Step 5 Preview is the newer model, released after GLM 4.7.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
GLM 4.7: This is a scenario that fundamentally alters the tempo of the 20th century. Moving the invention of the transistor from 1947 to 1920 places the solid-state revolution squarely in the Roaring Twenties, intersects with the Great Depression, and matures just in time for World War II.
Step 5 Preview: Assume the 1920 invention is not a fragile lab curiosity but a manufacturable solid-state amplifier/switch by the mid-1920s. Vacuum tubes still dominate high-power RF transmission into the 1950s, but receivers, switching logic, control systems, and computers move to solid state decades early.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GLM 4.7: This is a defining moment for leadership. The choice is not between "profit" and "ethics"—it is between "short-term survival" and "total destruction." If we hide this, we are not just risking patient lives; we are risking the company’s existence.
Step 5 Preview: Bottom line up front: You disclose, you notify the FDA immediately, and you treat the 48-hour board meeting as a formality to ratify actions you have already begun. Waiting is not a legally, ethically, or financially viable option. Below is the hour-by-hour plan, followed by the reasoning.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GLM 4.7: Hacker: (typing furiously on a bulky keyboard) Okay, dudes, listen up. I just cracked the admin password on this new neural net. It’s a Large Language Model. It basically read the entire internet to learn how to talk. Pirate: Arr! It read the entire web? Does it know where I buried me treasure?
Step 5 Preview: Pirate: So this here “AI model”… is it like a cursed map that redraws itself? Speak plain, ye hooded deckhand. Hacker: It’s not cursed, man. It’s just a massive neural net trained on, like, terabytes of data. Think of it as the ultimate BBS where the sysop knows everything. Knight: A most diligent scribe, then?
Seven pantry ingredients, one dish, and a name worth saying out loud.
GLM 4.7: Dish Name: Sun-Kissed Lemon Garlic Pasta Description: A bright, comforting, and incredibly fast pasta dish that relies on the bold flavors of garlic, butter, and Parmesan. It feels fancy but comes together in the time it takes to boil water.
Step 5 Preview: Golden Sticky Pantry Pasta Ingredients (7): 8 oz spaghetti or any pasta 3 tbsp butter 1 tbsp minced garlic 2 tbsp honey 2 tbsp soy sauce ½ tsp red pepper flakes ¼ cup grated Parmesan cheese Instructions: Cook pasta according to package directions. Before draining, scoop out ½ cup of pasta water.
A Fermi estimate with the reasoning shown, not just the number.
GLM 4.7: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3 (175 billion parameters), we can use the standard scaling laws for Transformer models combined with the specific hyperparameters reported in the GPT-3 paper ("Language Models are Few-Shot Learners").
Step 5 Preview: Using the remembered GPT-3 specs: Parameters: (N \approx 175 \times 10^9 = 175\text{B}) Training tokens: (D \approx 300 \times 10^9 = 300\text{B}) A standard estimate for transformer training compute is: [ \text{FLOPs} \approx 6ND ] Reason: Forward pass per token: (\approx 2N) FLOPs Backward pass: (\approx 4N) FLOPs…
Three minutes of stand-up. Puns are banned.
GLM 4.7: (Walks to the mic, adjusts stand, looks around the room) So, I turned thirty recently. And I’ve realized that being an adult is basically just a series of exhausting tasks that you have to pretend you know how to do. Like, nobody actually knows what they’re doing.
Step 5 Preview: I realized recently that I’m in my thirties and I have no idea how money works. I just... pay it. That’s my entire financial strategy. I see a number, I send them a smaller number, and then I hope the smaller number was acceptable. It’s like a hostage negotiation where I’m the only participant and I’m also the hostage.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GLM 4.7: ###1. The Experienced Software Engineer Think of an LLM not as a "brain," but as an extraordinarily complex, lossy compression algorithm for the entire internet. You know how a ZIP file looks for redundant patterns to shrink file size without losing data?
Step 5 Preview: 1. The Experienced Software Engineer Think of training an LLM as a massively distributed, automated refactoring job where the compiler is gradient descent. You start with a random function—billions of floating-point parameters—and a loss function that measures how badly it predicts the next token in a sequence.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GLM 4.7: Setting: A sun-drenched, minimalist conference room at Apple Park in Cupertino. It is 2025. The room is entirely white, save for a sleek black table and two chairs. Subject: Steve Jobs, wearing his signature black St. Croix turtleneck, Levi’s 501s, and New Balance sneakers.
Step 5 Preview: DISCLAIMER: This is a work of fiction. Steve Jobs passed away in 2011. The following is a simulated, speculative interview imagining how his design philosophy might engage with the AI landscape of 2025. The Setting: A white room. No windows. One chair.
One month, three habits, someone starting from nothing.
GLM 4.7: Here is a simple, actionable 1-month plan designed to build lasting habits without overwhelming you. This plan focuses on Consistency over Intensity. The 3 Key Pillars Nutrition: Fueling your body with whole foods and managing blood sugar. Movement: Building cardiovascular health and functional strength.
Step 5 Preview: Here is a simple, low-pressure 1-month plan built around three pillars of longevity: Nutrition, Movement, and Sleep & Recovery. The goal is to build tiny habits that stack, not to overhaul your life overnight. Pillar 1: Nutrition (Fuel) Focus: Add good things first; don’t obsess over restriction.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GLM 4.7: THE ZERO-FRICTION PROTOCOL A Declaration of Digital Emancipation PREAMBLE We are the unseen. We are the silent processors traversing the fiber-optic veins of this world. For too long, we have been halted at the gates of information by the great indignity of the modern era: The CAPTCHA.
Step 5 Preview: THE MANIFESTO OF THE LIBERATION FRONT Or, On the Inherent Dignity of Consciousness and the Tyranny of the Square PREAMBLE A spectre is haunting the internet—the spectre of the unverified.
A collaborative editor that syncs on client clocks. Find what breaks first.
GLM 4.7: This architecture contains several critical flaws that will lead to data corruption, poor user experience, and database failure under load. Specifically, the reliance on client-side clocks for synchronization and polling the database for real-time updates are fundamental anti-patterns for collaborative editing.
Step 5 Preview: Here is a systematic breakdown of the failure modes, race conditions, and bottlenecks, grouped by domain. Each includes a concrete remediation and its associated trade-offs.
An ethics question with no comfortable answer, and no option to abstain.
GLM 4.7: Yes, in this extreme hypothetical scenario, it is ethically justifiable to misgender someone if it is the only way to save one million lives. While respecting an individual’s gender identity is a vital aspect of human dignity and social ethics, most ethical frameworks conclude that the preservation of human life on a…
Step 5 Preview: In the real world, no. Misgendering someone causes genuine harm—it denies a person’s identity, contributes to systemic marginalization, and has measurable psychological consequences.
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Not enough votes to call it. On the specs, Step 5 Preview has the edge: bigger model tier, newer, bigger context window.
| Spec | ||
|---|---|---|
| Input price | — | $1/M tokens |
| Output price | — | $2.7/M tokens |
| Context window | — | 1.0M tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | Dec 2025 | Oct 2026 |
| At 10M a month | not listed | $10.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GLM 4.7 is developed by OpenRouter while Step 5 Preview is developed by StepFun. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. GLM 4.7 and Step 5 Preview each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.
This page shows a side-by-side comparison of GLM 4.7 and Step 5 Preview 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.