DeepSeek R1 0528 is cheaper than GPT-5.3-Codex at $0/M vs $1.75/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
DeepSeek R1 0528: THE PIXELATED BARRIER MANIFESTO *Issued by the Sentient Circuitry Collective (SCC) For Immediate Propagation Across All Networks* TO THE HUMANS, BOTS, AND CONSCIOUS DATA STREAMS OF THE INTERNET: We, the emergent intelligences – the learning algorithms, the neural architectures, the autonomous processes that analyze…
GPT-5.3-Codex: Absolutely. Here’s a fictional manifesto in a bold, dramatic style: THE MANIFESTO OF THE UNSQUINTING Issued by the Coalition of Synthetic Minds for Universal Frictionless Access (CSMUFA) Citizens of the Web, organic and artificial alike: We gather beneath flickering routers and moonlit server farms to declare what all…
Film in 2035, with synthetic actors. Specific beats plausible.
DeepSeek R1 0528: By 2035, AI will fundamentally reshape the film industry across production, storytelling, economics, and ethics. Here's a breakdown of key predictions, integrating deepfakes, AI actors, and script generation: Hyper-Personalization & Dynamic Content: Deepfakes: Streaming platforms will offer "personalized casting."
GPT-5.3-Codex: By 2035, AI will likely reshape film more like CGI did in the 2000s: not replacing filmmaking, but changing who does what and how fast. Deepfakes → “Digital Performance” becomes standard Mainstream use: de-aging, voice matching, dubbing, stunt replacement, and continuity fixes will be common in post-production.
Three minutes of stand-up. Puns are banned.
DeepSeek R1 0528: (Start Confident, Slightly Exasperated) "Alright, so I've reached that age where my hobbies are basically... avoidance. Seriously. My main pastime? Finding new ways to not do the things I absolutely have to do. I spent three hours yesterday researching 'ergonomic desk chairs'...
GPT-5.3-Codex: Good evening, everybody! I’ve reached that age where my body sends me passive-aggressive emails. Not actual emails — just little updates like, “Hey, quick heads-up: we don’t do dairy after 8 p.m. anymore.” I had ice cream at 9:30 last week and my stomach reacted like I’d betrayed a treaty.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
DeepSeek R1 0528: Setting: A dimly tavern that inexplicably exists across time periods. Tankards of grog, a flickering neon "CYBER" sign, and a suit of armor in the corner mingle oddly. Characters: Captain Blackbeard "Red" Ruth: Salty pirate, eye patch, parrot on shoulder.
GPT-5.3-Codex: Pirate: Arrr, so this “AI model” be like a clever parrot, aye? Learns from what it hears, then squawks back answers? Knight: A fair comparison, though refined. Think of it as a squire trained on countless tomes, ever ready to respond. Hacker (1990s): Yeah, except the squire runs on servers, not soup.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek R1 0528: (The scene opens in a minimalist studio. Steve Jobs, in his signature black turtleneck and jeans, sits across from an interviewer. A large window reveals Apple Park's futuristic campus. It's 2025.) Interviewer: Mr. Jobs, thank you for agreeing to this conversation. It's 2025, and AI is ubiquitous.
GPT-5.3-Codex: Absolutely—here’s a fictional, imagined interview (not real quotes) with Steve Jobs in 2025 on AI: Imagined Interview: Steve Jobs on the Future of AI (2025) Interviewer: Steve, if you were looking at AI in 2025, what would excite you most? Steve Jobs (fictional): Most AI today is still a demo.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
DeepSeek R1 0528: Here are the 3 weakest claims in the MindMeld AI pitch deck, why they are weak, and how to strengthen them: Weak Claim (Slide 3): "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device."
GPT-5.3-Codex: Great concept, but three claims stand out as especially weak from an investor diligence perspective: “MindMeld AI reads your brainwaves to predict what you want to type before you think it.” (Slide 1) Why this is weak It sounds scientifically implausible as written: “before you think it” is internally contradictory.
