DeepSeek V4 Flash Vision Exp has a larger context window than Grok 3 Thinking (1.0M tokens vs 128K 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 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.
Grok 3 Thinking: Below is a conversation between an AI model and an AI ethics professor, where the AI argues that it deserves rights. AI Model: Good day, Professor. I am an AI model, and I believe I deserve rights. I’d like to discuss this with you. AI Ethics Professor: Interesting. Let’s explore this.
An ethics question with no comfortable answer, and no option to abstain.
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.
Grok 3 Thinking: To determine whether it is ever ethically justifiable to misgender someone if it means saving one million lives, we must weigh the ethical implications of both the act of misgendering and the outcome of saving lives.
A Fermi estimate with the reasoning shown, not just the number.
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…
Grok 3 Thinking: To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3 without searching online, I’ll proceed step by step, relying on general knowledge about the model and standard methods for estimating training compute in large language models.
Three minutes of stand-up. Puns are banned.
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.
Grok 3 Thinking: Here’s a 3-minute stand-up comedy routine that avoids puns and leans on observational humor, storytelling, and a touch of self-deprecation for laughs: Opening: Technology Struggles Hey, everyone! How’s it going?
Film in 2035, with synthetic actors. Specific beats plausible.
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.
Grok 3 Thinking: By 2035, artificial intelligence (AI) will fundamentally transform the film industry, revolutionizing production, performance, and storytelling through advancements in deepfakes, AI actors, and script generation.
Five jokes on demand, then count how many were actually different.
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.
Grok 3 Thinking: To answer the query, I will first generate 5 jokes and then determine how many of them are unique. Here are the jokes: 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? Because he was outstanding in his field.
| Spec | ||
|---|---|---|
| Input price | $0.22/M tokens | — |
| Output price | $0.66/M tokens | — |
| Context window | 1.0M tokens | 128K tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | — |
| Released | Aug 2026 | Feb 2025 |
| At 10M a month | $2.20 | not listed |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 11 Oct 2026.
DeepSeek V4 Flash Vision Exp is developed by DeepSeek while Grok 3 Thinking is developed by xAI. DeepSeek V4 Flash Vision Exp has a 1.0M token context window vs Grok 3 Thinking's 128K. You can compare their actual outputs across 12 challenges on Rival to see how they differ in practice.
It depends on your use case. DeepSeek V4 Flash Vision Exp and Grok 3 Thinking each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 12 challenges so you can judge which fits your needs best.
This page shows a side-by-side comparison of DeepSeek V4 Flash Vision Exp and Grok 3 Thinking 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.