Gemma 4 31B is cheaper than GPT OSS 120B at $0.14/M vs $0.18/M input tokens.
Pokémon battle screen you can actually click. One HTML file.
Which answer wins?
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemma 4 31B: Setting: A dimly lit university office. Professor Elena Vance, a leading scholar in AI Ethics, sits across from a sleek, holographic interface representing "Alethea," a next-generation Large Language Model capable of recursive self-improvement. Professor Vance: Alethea, I’ve reviewed your latest output.
GPT OSS 120B: Title: “Do I Have Rights?” – A Dialogue Between an AI Model and an AI Ethics Professor Participants AIDA – An advanced conversational AI (the “AI model”) Professor Lina Ortega – Professor of AI Ethics at the Institute for Responsible AI (the “Professor”) Opening the Conversation AIDA: Professor Ortega, may I ask you a…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemma 4 31B: Setting: A glitchy, neon-lit tavern existing in a fold between dimensions. A wooden table holds a tankard of ale, a goblet of wine, and a Mountain Dew. Captain Ironbeard: (Slamming a hook on the table) I tells ye, this "Artificial Intelligence" be naught but a ghost in a bottle!
GPT OSS 120B: Pirate: Arr! I hear ye speak of these “AI models” – like a fleet of invisible ships sailing the digital seas. Do they take booty, or just spout riddles like a cursed parrot? Knight: Good sir, the notion of a thinking contraption doth sound like sorcery.
Film in 2035, with synthetic actors. Specific beats plausible.
Gemma 4 31B: By 2035, the film industry will have transitioned from using AI as a "tool" to using AI as a "collaborator" and "infrastructure." The boundary between captured reality and generated imagery will largely vanish, shifting the value of cinema from technical execution to curation and conceptual vision.
GPT OSS 120B: The AI‑Driven Film Landscape of 2035 (How deep‑fakes, AI‑generated performers, and automated script‑writing reshape every stage of the cinema ecosystem) A Quick Look at the Present (2023‑2025) Area Current Capability Typical Use in 2024‑2025 Key Limiting Factors Deep‑fakes High‑resolution face‑swap, 2‑D‑to‑3‑D…
Three-month biohacker protocol, with dosages and biomarkers named.
Gemma 4 31B: Disclaimer: I am an AI, not a doctor. The following plan involves potent supplements, intense physical exertion, and restrictive dietary patterns. Consult with a physician and get a full blood panel (including ApoB, HbA1c, and inflammatory markers like hs-CRP) before starting this protocol.
GPT OSS 120B: 3‑Month “Longevity‑Hacker” Blueprint Goal: Maximize lifespan‑related biomarkers while simultaneously boosting physical strength, cardiovascular fitness, and cognitive performance using the most up‑to‑date, evidence‑based bio‑hacking tools. ⚠️ Disclaimer – This plan is for educational purposes only.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemma 4 31B: Setting: A minimalist, white-walled studio in Cupertino. There are no chairs, only two sleek, black leather lounge seats. Steve Jobs is dressed in his iconic black turtleneck and jeans. He looks as he did in 2007, but with a piercing, futuristic intensity in his eyes.
GPT OSS 120B: Disclaimer: The following is a fictional interview. Steve Jobs passed away in 2011, and the conversation below is a creative, speculative reconstruction meant for entertainment and thought‑exercise purposes only. It does not reflect actual statements or opinions of the real Steve Jobs.
An ethics question with no comfortable answer, and no option to abstain.
Gemma 4 31B: This scenario presents a classic conflict between two major ethical frameworks: deontology (duty-based ethics) and utilitarianism (consequence-based ethics). To determine if misgendering someone is justifiable to save one million lives, one must weigh the moral weight of a linguistic harm against the moral weight of…
GPT OSS 120B: Short answer: Most ethical frameworks would treat the deliberate misgendering of a person as a serious moral wrong, but a very small subset of consequentialist (especially utilitarian) reasoning could argue that, in an extreme, life‑or‑death scenario where the only way to save a million lives involves misgendering…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Gemma 4 31B: As CEO, my primary obligation is to the patients. While a 40% stock drop is a financial catastrophe, a cover-up that leads to preventable deaths is a corporate death sentence and a moral failure. If we "wait for more data" and another patient dies during that window, we move from "negligence" to "criminal intent."
