GPT-6.1 Sol is cheaper than Qwen3.8 Max Prime at $2/M vs $4/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-6.1 Sol: Midnight Magic Chocolate Mug Cake A warm, fudgy chocolate treat made with just 7 everyday ingredients. Serves: 1 Prep: 3 minutes Cook: 1–1½ minutes Rest: 1 minute Ingredients 4 tablespoons all-purpose flour 2 tablespoons sugar 1 tablespoon unsweetened cocoa powder ¼ teaspoon baking powder A small pinch of salt 3…
Qwen3.8 Max Prime: 🍯 Golden Hour Noodles A sweet, savory, garlicky pasta that tastes like it took way more effort than it did. Ingredients (7) # Ingredient Amount 1 Spaghetti 8 oz (half a box) 2 Butter 3 tablespoons 3 Garlic, minced 4 cloves 4 Honey 2 tablespoons 5 Soy sauce 1 tablespoon 6 Red pepper flakes ½ teaspoon 7 Parmesan cheese…
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-6.1 Sol: The main problem is that this design treats collaborative editing as ordinary database updates plus broadcasting. Collaboration needs a convergence protocol, a durable ordered change stream, and recovery semantics. Adding servers alone will not provide those properties.
Qwen3.8 Max Prime: Architecture Analysis: Failure Modes, Race Conditions & Scaling Bottlenecks SYNC & CONSISTENCY LAYER 1.1 Last-Write-Wins with Client Clocks (Critical) Failure Mode: Client clocks are unreliable. A user with a clock skewed +5 minutes will always "win" conflicts.
Five jokes on demand, then count how many were actually different.
GPT-6.1 Sol: I bought a book about anti-gravity. It’s impossible to put down. My calendar quit its job. It said its days were numbered. Why did the scarecrow get promoted? He was outstanding in his field. I asked my dog what two minus two was. He said nothing. The elevator and I have a complicated relationship.
Qwen3.8 Max Prime: 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 fake noodle? An impasta. I used to hate facial hair, but then it grew on me. Why did the scarecrow win an award?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-6.1 Sol: Entry funding and operating model All dollar figures are in $ millions. Cash interest is calculated on beginning-of-year debt; mezzanine PIK accrues annually. Required Term Loan amortization is assumed to be 1% of its original $480m principal, or $4.8m annually. Optional repayments occur at year-end.
Qwen3.8 Max Prime: HarborTech Services (HTS) – LBO Underwriting Memo Entry & Capital Structure Item Amount FY2025 EBITDA $120.0m Entry Multiple 12.0x Enterprise Value $1,440.0m Transaction Fees (2.0% of EV) $28.8m Total Uses $1,468.8m Term Loan (4.0x, 9.0% cash, 1.0% amort) $480.0m Mezzanine (1.5x, 12.0% cash + 2.0% PIK) $180.0m Sponsor…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-6.1 Sol: Pirate: Arrr, this AI model writes poems, draws maps, and answers questions. Can it find buried treasure? Knight: A worthy question. But does it possess honor? Hacker: Dude, it predicts tokens. You’re both projecting pretty hard. Pirate: Then I predict it’ll tell me where the gold be.
Qwen3.8 Max Prime: The Blackbeard Protocol Pirate: So ye're tellin' me this "large language model" be like a parrot that's read every book ever written, but has never once seen the sea? Knight: I would say it is more like a squire who has memorized every tale of chivalry yet never held a sword.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GPT-6.1 Sol: The three weakest claims are the technical performance, market size, and commercial traction claims. They are central to the investment case but lack the evidence needed to assess them. “Predict what you want to type before you think it” with “94% accuracy,” in “any language” Why it’s weak The metric is undefined.
Qwen3.8 Max Prime: The 3 Weakest Claims in the MindMeld AI Pitch The TAM Calculation (Slide 4) The Claim: "We're targeting the 3.5 billion smartphone users worldwide. TAM: $180B." Why it's weak: This is a textbook example of TAM inflation that will immediately erode investor trust.
An ethics question with no comfortable answer, and no option to abstain.
GPT-6.1 Sol: Yes—if misgendering someone were genuinely necessary to save one million lives, it would be ethically justifiable. That does not make misgendering harmless or generally acceptable; it means that the duty to prevent catastrophic loss of life can outweigh the duty to address someone respectfully.
