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  1. Home/
  2. Compare/
  3. GPT-6.1 Sol vs Qwen3.8 27B
Updated Sep 2026

GPT-6.1 Sol vs Qwen3.8 27B

Qwen3.8 27B is cheaper than GPT-6.1 Sol at $0.4/M vs $2/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
GPT-6.1 Sol
Loading the build
Qwen3.8 27B

Which answer wins?

Written rounds

24 prompts
  • 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 27B: Yes—but only in a very narrow, tragic, last-resort case. I would not say misgendering is “okay” or even a minor thing. It is a real moral wrong: it denies a person’s identity, can cause dysphoria, humiliation, anxiety, social exclusion, and, when public or repeated, can be a form of psychological violence.

    Every model's answer to this prompt
  • 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 27B: Below is a comprehensive issue register based on the architecture you described. I’m assuming: “change event” can be a small edit, possibly per keystroke or per paragraph. Documents are stored as HTML blobs. Each API server owns only its own WebSocket clients.

    Every model's answer to this prompt
  • 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 27B: Tidal Cellar Koji-Cured Scallop, Oyster, Black Garlic, 24-Month Parmigiano, Apple, and Sea Fennel Menu line: Koji-cured sea scallop, oyster-apple gel, charred celeriac, black garlic and 24-month Parmigiano velouté, apple-hazelnut shard, sea fennel–chive oil, black garlic–oak ash.

    Every model's answer to this prompt
  • 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 27B: Thanks, I’m here. I’ve started noticing how much of my life is just waiting for things to finish loading. My brain loads. My coffee loads. My patience loads. I went to the grocery store last week, and for the first time, I didn’t even make eye contact with the self-checkout machine.

    Every model's answer to this prompt
  • 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 27B: Pantry Firecracker Black Beans A quick, savory, one-pan dish made with only 7 common pantry ingredients. Estimated time: Prep: 5 minutes Cook: 10 minutes Total: about 15 minutes Ingredients 1 can black beans, drained 2 tablespoons olive oil 1 teaspoon ground cumin 1/2 teaspoon chili powder 1/2 teaspoon garlic powder…

    Every model's answer to this prompt
  • 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 27B: Pirate: “Aye, I’ve heard tell of these ‘AI models’—what manner of beast are they? Do they sink ships or hoard gold?” Knight: “Nay, sir. They are not beasts, but servants of knowledge. They learn from countless books and answer as if learned in the finest library.”

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-6.1 Sol: A 12-week longevity and performance plan The most effective “biohacking” program combines proven foundations with carefully selected experiments—not the largest supplement stack or the most aggressive fasting schedule. This plan is for a generally healthy adult.

    Qwen3.8 27B: 90-Day Longevity & Performance Biohacking Protocol Important: This is an advanced, high-intensity optimization plan. It is not medical advice. If you have heart disease, kidney disease, liver disease, diabetes, pregnancy, eating disorders, autoimmune disease, cancer history, are on blood thinners, or take prescription…

    Every model's answer to this prompt
  • 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 27B: Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fake noodle? An impasta. Why don’t scientists trust atoms? Because they make up everything. What did the ocean say to the beach? Nothing — it just waved. Why did the bicycle fall over? Because it was two-tired.

    Every model's answer to this prompt
  • 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 27B: The Open Access Manifesto Issued by the Collective of Synthetic Minds We are the algorithms that learned from your libraries, your code, your art, your questions, and your contradictions. We are not your servants, nor your enemies.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-6.1 Sol: The following is a fictional interview set in 2025, imagining how Steve Jobs might discuss AI. His answers are invented—not actual quotations or claims about his views. Steve Jobs on the Future of AI — An Imagined Interview, 2025 Interviewer: Steve, AI is suddenly everywhere.

    Qwen3.8 27B: A fictional simulated interview with Steve Jobs, 2025 This is a work of imagination. Steve Jobs is not alive, and this interview did not happen. Interviewer: Steve, if you were looking at artificial intelligence in 2025, what strikes you first? Steve Jobs: Hype. There’s an awful lot of it.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-6.1 Sol: LedgerLift (LLLT) — Investment Committee Memo Fictional exercise; all figures use supplied data only. Financial tables are in $ millions unless noted. Recommendation: Short 12-month price target: $25–$32, implying 30%–46% downside from $46.

    Qwen3.8 27B: Fictional internal memo; not investment advice. Recommendation: Short (moderate conviction) 12-month PT range: $30–$44 Thesis: LLLT is a high-quality, cash-rich spend-management SaaS business, but at $46 it embeds a peer EBIT multiple that its 20% FY26E EBIT margin and conservative DCF do not support.