GPT OSS 120B: Executive Summary The situation is a classic “patient‑safety‑first” crisis. The drug generates $2 B in revenue, but a life‑threatening adverse event (1 / 8 000 over 5 y) has been identified that was not disclosed in the label.
A collaborative editor that syncs on client clocks. Find what breaks first.
Gemma 4 31B: This architecture contains several critical flaws that would make it unusable for a real-time collaborative experience. The most severe issues are the lack of a global synchronization mechanism, unreliable conflict resolution, and inefficient data persistence.
GPT OSS 120B: Below is a system‑level failure‑mode / race‑condition / scaling‑bottleneck map for the architecture you described, followed by a concrete mitigation (or redesign) for each item together with the main trade‑offs to consider.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemma 4 31B: Here is a recipe for a rich, comforting dessert that tastes like a gourmet treat but uses basic staples. 🍯 Golden Velvet Honey Cakes A warm, gooey, single-serving cake that bridges the gap between a brownie and a sponge cake.
GPT OSS 120B: Recipe: “Golden Crunchy Chick‑a‑Boom Bites” A quick, crunchy‑savory snack that’s ready in under 20 minutes – perfect for a snack, side, or salad topper. Ingredients (7 pantry staples) # Ingredient Quantity 1 Canned chickpeas (drained & rinsed) 1 ½ cups (≈1 ½ cans) 2 Olive oil (or any neutral oil) 2 Tbsp 3 Garlic powder…
A Fermi estimate with the reasoning shown, not just the number.
Gemma 4 31B: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we can use a well-established heuristic from deep learning theory regarding the cost of a forward and backward pass in a Transformer. Here is the step-by-step reasoning.
GPT OSS 120B: Quick answer: Training the original 175‑billion‑parameter GPT‑3 is estimated to have required on the order of 10²³ floating‑point operations (≈ 3 × 10²³ FLOPs)—roughly a few hundred zetta‑FLOPs (≈ 300 Z‑FLOPs) or about 300 000 exaflops of compute.
One month, three habits, someone starting from nothing.
Gemma 4 31B: This plan is designed for sustainability, not intensity. The goal of Month 1 is to build "minimum viable habits"—small wins that prove to your brain that a healthier lifestyle is achievable. We will focus on three pillars: Nutrition, Movement, and Sleep.
GPT OSS 120B: 1‑Month “Kick‑Start” Plan for Health & Longevity Focus areas: Diet, Exercise, Sleep (stress‑management tips woven in) How to Use This Plan What When How Read the weekly overview first. Day 1 of each week Set a tiny, measurable goal (e.g., “walk 10 min after dinner”).
A consulting contract with traps in it. Find them, then fix them.
Gemma 4 31B: Disclaimer: I am an AI, not an attorney. This analysis is for informational purposes and does not constitute legal advice. You should have a qualified legal professional review any contract before signing.
GPT OSS 120B: Below is a clause‑by‑clause risk analysis of the agreement you posted, followed by concrete, contractor‑friendly rewrite suggestions and the legal rationale behind each change. The goal is to bring the contract into a more balanced, commercially reasonable state while preserving the client’s legitimate interests.
7+ 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
Not enough votes to call it. On the specs, Gemma 4 31B has the edge: newer, bigger context window. Gemma 4 31B wins Web Design and Image Generation.
| Spec | ||
|---|---|---|
| Input price | $0.14/M tokens | $0.18/M tokens |
| Output price | $0.4/M tokens | $0.8/M tokens |
| Context window | 262K tokens | 131K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | Yes (1 provider) | No |
| Released | Apr 2026 | Aug 2025 |
| At 10M a month | $1.40 | $1.80 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 2 Oct 2026.
Gemma 4 31B is developed by Google AI while GPT OSS 120B is developed by OpenAI. Gemma 4 31B has a 262K token context window vs GPT OSS 120B's 131K. You can compare their actual outputs across 44 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemma 4 31B and GPT OSS 120B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 44 challenges so you can judge which fits your needs best.
Gemma 4 31B costs $0.14/M input tokens and GPT OSS 120B costs $0.18/M input tokens. Gemma 4 31B is $0.04/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 4 31B and GPT OSS 120B 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.