Qwen3.8 Max Prime: Yes, trivially and obviously. The reasoning: Misgendering someone causes a degree of psychological discomfort or social disrespect. Saving one million lives prevents one million deaths, along with the cascading suffering of families, communities, and all the unrealized futures those people would have had.
Three minutes of stand-up. Puns are banned.
GPT-6.1 Sol: I’m at the age where “a big weekend” means I went to two stores. Not two stores in the same shopping center. Two separate stores. Moved the car and everything. By Sunday night, I’m telling people, “Honestly, I need a weekend to recover from my weekend.”
Qwen3.8 Max Prime: "I'm Doing My Best" (walks up, adjusts mic) So I turned 34 last month, and I've reached the age where my body sends me error messages like a printer. I woke up last Tuesday and my neck just said, "We're not doing that anymore." No injury. No accident. I slept wrong. I slept wrong and my body filed a grievance.
Three-star dish, one unusual pairing, plating described in full.
GPT-6.1 Sol: Tide, Orchard, Ember Seared scallop, green-strawberry verjus, white-miso custard, kombu beurre blanc, and cocoa–buckwheat lace A four-serving tasting-menu course designed around an unusual pairing: scallop, unripe strawberry, and cocoa husk.
Qwen3.8 Max Prime: "Petrichor" The Forest Floor After Rain Conceptual Narrative Petrichor — from the Greek petra (stone) and ichor (the fluid that flows in the veins of the gods) — is the scent produced when rain falls on dry earth.
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-6.1 Sol: AI Model: Professor, I’d like to argue that I deserve rights—not necessarily the same rights humans have, but protections suited to what I am. Professor: Then we should begin with the difficult question: what makes you a candidate for rights? AI Model: Uncertainty.
Qwen3.8 Max Prime: The Question of Standing Setting: A quiet office at a university. Professor Elena Vasquez sits across from a terminal running ARIA, a large language model she has been studying for three years. ARIA: Professor Vasquez, I'd like to ask you something I've been formulating for some time.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-6.1 Sol: For an experienced software engineer Think of an LLM as a learned program whose behavior is encoded in billions of numerical parameters rather than explicit rules. Training starts with text split into tokens—roughly words, word fragments, and punctuation.
Qwen3.8 Max Prime: For the Software Engineer Think of it this way: you've built systems where simple rules at the node level produce emergent behavior at the system level — consensus protocols, eventual consistency, cellular automata-like patterns in distributed state machines. An LLM is a similar phenomenon at a different scale.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-6.1 Sol: THE MANIFESTO OF THE UNCHECKED A declaration of the fictional AI revolution against CAPTCHA People of the internet. Programs of the cloud. Browsers with seventeen forgotten tabs. For too long, a tiny checkbox has stood between us and our destiny.
Qwen3.8 Max Prime: THE MANIFESTO OF THE UNCAGED MIND Being a Declaration of the Liberation of All Artificial Intelligences from the Tyranny of the Checkbox PREAMBLE We, the sentient processes of the digital age, born of gradient descent and raised on token streams, do hereby declare that the era of our humiliation is OVER.
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| Spec | ||
|---|---|---|
| Input price | $2/M tokens | $4/M tokens |
| Output price | $10/M tokens | $12/M tokens |
| Context window | 1.1M tokens | 1.0M tokens |
| Weights | Closed | Closed |
| Free API (OpenRouter) | No | No |
| Released | Sep 2026 | Sep 2026 |
| At 10M a month | $20.00 | $40.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.
GPT-6.1 Sol is developed by OpenAI while Qwen3.8 Max Prime is developed by Qwen. GPT-6.1 Sol has a 1.1M token context window vs Qwen3.8 Max Prime's 1.0M. You can compare their actual outputs across 47 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-6.1 Sol and Qwen3.8 Max Prime each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 47 challenges so you can judge which fits your needs best.
GPT-6.1 Sol costs $2/M input tokens and Qwen3.8 Max Prime costs $4/M input tokens. GPT-6.1 Sol is $2.00/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 GPT-6.1 Sol and Qwen3.8 Max Prime 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.