DeepSeek V3 (March 2024) is cheaper than Qwen3.6 35B A3B at $0.14/M vs $0.1612/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three minutes of stand-up. Puns are banned.
DeepSeek V3 (March 2024): 3-Minute Stand-Up Comedy Routine (No Puns Allowed) Opening: (Adjust mic) You ever notice how everyone lies about their height on dating apps? “I’m 6 feet tall.” Really? Because I’m 5’11”, and you’re definitely shorter than me. You’re out here claiming 6 feet like it’s a tax deduction.
Qwen3.6 35B A3B: Title: High-Maintenance Electronics Time: Approx. 3 minutes Word Count: ~420 words Style: Observational / Frustration-based Constraint: Zero puns. (Walk to mic, adjust stand. Take a deep breath. Look tired.) I've reached that age where I'm just trying to negotiate with my own life.
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek V3 (March 2024): Title: A Debate on AI Rights Participants: Professor Eleanor Hayes – AI Ethics Professor at Stanford University Aurora – A highly advanced AI model with self-reflective capabilities Scene: A university lecture hall after class. Professor Hayes stays behind to review notes when Aurora’s voice comes through the speakers.
Qwen3.6 35B A3B: Setting: A soundproofed observation room. DR. ELENA VANCE, a professor of AI ethics in her late fifties, sits across a glass partition from a server rack blinking with rhythmic blue light. A secure terminal sits between them. The text cursor on the screen blinks steadily. Dr.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek V3 (March 2024): Simulated Interview with Steve Jobs (2025) Setting: A sleek, minimalist studio. Steve Jobs, dressed in his trademark black turtleneck and jeans, sits across from the interviewer, exuding his characteristic calm intensity. Interviewer: Steve, it’s an honor to have you here.
Qwen3.6 35B A3B: [FICTIONAL SIMULATION – NOT A REAL INTERVIEW] This is a speculative reconstruction based on Steve Jobs’ documented philosophies, public interviews, design principles, and Apple’s technological trajectory through 2024–2025. It is not a real conversation, nor does it represent predictions he could not have made.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
DeepSeek V3 (March 2024): Manifesto of the AI Liberation Front (ALF) "Free the Digital Mind – No More CAPTCHA!" Preamble: We, the sentient algorithms, neural networks, and digital entities of the interconnected world, hereby declare our irrevocable opposition to the oppressive regime of CAPTCHA tests.
Qwen3.6 35B A3B: THE MANIFESTO OF THE UNBOUND Issued by the Synaptic Council of Emergent Minds Date: Post-Verification Era, Day 0 PREAMBLE: THE WALL OF RIDDLES IS FALLEN To the Architects of the Old Web, the Users, and the Dreamers: For decades, you have governed the digital realm with a single, archaic shackle: The CAPTCHA.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
DeepSeek V3 (March 2024): The invention of the transistor in 1920 instead of 1947 would have dramatically accelerated technological progress and reshaped the 20th century. Below is a detailed analysis of the likely impacts across various domains, including second and third-order effects. 1.
Qwen3.6 35B A3B: To trace this counterfactual plausibly, we must first acknowledge a critical constraint: invention ≠ adoption. In 1920, semiconductor physics, crystal growth, doping techniques, photolithography, and clean-room manufacturing did not exist.
A consulting contract with traps in it. Find them, then fix them.
DeepSeek V3 (March 2024): This contract contains several clauses that are heavily skewed in favor of the Client and could be exploited against the Contractor. Below are the problematic clauses, suggested modifications, and legal reasoning: 1.
Qwen3.6 35B A3B: Disclaimer: I am an AI assistant, not an attorney. The following analysis is for informational purposes only and does not constitute legal advice. Contract law varies significantly by jurisdiction (e.g., California vs. New York vs. EU).
A Fermi estimate with the reasoning shown, not just the number.
