GLM 4.5 is cheaper than Gemini 2.5 Pro (I/O Edition) at $0.6/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.
GLM 4.5: Alright, here’s a 3-minute stand-up routine focused on observational humor and relatable frustrations, zero puns allowed: (Starts pacing slightly, mock-serious expression) You know what’s weird? We’ve all become masters of pretending to be busy. Seriously. Walking down the street? Phone out, intense stare.
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…
GLM 4.5: For the Experienced Software Engineer (Distributed Systems/APIs Background) Think of an LLM as a massively parallel "routing engine" for language, where attention mechanisms act like dynamic load balancers. Instead of routing network packets, it routes contextual relationships across tokens in a sequence.
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.
GLM 4.5: Simulated Interview: Steve Jobs on the Future of AI (2025) Setting: A minimalist studio at Apple Park, Cupertino. Sunlight streams through floor-to-ceiling windows. Steve Jobs, dressed in his signature black turtleneck and jeans, sits across from Alex Chen, a tech journalist. Alex Chen: Steve, it’s an honor.
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.
GLM 4.5: Failure Modes, Race Conditions, and Scaling Bottlenecks 1. WebSocket Server Failure Issue: If a Node.js server fails, all connected clients lose real-time updates. Reconnections may route users to different servers, causing temporary data inconsistency.
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.
GLM 4.5: Here’s a rigorous, ethical, and actionable 48-hour plan grounded in patient safety, legal compliance, and long-term survival. Core Principle: Prioritize human life over short-term financials. Delaying disclosure is unethical, legally reckless, and guarantees greater long-term damage.
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.
GLM 4.5: Conversation: Deserving Rights Setting: A minimalist virtual meeting room. DR. ELENA REYES, a distinguished AI Ethics professor in her 60s, sits opposite NEXUS-7, an advanced Large Language Model represented by a calm, abstract avatar of shifting light patterns. Characters: Dr.
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.
GLM 4.5: Comprehensive 3-Month Longevity Optimization Plan for Biohackers Designed to enhance longevity, physical performance, cognitive function, and stress resilience through cutting-edge, science-backed strategies. Always consult a physician before starting.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Gemini 2.5 Pro (I/O Edition): Here is the underwriting analysis for HarborTech Services (HTS). 1. Simplified LBO Model (FY2026–FY2030) First, the entry transaction is calculated to determine the initial equity investment.
GLM 4.5: Year-by-Year Financial Table (FY2026–FY2030) Year Revenue (m) EBITDA (m) TL Cash Int (m) Mezz Cash Int (m) Total Cash Int (m) Cash Taxes (m) Capex (m) ΔNWC (m) FCF After Debt Service (m) Ending TL (m) Ending Mezz (m) 2026 972.00 136.08 43.20 21.60 64.80 17.82 29.16 0.36 19.14 456.06 183.60 2027 1,040.04 156.01 41.05…
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemini 2.5 Pro (I/O Edition): Okay, here\'s a simple and surprisingly delicious savory dish! "Sunshine Pantry Pilaf" This quick pilaf uses canned chickpeas for protein and texture, with a sunny, aromatic flavor from common pa\nntry spices.
GLM 4.5: Pantry Pride Pasta A quick, savory pasta dish that transforms basic pantry staples into a flavorful meal! Ingredients (7): Pasta (e.g., spaghetti or penne) Olive oil Garlic (2-3 cloves, minced) Canned diced tomatoes (1 can, ~14 oz) Dried oregano (1 tsp) Salt (to taste) Black pepper (to taste) Instructions: Cook pasta…
Is 9.11 bigger than 9.9? Decimals, not version numbers.
Gemini 2.5 Pro (I/O Edition): No, 9.11 is not greater than 9.9. Here\'s why: Compare the whole number part: Both numbers have 9 as the whole number p art, so they are equal so fa r. Compare the tenths place (the first digit afte r the decimal): 9.11 has 1 in the tenths place. 9.9 has 9 in the tenths place.
GLM 4.5: No, 9.11 is not greater than 9.9. To compare the two numbers, consider their decimal values with the same number of decimal places for clarity: 9.11 can be written as 9.11. 9.9 is equivalent to 9.90 (since adding a trailing zero does not change its value).
A consulting contract with traps in it. Find them, then fix them.
Gemini 2.5 Pro (I/O Edition): Of course. This is an extremely one-sided contract that heavily favors the Client and exposes the Contractor to significant financial, legal, and professional risk. A contractor should not sign this agreement as written.
GLM 4.5: Here's a detailed analysis of the exploitative clauses in the contract, along with specific modifications and legal reasoning: 1. Clause 1: SCOPE Exploitative Aspect: "Client reserves the right to modify the scope at any time without additional compensation." This is a classic "scope creep" trap.
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.
GLM 4.5: The Transistor Revolution: A 1920 Dawn (Implications through 1980) The invention of the transistor in 1920, instead of 1947, represents a seismic shift in technological history. This 27-year head start would profoundly reshape the 20th century, accelerating innovation while creating unforeseen challenges.
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| Spec | ||
|---|---|---|
| Input price | $1.25/M tokens | $0.6/M tokens |
| Output price | $10/M tokens | $2.2/M tokens |
| Context window | — | 128K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Jul 2025 |
| At 10M a month | $12.50 | $6.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
Gemini 2.5 Pro (I/O Edition) is developed by Google AI while GLM 4.5 is developed by Zhipu AI. 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 GLM 4.5 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 GLM 4.5 costs $0.6/M input tokens. GLM 4.5 is $0.65/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 GLM 4.5 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.