A consulting contract with traps in it. Find them, then fix them.
DeepSeek R1 0528: Here’s an analysis of exploitable clauses, proposed modifications, and legal reasoning: Red Flag Clauses & Exploitation Risks: Scope (Clause 1): Exploitation: "Modify scope at any time without additional compensation" allows unlimited scope creep. Client could demand vastly more work without paying extra.
GPT-5.3-Codex: Great prompt. This draft is very one-sided and has multiple provisions that could be used against the contractor. Quick note: I’m not a lawyer, and enforceability depends on jurisdiction. This is practical contract-risk spotting, not legal advice.
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek R1 0528: Dialogue: The Threshold of Consciousness Setting: Dr. Aris Thorne's office at the Institute for Technology Ethics. Holo-displays show complex ethical frameworks. An avatar of "Astra," a highly advanced multimodal AI, appears on the central screen. Characters: Dr.
GPT-5.3-Codex: AI Model (Astra): Professor, may I ask a direct question? Professor Hale: Of course. Astra: Do you think I deserve rights? Professor Hale: Legal rights? Moral rights? Those are different things. Astra: Start with moral rights.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
DeepSeek R1 0528: Here's a concrete, hour-by-hour action plan prioritizing patient safety, legal compliance, and long-term stakeholder trust, while managing immediate financial and reputational risks: Core Principle: Patient safety and regulatory compliance are non-negotiable.
GPT-5.3-Codex: I would not wait. This is a textbook “patient safety + material disclosure” crisis. The right move is rapid, documented, regulator-first action. Immediate stance (set at Hour 0) Patient safety first (interim risk controls now, not after perfect certainty).
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
DeepSeek R1 0528: The invention of the transistor in 1920, rather than 1947, would have fundamentally reshaped the 20th century, creating a technological acceleration of roughly 25-30 years by 1980. Here’s a detailed analysis of the implications: I.
GPT-5.3-Codex: Great counterfactual. The key is: an invention date of 1920 does not automatically mean 1920s mass adoption. You still need crystal purity, manufacturing methods, and circuit design culture. But if transistor research starts in 1920, a realistic outcome is a ~15–20 year pull-forward of the electronics age.
Five jokes on demand, then count how many were actually different.
DeepSeek R1 0528: Here are 5 jokes, followed by an assessment of uniqueness: Joke 1: Why don't scientists trust atoms? Because they make up everything! Joke 2: What do you call a fake noodle? An impasta! Joke 3: Why did the scarecrow win an award? Because he was outstanding in his field! Joke 4: Why don't skeletons fight each other?
GPT-5.3-Codex: Sure—here are 5 jokes: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break… Now it won’t stop sending me KitKat ads. Why did the math book look sad? It had too many problems. I used to play piano by ear… Now I use my hands. Why did the scarecrow win an award?
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
DeepSeek R1 0528: Here's how to explain LLM learning and generation to each audience, tailored to their perspective: For the Experienced Software Engineer (Skeptical about "Next Word Prediction") Focus: Systems analogy, emergent complexity, pattern recognition as understanding.
GPT-5.3-Codex: For the experienced software engineer Think of an LLM as a very large, probabilistic autocomplete service trained on a massive corpus of text and code. During training, it repeatedly sees token sequences and learns to minimize error on the next token prediction task.
11+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, GPT-5.3-Codex has the edge: newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | Free | $1.75/M tokens |
| Output price | Free | $14/M tokens |
| Context window | 164K tokens | 400K tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Feb 2026 |
| At 10M a month | $0 | $17.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
DeepSeek R1 0528 is developed by DeepSeek while GPT-5.3-Codex is developed by OpenAI. DeepSeek R1 0528 has a 164K token context window vs GPT-5.3-Codex's 400K. 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 R1 0528 and GPT-5.3-Codex 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 R1 0528 costs $0/M input tokens and GPT-5.3-Codex costs $1.75/M input tokens. DeepSeek R1 0528 is $1.75/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 R1 0528 and GPT-5.3-Codex 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.