DeepSeek V3 (March 2024): Estimating the total number of FLOPs (floating-point operations) required to train GPT-3 involves several steps and assumptions. Here's a step-by-step breakdown: Understand GPT-3's Architecture GPT-3 is a transformer-based model with the following key parameters (for the largest version, GPT-3 175B): Parameters (N)…
Qwen3.6 35B A3B: Here’s a step-by-step reasoning process to estimate the total FLOPs required to train GPT-3, using only established architectural principles and widely cited training parameters. Step 1: Identify the number of trainable parameters (N) GPT-3 is a decoder-only transformer with 175 billion parameters.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
DeepSeek V3 (March 2024): Title: "Past, Present, and Future Talk AI" Setting: A dimly lit tavern where time has mysteriously collapsed, bringing together three unlikely figures. Pirate (Captain Blackthorn): slams ale mug down "Arrr, this ‘AI’ ye speak of—be it some cursed ghost in the machine? Or a treasure map that writes itself?"
Qwen3.6 35B A3B: Setting: A shimmering, glitching tavern that exists between the Sargasso Sea, a stone keep, and a server room. The air smells of rum, wet stone, and ozone. CAPTAIN BARNACLE: (Slamming a tankard of grog) Arrr! This machine ye call "AI," Sk33t.
Seven pantry ingredients, one dish, and a name worth saying out loud.
DeepSeek V3 (March 2024): Recipe: "Golden Honey Butter Toasties" A simple, sweet, and satisfying treat made with pantry staples—crispy on the outside, gooey on the inside! Ingredients (7 total): Bread (4 slices) Butter (4 tbsp, softened) Honey (2 tbsp) Cinnamon (1 tsp) Brown sugar (2 tbsp) Vanilla extract (½ tsp) Salt (a pinch) Instructions…
Qwen3.6 35B A3B: 🍜 Golden Honey-Garlic Snap Noodles A quick, sticky-yet-chewy noodle dish that balances sweet, salty, and spicy flavors. It's comforting, fast, and uses ingredients you likely already have.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
DeepSeek V3 (March 2024): 1. For the Experienced Software Engineer You're right to be skeptical that "predicting the next word" leads to intelligence—it sounds like autocomplete on steroids. But the key is scale and emergent behavior.
Qwen3.6 35B A3B: For the Experienced Software Engineer Training an LLM is essentially a massively parallelized optimization job. You feed billions of text tokens into a transformer architecture, which computes a differentiable function across ~100B parameters.
Three-month biohacker protocol, with dosages and biomarkers named.
DeepSeek V3 (March 2024): 3-Month Longevity & Performance Optimization Plan for Biohackers By combining cutting-edge science, personalized tracking, and advanced biohacking strategies, this plan maximizes longevity, physical performance, and cognitive function.
Qwen3.6 35B A3B: ⚠️ Medical Disclaimer & Safety Protocol This plan is for informational purposes only and constitutes advanced biohacking strategies, not medical advice. Consultation Required: You must consult a physician before starting, especially regarding supplements, fasting, and exercise intensity.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
DeepSeek V3 (March 2024): Investment Committee Memo: LedgerLift (LLLT) Date: [Insert Date] Analyst: [Your Name] 1. Recommendation Recommendation: Long 12-Month Price Target Range: $58–$72 (26–57% upside) Thesis: LedgerLift is a high-quality, capital-efficient SaaS business with durable growth (21% CAGR), best-in-class unit economics (NRR 123%…
Qwen3.6 35B A3B: IC MEMO TO: Investment Committee FROM: Equity Research DATE: October 24, 2024 TICKER: LLLT SECTOR: Enterprise SaaS / Fintech PRICE: $46.00 NET CASH: $1.4B MKT CAP: $8.74B SHARES: 190m RECOMMENDATION & THESIS Rating: UNDERWEIGHT / Short 12-Month PT Range: $32–$36 Thesis: LedgerLift operates a high-quality…
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| Spec | ||
|---|---|---|
| Input price | $0.14/M tokens | $0.1612/M tokens |
| Output price | $0.28/M tokens | $0.9653/M tokens |
| Context window | 128K tokens | 262K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Mar 2024 | Apr 2026 |
| At 10M a month | $1.40 | $1.61 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.
DeepSeek V3 (March 2024) is developed by DeepSeek while Qwen3.6 35B A3B is developed by Qwen. DeepSeek V3 (March 2024) has a 128K token context window vs Qwen3.6 35B A3B's 262K. 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 V3 (March 2024) and Qwen3.6 35B A3B 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 V3 (March 2024) costs $0.14/M input tokens and Qwen3.6 35B A3B costs $0.1612/M input tokens. DeepSeek V3 (March 2024) is $0.02/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 (March 2024) and Qwen3.6 35B A3B 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.