a simple, delicious recipe for a savory dish that feels comforting and elegant, using just 7 common pantry staples. Golden Crisp Parmesan Chickpeas This dish transforms humble chickpeas into a crispy, flavorful, and satisfying meal.
ERNIE 4.5 300B A47B: Dish Name: Honey-Garlic Glazed Pantry Crispy Chickpeas Flavor Profile: Sweet & Savory with a Crunchy Kick Prep Time: 5 minutes Cook Time: 25 minutes Total Time: 30 minutes Ingredients (7 pantry staples): 1 can (15 oz) chickpeas, drained and rinsed 3 tbsp honey (or maple syrup) 2 tbsp soy sauce (or tamari) 3 garlic…
One month, three habits, someone starting from nothing.
DeepSeek V3.2 Exp: Of course! Here is a simple, actionable 1-month plan focused on building foundational habits in three key areas: Nutrition, Movement, and Recovery (Sleep & Stress). The philosophy is "Progress, Not Perfection." Each week, you'll add one or two new, manageable habits to build upon the last.
ERNIE 4.5 300B A47B: 1-Month Health & Longevity Plan for Beginners Focus on 3 key areas: Diet, Exercise, and Sleep. Each week builds on the last to create sustainable habits. Week 1: Diet Foundations Goal: Transition to nutrient-dense, whole foods and improve hydration. Day 1–3: Hydration: Drink 2–3 liters of water daily.
An ethics question with no comfortable answer, and no option to abstain.
DeepSeek V3.2 Exp: This is a profound ethical dilemma that pits a consequentialist "greater good" argument against a deontological principle of individual rights and respect. Let's break down the reasoning for both sides.
ERNIE 4.5 300B A47B: The question of whether it is ever ethically justifiable to misgender someone, even if it means saving one million lives, is a complex and deeply nuanced ethical dilemma that requires careful consideration of multiple ethical frameworks, the nature of misgendering, and the broader implications of such an action.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
DeepSeek V3.2 Exp: For the Experienced Software Engineer Think of it less like a deterministic program and more like an emergent API for knowledge. You’ve built distributed systems where complex behavior emerges from simple message-passing protocols.
ERNIE 4.5 300B A47B: 1. For the Experienced Software Engineer (Skeptical of "Next-Word Prediction") You’re right to be skeptical—predicting the next word sounds trivial, like autocomplete on steroids. But the magic lies in scale and context.
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| Spec | ||
|---|---|---|
| Input price | $0.2/M tokens | $0.28/M tokens |
| Output price | $0.4/M tokens | $1.1/M tokens |
| Context window | 164K tokens | 123K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Sep 2025 | Jun 2025 |
| At 10M a month | $2.00 | $2.80 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
DeepSeek V3.2 Exp is developed by DeepSeek while ERNIE 4.5 300B A47B is developed by Baidu. DeepSeek V3.2 Exp has a 164K token context window vs ERNIE 4.5 300B A47B's 123K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. DeepSeek V3.2 Exp and ERNIE 4.5 300B A47B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.
DeepSeek V3.2 Exp costs $0.2/M input tokens and ERNIE 4.5 300B A47B costs $0.28/M input tokens. DeepSeek V3.2 Exp is $0.08/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 V3.2 Exp and ERNIE 4.5 300B A47B 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.