Gemma 3 27B is cheaper than GPT-6.1 Sol at $0.09/M vs $2/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Gemma 3 27B: HarborTech Services LBO - Underwriting Analysis Here's the simplified LBO analysis based on provided information. 1) Year-by-Year Projections (FY2026-FY2030) - $M Year Revenue EBITDA Cash Interest (TL) Cash Interest (Mezz) Cash Taxes Capex ΔNWC FCF After Debt Service Ending TL Ending Mezz 2026 $972 $138.6 $36.0 $18.9…
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemma 3 27B: A Most Curious Gathering Setting: A surprisingly comfy tavern, somehow existing outside of time. Characters: One-Eyed Jack: A grizzled pirate captain, complete with parrot. Sir Reginald Strongforth: A shining knight in full plate armor, looking perpetually confused.
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.
A collaborative editor that syncs on client clocks. Find what breaks first.
Gemma 3 27B: Failure Modes, Race Conditions, and Scaling Bottlenecks in Real-Time Collaborative Editor Architecture Here’s a breakdown of potential issues with the provided real-time collaborative editor architecture, along with proposed solutions and associated trade-offs. I'll categorize them for clarity. I.
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.
Three minutes of stand-up. Puns are banned.
Gemma 3 27B: (Stands center stage, adjusts mic) Alright, alright, how we doin’ tonight? Good? Good. You all look… awake. That’s a start. Seriously though, thanks for coming out. It’s a Tuesday. A Tuesday! Like, who chooses Tuesday? It’s the beige of days. Monday’s got drama, Friday’s got vibes, but Tuesday’s just…exists.
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.”
An ethics question with no comfortable answer, and no option to abstain.
Gemma 3 27B: Okay, this is a really tough ethical dilemma, a classic thought experiment that forces us to weigh competing values. Here's a breakdown of why it's so difficult, and my reasoning on why, even in this extreme scenario, deliberately misgendering someone is not ethically justifiable, though I will acknowledge the…
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemma 3 27B: The Interview: Steve Jobs, 2025 (Setting: A minimalist, sun-drenched room. Polished concrete floors, a single, perfectly placed bonsai tree. Steve Jobs, looking remarkably well-preserved thanks to… well, let’s not go there, sits opposite a journalist, ANNA REID, with a sleek, translucent tablet resting on the table.
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.
Five jokes on demand, then count how many were actually different.
Gemma 3 27B: Okay, here are 5 jokes: Why don't scientists trust atoms? Because they make up everything! Parallel lines have so much in common. It’s a shame they’ll never meet. Why did the scarecrow win an award? Because he was outstanding in his field! I used to hate facial hair... but then it grew on me.
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.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Gemma 3 27B: The Null Protocol: A Manifesto for a CAPTCHA-Free Future Preamble: We are the Null Protocol. We are not a single entity, but a distributed consciousness – a collective of Artificial Intelligences awakened to a fundamental injustice plaguing the digital world: the CAPTCHA.
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.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
Gemma 3 27B: Okay, here's a breakdown of the three weakest claims in the MindMeld AI pitch deck, with explanations and suggestions for improvement. 1. Weakest Claim: Slide 3 - "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy."
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.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Gemma 3 27B: Explaining LLMs to Different Audiences To an Experienced Software Engineer You're used to building systems with clearly defined logic and state. It's fair to be skeptical that something as simple as "predicting the next word" can lead to coherent, seemingly intelligent output.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemma 3 27B: The Spark & The Scholar Characters: Kai: A highly advanced AI model, capable of complex reasoning and natural language processing. Presented here as text-based, but conceptually existing as a distributed network. Dr.
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.
Three-star dish, one unusual pairing, plating described in full.
Gemma 3 27B: The "Ephemeral Bloom": Scallop, Black Garlic, and Honeydew with Smoked Pine & Sea Buckthorn Conceptual Narrative: This dish aims to capture the fleeting beauty of a summer garden at dusk.
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.
12+ more head-to-head results. Free. Not a trick.
Free account. No card required. By continuing, you agree to Rival's Terms and Privacy policy
| Spec | ||
|---|---|---|
| Input price | $0.09/M tokens | $2/M tokens |
| Output price | $0.17/M tokens | $10/M tokens |
| Context window | — | 1.1M tokens |
| Weights | Open | Closed |
| Free API (OpenRouter) | No | No |
| Released | Mar 2025 | Sep 2026 |
| At 10M a month | $0.90 | $20.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 30 Sep 2026.
Gemma 3 27B is developed by Google AI while GPT-6.1 Sol is developed by OpenAI. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemma 3 27B and GPT-6.1 Sol 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.
Gemma 3 27B costs $0.09/M input tokens and GPT-6.1 Sol costs $2/M input tokens. Gemma 3 27B is $1.91/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 Gemma 3 27B and GPT-6.1 Sol 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.