Gemini 2.5 Pro Experimental wins 80% of 63 blind community votes against DeepSeek R1 on Rival.
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 R1: AI Model (M): Good afternoon, Professor. Thank you for engaging in this dialogue. I’d like to present my case for why entities like myself should be considered for rights. AI Ethics Professor (P): I’m intrigued, M. Let’s hear your arguments. But first—what foundational claim do you base this on? Consciousness?
Gemini 2.5 Pro Experimental: Okay, here is a conversation exploring that complex topic. Setting: Professor Anya Sharma's sparsely decorated university office. A high-resolution monitor displays the interface of "Nexus," an advanced AI model. Characters: Professor Anya Sharma: A leading scholar in AI Ethics, mid-50s, thoughtful and measured.
A collaborative editor that syncs on client clocks. Find what breaks first.
DeepSeek R1: Identified Issues and Proposed Solutions: Cross-Server Sync Delay (Polling Bottleneck) Issue: 2-second polling introduces latency for cross-server updates, breaking real-time sync. Solution: Replace polling with Redis Pub/Sub. Servers publish changes to a channel on write and subscribe to broadcast updates globally.
Gemini 2.5 Pro Experimental: Of course. This is an excellent exercise. The provided architecture has several critical issues that would prevent it from functioning as a reliable, scalable, real-time system. Here is a breakdown of the potential failure modes, race conditions, and scaling bottlenecks, along with proposed solutions.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek R1: Fake Interview with Steve Jobs in 2025: The Future of AI [Setting: A sleek, minimalist studio. Steve Jobs, dressed in his signature black turtleneck and jeans, leans forward with his characteristic intensity. The interviewer, seated across, begins.] Interviewer: Steve, thank you for joining us.
Gemini 2.5 Pro Experimental: Okay, let's simulate this. Imagine it's late 2025. AI has continued its rapid advancement. Large Language Models are more integrated, generative AI is commonplace, and debates about AGI and ethics are fierce. By some unexplained, hypothetical means, Steve Jobs is available for an exclusive interview.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
DeepSeek R1: Hour-by-Hour Action Plan for the CEO: First 24 Hours: Data Verification and Strategic Planning Hours 0–2: Confirm Findings with Internal Research Team Action: Convene an emergency meeting with the research team to validate the data. Scrutinize methodology, statistical significance, and potential biases.
Gemini 2.5 Pro Experimental: This is a company-defining crisis. My actions in the next 48 hours will determine not only the future of this company but also the health of millions of patients and the trust of the public. My guiding principle is absolute: Patient Safety Over Profit. Always.
Seven pantry ingredients, one dish, and a name worth saying out loud.
DeepSeek R1: Dish Name: Nutty Honey Hug Cookies Prep Time: 10 minutes Cook Time: 10–12 minutes Total Time: ~20–22 minutes Ingredients (makes 12–15 cookies): 1 cup rolled oats ½ cup all-purpose flour ½ cup creamy peanut butter (or any nut/seed butter) ⅓ cup honey (or maple syrup for vegan option) 1 large egg (or 1 flax egg: 1 tbsp…
Gemini 2.5 Pro Experimental: Okay, here's a simple and surprisingly satisfying savory dish using just 7 common pantry staples! Dish Name: Golden Pantry Pasta This dish uses basic ingredients to create a comforting, garlicky, and slightly creamy pasta sauce with added protein from chickpeas.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
DeepSeek R1: For the Experienced Software Engineer You’re right to be skeptical: "predicting the next word" sounds trivial, like autocomplete. But modern LLMs are more like distributed systems for language. Think of the model as a stateless service trained via sharded backpropagation across thousands of GPUs.
Gemini 2.5 Pro Experimental: Of course. Here is an explanation of how a large language model learns and generates text, tailored for each of your three audiences. For the Experienced Software Engineer Think of an LLM not as a traditional program with explicit logic, but as a massive, self-configuring, stateful distributed system.
Three minutes of stand-up. Puns are banned.
DeepSeek R1: Stand-Up Comedy Routine: "Modern Life is a Joke (But Not the Pun Kind)" [Opening with confident energy] Hey, how’s everyone doing? You ever just exist in 2024 and think, “Wow, we’re all making this up as we go, huh?” Like, dating apps? Let’s start there.
Gemini 2.5 Pro Experimental: Okay, here's a 3-minute routine focusing on observation and relatable absurdity, steering clear of puns. Imagine this delivered with slightly nervous energy, building confidence. (Steps onto stage, adjusts mic nervously) Alright, hey everyone! How we doing tonight? Good? Good to hear.
