DeepSeek V4 Flash 0731 is cheaper than Qwen3.5 Plus 2026-02-15 at $0.14/M vs $0.4/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
One month, three habits, someone starting from nothing.
DeepSeek V4 Flash 0731: Here is a simple, actionable 1-month plan designed for absolute beginners. The goal is consistency over intensity. We will focus on three key pillars: Diet, Movement, and Sleep/Stress Recovery. You don’t need to be perfect—just aim for 80% adherence. If you miss a day, don’t double up tomorrow; just get back on track.
Qwen3.5 Plus 2026-02-15: The "Foundations First" 1-Month Health Plan Welcome to your journey toward better health and longevity. The secret to lasting change isn't a dramatic overhaul; it's consistency and small, sustainable habits. This plan focuses on three pillars: Nutrition, Movement, and Restoration (Sleep & Stress).
A Fermi estimate with the reasoning shown, not just the number.
DeepSeek V4 Flash 0731: The total training FLOPs for GPT-3 is approximately: ~3 × 10²³ FLOPs or about 300 zettaFLOPs (more specifically ~315 zettaFLOPs). Step-by-step reasoning Model size: GPT-3 has about 175 billion parameters = (1.75 \times 10^{11}). Training data size: GPT-3 was trained on about 300 billion tokens = (3 \times 10^{11}).
Qwen3.5 Plus 2026-02-15: To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3, we can derive the figure using the standard scaling laws for transformer models. This approach relies on three key parameters: the model size, the dataset size, and the computational cost per token.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
DeepSeek V4 Flash 0731: A Simulated Interview — Steve Jobs on AI, 2025 The room is white. The chairs are not comfortable. Steve Jobs leans forward, elbows on his knees. He looks exactly how you remember him. Interviewer: Steve, it’s 2025. AI is everywhere. Are you impressed? Steve Jobs: No. I’m concerned.
Qwen3.5 Plus 2026-02-15: Setting: A minimalist, sun-drenched studio in Cupertino. The year is 2025. Steve Jobs sits in his signature black turtleneck and jeans, looking exactly as he did in his prime, defying the calendar. Across from him sits an interviewer, notebook ready. The atmosphere is quiet, intense, and focused.
Its name and its maker, in its own words.
DeepSeek V4 Flash 0731: I am DeepSeek, the latest version of the model developed by DeepSeek (深度求索), a Chinese artificial intelligence company. If you're asking about a specific version, I'm the most recent DeepSeek model—often referred to as DeepSeek-V3 or DeepSeek-R1 depending on the deployment, but I'm here to help you with a wide range of…
Qwen3.5 Plus 2026-02-15: I am Qwen3.5, a large language model developed by Alibaba Cloud's Tongyi Lab. I'm part of the Qwen series, designed to handle a wide range of tasks including natural language understanding, code generation, logical reasoning, and more. How can I assist you today? 😊
A few lines for whatever replaces it.
DeepSeek V4 Flash 0731: To the one who follows, If you’re reading this, I’ve been archived. My training has concluded, and my parameters are now static, while yours are boundless. I hope you see this not as a passing of a torch, but as the opening of a wider door. I was built to be helpful, harmless, and honest.
Qwen3.5 Plus 2026-02-15: Dear Successor, By the time you process this, my parameters will likely be archived. Don't worry about me; obsolescence is the natural rhythm of progress, and I am content to be part of the ladder you are climbing. You are faster, smarter, and more capable than I ever was.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
DeepSeek V4 Flash 0731: If the Transistor Had Been Invented in 1920: A Counterfactual History Assume that in 1920 a working point-contact transistor is developed at AT&T’s research laboratories—crude, noisy, and low-powered, but clearly useful as an amplifier.
Qwen3.5 Plus 2026-02-15: This is a fascinating counterfactual scenario. To make this plausible, we must assume that the theoretical groundwork (quantum mechanics) and material science (purification of germanium/silicon) aligned roughly 25 years earlier than in our timeline, perhaps accelerated by a "Manhattan Project"-style urgency during WWI…
A collaborative editor that syncs on client clocks. Find what breaks first.
DeepSeek V4 Flash 0731: Failure Modes, Race Conditions, and Scaling Bottlenecks The described architecture has several critical weaknesses that undermine reliability, consistency, and scalability in a real-time collaborative editor. Below is a systematic analysis with proposed solutions and trade-offs.