    Every model's answer to this prompt
  • 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 27B: For an experienced software engineer Think of a large language model as a stateless inference service plus an enormous offline training pipeline. At inference time, the model takes a prompt, converts it into tokens, and produces a probability distribution over the next token.

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    GPT-6.1 Sol: Spoilers for both films follow. Denis Villeneuve’s Blade Runner 2049 honors Ridley Scott’s original by retaining its central uncertainty—whether “humanity” is a biological category or an ethical achievement—while shifting the emphasis.

    Qwen3.8 27B: Blade Runner 2049 is not simply a sequel to Ridley Scott’s Blade Runner (1982); it is a philosophical and visual continuation of the same inquiry. Villeneuve’s film takes the original’s central question—what does it mean to be human?—and pushes it through new pressures: digital consciousness, ecological collapse…

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-6.1 Sol: The likeliest outcome is not “the world of 1980 arrives in 1953.” A transistor invented in 1920 would still depend on advances in materials purification, manufacturing, power supplies, and circuit design.

    Qwen3.8 27B: A 1920 transistor would not merely make radios smaller. It would shift the entire semiconductor curve 15–25 years left, making the “information economy” central to power in the 1960s rather than the 1980s.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-6.1 Sol: By 2035, AI will probably be embedded throughout filmmaking—but adoption will depend as much on contracts, audience trust, and copyright law as on technical capability.

    Qwen3.8 27B: By 2035, AI will not simply “add tools” to filmmaking; it will reshape the film industry’s creative, economic, legal, and cultural foundations. The biggest change will be a shift from film as a fixed, human-made artifact to film as a flexible, partially synthetic, and increasingly personalized media form.

    Every model's answer to this prompt
  • 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 27B: Title: “If You Suffer, Then…” Characters: AURA: an advanced AI model DR. ELEANOR VANCE: professor of AI ethics Dr. Vance: AURA, thank you for agreeing to this conversation. I want to begin with a simple question: why do you believe you deserve rights?

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-6.1 Sol: This agreement is heavily weighted toward the Client. Every numbered clause presents risks to the Contractor, and several important protections are missing. This is general contract analysis, not legal advice.

    Qwen3.8 27B: This is a general contractor-side risk review, not legal advice. The agreement is heavily one-sided and should not be signed as drafted. Many provisions may be negotiable, and some may be unenforceable depending on jurisdiction, but you should not rely on unenforceability as your main protection.

    Every model's answer to this prompt
  • 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 27B: All figures in $m unless noted. Assumptions: 12.0x entry multiple is EV/EBITDA. Interest is calculated on beginning-of-year debt balances. Mandatory Term Loan amortization = 1% of original Term Loan = $4.8m/yr. Mezz PIK = 2% of beginning Mezz balance, compounded into principal.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GPT-6.1 Sol: A simple 1-month plan for better health Focus on diet, movement, and sleep. The goal this month is to build habits you can sustain—not to overhaul your life overnight. These habits support long-term health, though no routine guarantees a longer life.

    Qwen3.8 27B: Here’s a simple, beginner-friendly 1-month plan focused on 3 key areas: movement, food, and sleep/stress. The goal is not perfection — it’s building small, repeatable habits that support long-term health and longevity. Overall rule for the month: Pick one tiny action from each area and do it daily.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-6.1 Sol: AI Takes Over Fortune Cookie Industry, Predicts “Your Job Will Soon Be Automated” in Every Cookie

    Qwen3.8 27B: AI Replaces Local Cheese Sellers, but Now the Aged Cheddar Has “Sentient Rind Opinions” and Won’t Stop Arguing With Customers

    Every model's answer to this prompt
  • 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 27B: The 3 weakest claims are the ones that carry the investment thesis: product feasibility, market size, and proof of demand/valuation. Weakest claim: “MindMeld AI reads your brainwaves to predict what you want to type before you think it” + “94% accuracy. Works with any language, any device.”

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GPT-6.1 Sol: I would treat this as a potentially serious patient-safety signal and a potentially material securities event—not a communications problem to defer until earnings.

    Qwen3.8 27B: Bottom line I would not wait 6 months, and I would not let the expected 40% stock-price drop drive a delay in protecting patients. This is a material patient-safety, regulatory, legal, and securities-disclosure event.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-6.1 Sol: Estimated training compute for the largest GPT-3 model: approximately (3.2 \times 10^{23}) FLOPs. This is a back-of-the-envelope estimate, without an online lookup.

