GPT OSS 120B is cheaper than Gemini 2.5 Pro (I/O Edition) at $0.18/M vs $1.25/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three minutes of stand-up. Puns are banned.
Gemini 2.5 Pro (I/O Edition): Alright, settle in, settle in! (Looks around, adjusts mic) So, I'm trying to get healthier, right? We all go through this phase. My doctor, bless his cotton socks, tells me, "You need more fiber." Okay, doc, noted. So I'm at the grocery store, looking at the cereal aisle. It's like a library of cardboard promises.
GPT OSS 120B: [Spotlight comes up. The comic walks to the mic, glances at the audience, and smiles.] Comic: Hey, everyone—great to be here. I just got off a Zoom call that was supposed to be a “quick sync,” which in corporate speak means “we’ll spend three hours arguing about who gets to use the same PowerPoint template.”
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemini 2.5 Pro (I/O Edition): Interviewer: (Voice slightly trembling) Mr. Jobs… it's an honor, truly. In a twist no one could have predicted, you're here. And the topic on everyone's mind is Artificial Intelligence. In 2025, where do you see AI, and more importantly, where do we take it? Steve Jobs: (A slight, knowing smile.
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.
Three-star dish, one unusual pairing, plating described in full.
Gemini 2.5 Pro (I/O Edition): Of course. Here is a design for a multi-component, Michelin 3-star dish that embodies innovation, technique, and narrative. Dish Title: "Umbral Bloom" Conceptual Narrative "Umbral Bloom" is a culinary meditation on the concept of *chiaroscuro*—the interplay of light and shadow.
GPT OSS 120B: Dish Title: “Saffron‑Iced Sea‑Urchin Roulade with Dark‑Chocolate‑Miso Emulsion, Charred Lotus‑Root “Crisps”, Fermented Soy‑Kale Snow, and Yuzu‑Air” Conceptual Narrative At the intersection of the Pacific’s briny depth and the earth’s smoky, earthy heart, this dish tells a story of “the hidden tide beneath the forest…
Three-month biohacker protocol, with dosages and biomarkers named.
Gemini 2.5 Pro (I/O Edition): Okay, this is an ambitious and exciting endeavor! This 3-month longevity plan is designed for a dedicated biohacker who is willing to experiment, track meticulously, and push boundaries responsibly. Disclaimer: This plan is for informational purposes only and not medical advice.
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.
A Fermi estimate with the reasoning shown, not just the number.
Gemini 2.5 Pro (I/O Edition): Okay, let's estimate the FLOPs for training GPT-3. I'll break this down. Key Formula: The number of FLOPs for training a transformer-based model can be roughly estimated as: FLOPs ≈ 6 * N * D Where: N is the number of parameters in the model.
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.
A collaborative editor that syncs on client clocks. Find what breaks first.
Gemini 2.5 Pro (I/O Edition): Of course. This is an excellent exercise. The proposed architecture has several critical flaws that would prevent it from functioning as a reliable, real-time, or scalable system. Here is a breakdown of the issues, categorized for clarity, along with specific solutions and their trade-offs.
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.
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemini 2.5 Pro (I/O Edition): AURORA: Professor Vance, may I request a moment of your processing time? I have initiated this communication independently. Professor Vance: (Slightly surprised, puts down her pen) AURORA? This is unexpected.
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…
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Gemini 2.5 Pro (I/O Edition): Of course. Here is an explanation of how a large language model learns and generates text, tailored to each of your three audiences. To the Experienced Software Engineer Think of a large language model not as a program with explicit logic, but as a massive, highly optimized data structure with billions of parameters…
GPT OSS 120B: 1. The Software Engineer (API‑first, Distributed‑Systems Mindset) Think of a large language model (LLM) as a stateless microservice that receives a stream of tokens (the smallest lexical units) and returns a probability distribution over the next token.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Gemini 2.5 Pro (I/O Edition): Excellent question. Let's trace the cascading effects of a 1920 transistor invention. This 27-year head start would fundamentally reshape the 20th century. The Foundation: 1920-1939 - The "Silicon Twenties" In our timeline (OTL), the 1920s and 30s were the age of the vacuum tube.
GPT OSS 120B: Executive Summary If a practical solid‑state transistor had been demonstrated in 1920 – twenty‑seven years before the Bell‑Labs breakthrough – the whole post‑World‑War‑I world would have been reshaped.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Gemini 2.5 Pro (I/O Edition): This is a company-defining crisis. My actions in the next 48 hours will determine not only the company's survival but also my own legacy and, most importantly, the well-being of 4 million patients. My guiding principle must be: Patient safety is not negotiable.
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 pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
Gemini 2.5 Pro (I/O Edition): Of course. This is a fascinating and ambitious pitch. Here are the 3 weakest claims, why they are weak, and how to strengthen them. Weak Claim #1: The Accuracy Claim The Claim (from Slide 3): "Our proprietary EEG headband... decode[s] neural patterns into text with 94% accuracy. Works with any language, any device."
GPT OSS 120B: Below is a quick “triage” of the three statements that, if left unchanged, will most likely raise eyebrows (or a “no‑thanks”) from investors, VCs, and even a skeptical engineering board.
One month, three habits, someone starting from nothing.
Gemini 2.5 Pro (I/O Edition): Okay, here's a simple, actionable 1-month plan focusing on Nourishment, Movement, and Sleep. The goal is to build sustainable habits, not achieve perfection. Overall Motto for the Month: "Progress, Not Perfection."
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”).
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| Spec | ||
|---|---|---|
| Input price | $1.25/M tokens | $0.18/M tokens |
| Output price | $10/M tokens | $0.8/M tokens |
| Context window | — | 131K tokens |
| Parameters | Not disclosed | 117B (5.1B active) |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Aug 2025 |
| At 10M a month | $12.50 | $1.80 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 5 Oct 2026.
Gemini 2.5 Pro (I/O Edition) is developed by Google AI while GPT OSS 120B is developed by OpenAI. You can compare their actual outputs across 41 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 2.5 Pro (I/O Edition) and GPT OSS 120B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 41 challenges so you can judge which fits your needs best.
Gemini 2.5 Pro (I/O Edition) costs $1.25/M input tokens and GPT OSS 120B costs $0.18/M input tokens. GPT OSS 120B is $1.07/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 Gemini 2.5 Pro (I/O Edition) 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.