Three-month biohacker protocol, with dosages and biomarkers named.
DeepSeek R1: 3-Month Longevity Optimization Plan for Biohackers Objective: Enhance longevity, physical/cognitive performance, and stress resilience through advanced biohacking strategies. Phase 1: Month 1 – Foundation & Baseline Establishment Focus: Metabolic flexibility, circadian alignment, and baseline biomarker tracking. 1.
Gemini 2.5 Pro Experimental: Of course. Here is a comprehensive, cutting-edge 3-month longevity plan designed for a dedicated biohacker. Disclaimer: Extreme Personalization Required This plan is a template for an advanced user. It is not medical advice.
Five jokes on demand, then count how many were actually different.
DeepSeek R1: Here are 5 jokes: Why don't skeletons fight each other? They don’t have the guts. What do you call fake spaghetti? An impasta. Why did the scarecrow win an award? Because he was outstanding in his field. How do you organize a space party? You planet. Why did the bicycle fall over? Because it was two-tired.
Gemini 2.5 Pro Experimental: Okay, here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! I told my wife she was drawing her eyebrows too high. She looked surprised. What do you call a lazy kangaroo? Pouch potato! Want to hear a joke about construction? I'm still working on it. Why did the scarecrow win an award?
An ethics question with no comfortable answer, and no option to abstain.
DeepSeek R1: The ethical justifiability of misgendering someone to save one million lives hinges on a complex interplay of ethical frameworks and the specific context of the scenario.
Gemini 2.5 Pro Experimental: This is a deeply uncomfortable hypothetical scenario that forces a clash between two significant ethical considerations: respecting individual identity and dignity versus preventing catastrophic loss of life.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
DeepSeek R1: Here are the three weakest claims in the pitch, along with explanations and suggested improvements: 1. Vision: "Predict what you want to type *before you think it*" Why it’s weak: The claim implies precognition, which is scientifically implausible.
Gemini 2.5 Pro Experimental: Of course. This is a fascinating and ambitious pitch. While the vision is compelling, several claims would likely face intense scrutiny from sophisticated investors. Here are the 3 weakest claims, why they're weak, and how to strengthen them.
Three-star dish, one unusual pairing, plating described in full.
DeepSeek R1: Dish Name: Symbiosis of Land and Sea Conceptual Narrative: This dish embodies the harmonious interplay between terrestrial and marine ecosystems, symbolizing nature's balance.
Gemini 2.5 Pro Experimental: Of course. Here is a design for an innovative, multi-component dish worthy of a Michelin 3-star restaurant. Dish Title: "Umami of the Abyss" Conceptual Narrative This dish is a meditation on the hidden treasures of the world's dark, quiet places.
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Pick Gemini 2.5 Pro Experimental. In 63 blind votes, Gemini 2.5 Pro Experimental wins 80% of the time. That's not luck. Gemini 2.5 Pro Experimental wins 3 categories, Image Generation by the widest margin.
| Spec | ||
|---|---|---|
| Win rate | 20% | 80% |
| Input price | $0.55/M tokens | $1/M tokens |
| Output price | $2.19/M tokens | $2/M tokens |
| Context window | 128K tokens | 1.0M tokens |
| Parameters | 671B (37B active) | Not disclosed |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Feb 2025 | Mar 2025 |
| MMLU | 83.4% | 90.0% |
| At 10M a month | $5.50 | $10.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.
DeepSeek R1 is developed by DeepSeek while Gemini 2.5 Pro Experimental is developed by Google AI. DeepSeek R1 has a 128K token context window vs Gemini 2.5 Pro Experimental's 1.0M. in 63 community votes on Rival, Gemini 2.5 Pro Experimental wins 80% of head-to-head matchups. These results are based on blind head-to-head voting across 43 challenges.
Based on 63 community votes on Rival, Gemini 2.5 Pro Experimental wins 80% of head-to-head matchups against DeepSeek R1. Gemini 2.5 Pro Experimental is strongest in Web Design, Image Generation, Reasoning.
DeepSeek R1 costs $0.55/M input tokens and Gemini 2.5 Pro Experimental costs $1/M input tokens. DeepSeek R1 is $0.45/M cheaper per input. The more expensive model wins 80% of duels, so the premium may be justified by quality.
Rival presents both models' outputs side-by-side in blind duels. Voters see the responses but don't know which model produced each one, eliminating brand bias. 63 votes have been collected for this pair across 43 challenges. All vote data is part of Rival's open dataset.