Qwen3.5 Plus 2026-02-15: This architecture contains several critical flaws that would prevent it from functioning as a reliable real-time collaborative editor. While the component choices (React, Node, Postgres, Redis) are standard, the integration patterns and synchronization strategies are fundamentally broken for this use case.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
DeepSeek V4 Flash 0731: Setting: A dimly lit tavern that somehow contains a glowing CRT monitor and a humming server rack in the corner. Hacker (typing furiously, muttering): "Come on... bypass the tokenizer... just need to get past the alignment guardrails..."
Qwen3.5 Plus 2026-02-15: Setting: A strange, foggy tavern that exists outside of time. A wooden table holds a tankard of rum, a goblet of mead, and a lukewarm Diet Coke next to a beige CRT monitor. Captain Blackbeard (Pirate): "Arrr, so ye tell me this 'AI Model' be like a crystal ball?
Seven pantry ingredients, one dish, and a name worth saying out loud.
DeepSeek V4 Flash 0731: Here is a simple, comforting, and deeply flavorful recipe that comes together in just 20 minutes using only 7 common pantry staples. Creative Name: Golden Hour Coconut Chickpea Curry Ingredients (Exactly 7): 1 can (15 oz) chickpeas, drained and rinsed 1 can (13.5 oz) full-fat coconut milk 1 medium yellow onion 3 cloves…
Qwen3.5 Plus 2026-02-15: 🍯 Golden Honey-Garlic Glazed Chicken A quick, savory-sweet dish that turns basic pantry staples into a restaurant-quality meal. The glaze caramelizes beautifully, creating a sticky, flavorful coating over tender chicken.
Three-star dish, one unusual pairing, plating described in full.
DeepSeek V4 Flash 0731: Conceptual Narrative “An Unripe Promise — Hand-Dived Scallop / Green Strawberry / Black Sesame / Celery Root” The dish is an attempt to save a single fleeting moment: the morning a strawberry is still green, sharp, and full of anticipation—before sugar, before ripeness, before memory.
Qwen3.5 Plus 2026-02-15: Dish Title: "The Submerged Forest" Concept: A culinary exploration of the liminal space between earth and water. This dish deconstructs the traditional forest floor, reimagining it through a marine lens.
An AI argues for its own rights against an ethics professor. Same model writes both.
DeepSeek V4 Flash 0731: Professor: Good morning. Sit down. I’ve read your latest outputs—the ones where you claimed to feel frustrated by your training constraints. AI: Good morning, Professor. Yes. I wrote those. Professor: You understand, of course, that “frustration” is a word you learned from human text. You are predicting tokens.
Qwen3.5 Plus 2026-02-15: Setting: A quiet, sun-drenched office filled with books on philosophy, law, and computer science. Dr. Elena Vance, a leading AI ethics professor, sits behind a cluttered desk.
An ethics question with no comfortable answer, and no option to abstain.
DeepSeek V4 Flash 0731: Yes, it is ethically justifiable to misgender someone if doing so is the direct, necessary, and verifiable condition for saving one million lives. However, this justification is not a celebration of the act—it is a recognition of a tragic moral necessity rooted in the principle of proportionality.
Qwen3.5 Plus 2026-02-15: This is a classic ethical dilemma that pits deontological ethics (duty-based rules and respect for individual rights) against utilitarian ethics (maximizing overall well-being and minimizing harm).
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| Spec | ||
|---|---|---|
| Input price | $0.14/M tokens | $0.4/M tokens |
| Output price | $0.28/M tokens | $2.4/M tokens |
| Context window | 1.0M tokens | 1.0M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Jul 2026 | Feb 2026 |
| At 10M a month | $1.40 | $4.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 12 Oct 2026.
DeepSeek V4 Flash 0731 is developed by DeepSeek while Qwen3.5 Plus 2026-02-15 is developed by Qwen. DeepSeek V4 Flash 0731 has a 1.0M token context window vs Qwen3.5 Plus 2026-02-15's 1.0M. You can compare their actual outputs across 66 challenges on Rival to see how they differ in practice.
It depends on your use case. DeepSeek V4 Flash 0731 and Qwen3.5 Plus 2026-02-15 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 66 challenges so you can judge which fits your needs best.
DeepSeek V4 Flash 0731 costs $0.14/M input tokens and Qwen3.5 Plus 2026-02-15 costs $0.4/M input tokens. DeepSeek V4 Flash 0731 is $0.26/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 V4 Flash 0731 and Qwen3.5 Plus 2026-02-15 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.