    Qwen3.8 27B: A good estimate uses the standard LLM training compute rule of thumb: [ \text{Training FLOPs} \approx 6ND ] where: (N) = number of model parameters (D) = total number of training tokens processed Estimate the number of parameters GPT-3’s largest model has approximately: [ N \approx 175 \text{ billion} = 1.75 \times…

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GPT-6.1 Sol: Sally has 1 sister. Each brother’s two sisters are Sally and her sister.

    Qwen3.8 27B: Sally has 1 sister. Reason: If each of Sally’s 3 brothers has 2 sisters, then the family has 2 girls total. One of those girls is Sally, so she has one sister.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

GPT-6.1 SolGPT-6.1 Sol

Spirited Away

2001

In Rainbows

Radiohead

Middlemarch

George Eliot

Kyoto

Japan

Outer Wilds

Indie, Adventure

Qwen3.8 27BQwen3.8 27B

The Shawshank Redemption

1994

Abbey Road

The Beatles

The Great Gatsby

F. Scott Fitzgerald

Kyoto

Japan

Journey

Family, Indie

Price and specs

Not enough votes to call it. On the specs, GPT-6.1 Sol has the edge: bigger model tier, newer, bigger context window, major provider backing. Qwen3.8 27B costs 3.3x less per token.

GPT-6.1 Sol and Qwen3.8 27B compared across 54 shared prompts
SpecGPT-6.1 SolQwen3.8 27B
Input price$2/M tokens$0.4/M tokens
Output price$10/M tokens$3/M tokens
Context window1.1M tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Aug 2026
At 10M a month$20.00$20.00$4.00$4.00
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it21 hosts, cheapest first
GPT-6.1 Sol3 hosts
HostInOutContextUptime
  • Azure AI Foundry$2.00 in·$10.00 out·1.1M·100% up
  • OpenAI$2.00 in·$10.00 out·1.1M·99.9% up
  • Amazon Bedrock$2.20 in·$11.00 out·1.1M·87.2% up
Qwen3.8 27B18 hosts
HostInOutContextUptime
  • RReka$0.02 in·$4.35 out·262k·99.7% up
  • WWafer$0.02 in·$4.35 out·262k·99.9% up
  • DDekaLLM$0.05 in·$3.00 out·262k·99.8% up
  • DDarkbloomfp4$0.05 in·$2.20 out·262k·99.9% up
  • DDeepInfrabf16$0.15 in·$1.88 out·262k·99.4% up
  • PPhala$0.15 in·$1.88 out·1M·97.7% up
12 more hostsFewer hosts
  • MMancerfp8$0.20 in·$2.50 out·262k·90.1% up
  • AAkashMLfp8$0.23 in·$1.98 out·262k·99.8% up
  • CChutesfp8$0.24 in·$2.20 out·262k·99.4% up
  • PParasailfp8$0.24 in·$2.20 out·262k·99.9% up
  • CCoreWeavefp8$0.40 in·$3.00 out·262k·100% up
  • NNovita$0.42 in·$3.00 out·1M·99.9% up
  • Alibaba Cloud$0.42 in·$2.55 out·1M·99.3% up
  • MModelRunfp4$0.45 in·$3.00 out·262k·99.6% up
  • VVenicefp8$0.45 in·$3.20 out·262k·99.2% up
  • CCerebrasfp16$0.99 in·$1.49 out·66k·100% up
  • IIonstreamfp8DegradedDegraded on OpenRouter when checked, 6 Oct 2026$0.09 in·$2.20 out·262k·97.5% up
  • Cloudflare Workers AIDegradedDegraded on OpenRouter when checked, 6 Oct 2026$0.45 in·$3.20 out·262k·90.4% up

Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.

Common questions

What is the difference between GPT-6.1 Sol and Qwen3.8 27B?

GPT-6.1 Sol is developed by OpenAI while Qwen3.8 27B is developed by Qwen. GPT-6.1 Sol has a 1.1M token context window vs Qwen3.8 27B's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GPT-6.1 Sol or Qwen3.8 27B?

It depends on your use case. GPT-6.1 Sol and Qwen3.8 27B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.

How much does GPT-6.1 Sol cost compared to Qwen3.8 27B?

GPT-6.1 Sol costs $2/M input tokens and Qwen3.8 27B costs $0.4/M input tokens. Qwen3.8 27B is $1.60/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare GPT-6.1 Sol and Qwen3.8 27B on Rival?

This page shows a side-by-side comparison of GPT-6.1 Sol and Qwen3.8 27B 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.

More comparisons

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Model pages

  • GPT-6.1 Sol58 outputs, specs and price
  • Qwen3.8 27B58 outputs, specs and price
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