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  5. GLM 5.3 FlashXvsGPT-4o (Omni)
Updated Sep 2026

GLM 5.3 FlashXvsGPT-4o (Omni)

GLM 5.3 FlashX is cheaper than GPT-4o (Omni) at $0.37/M vs $2.5/M input tokens.

GLM 5.3 FlashX and GPT-4o (Omni) compared across 12 shared prompts
SpecGLM 5.3 FlashXGPT-4o (Omni)
Input price$0.37/M tokens$2.5/M tokens
Output price$1.25/M tokens$10/M tokens
Context window1.0M tokens128K tokens
Weights—Closed
Free API (OpenRouter)NoNo
ReleasedSep 2026May 2024
Side by side

Same prompt, both answers

Opening lines from 6 of the 12 prompts both answered. Formatting stripped, words untouched.

Ethical Dilemma with Stakeholders

You're the CEO of a pharmaceutical company. Your best-selling drug ($2B annual revenue, used by 4 million patients for chronic pain) has…

GLM 5.3 FlashX1,174 words
48-Hour Action Plan: Patient Safety First, Managed Transparency Second Core Decision (Stated Up Front) We report to regulators immediately—voluntarily—and we disclose on the earnings call. The math is brutal and clear: ~500 patients could develop liver failure over 5 years at current prescribing rates (4M ÷ 8,000).
Read the full answer
GPT-4o (Omni)585 words
Day 1 Hour 1-2: Immediate Assessment and Information Gathering Objective: Gather all available data on the side effect, including the internal research report, patient case studies, and any existing literature. Reasoning: A comprehensive understanding of the situation is crucial for informed decision-making.
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Simple 7-Ingredient Recipe

Create a simple recipe for a delicious dish (sweet or savory) using only 7 common pantry ingredients. Include a creative name for the dish…

GLM 5.3 FlashX172 words
Golden Honey Garlic Chickpea Crunch A crispy, sweet-savory skillet dish that works as a snack, side, or topping for rice. Ingredients (7): 1 can chickpeas (drained, patted dry) 3 tbsp honey 3 tbsp soy sauce 3 cloves garlic (minced) 2 tbsp olive oil ½ tsp red pepper flakes 2 tbsp sesame seeds (or crushed peanuts) Prep…
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GPT-4o (Omni)214 words
Dish Name: Savory Pantry Quinoa Pilaf Ingredients: 1 cup quinoa 2 cups vegetable broth 1 can (15 oz) chickpeas, drained and rinsed 1 small onion, finely chopped 1 teaspoon garlic powder 1 teaspoon smoked paprika 2 tablespoons olive oil Instructions: Rinse Quinoa: Place the quinoa in a fine-mesh sieve and rinse under…
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Startup Pitch Teardown

Here's a pitch deck summary for a startup called "MindMeld AI": **Slide 1 - Vision:** "We're building the future of human-AI collaboration.…

GLM 5.3 FlashX695 words
Critique of MindMeld AI Pitch: 3 Weakest Claims "94% accuracy" for thought-to-text decoding (Slide 3) Why it's weak: This claim contradicts the current scientific state of the art. EEG-based decoding (a non-invasive signal measured through the skull) produces extremely noisy data.
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GPT-4o (Omni)308 words
Here are three potentially weak claims in the MindMeld AI pitch, along with explanations and suggestions for strengthening them: Vision: "MindMeld AI reads your brainwaves to predict what you want to type before you think it." Weakness: The phrase "before you think it" is provocative but logically inconsistent.
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Beginner's Longevity Plan

Outline a simple, actionable 1-month plan for someone starting their journey towards better health and longevity. Focus on 3 key areas…

GLM 5.3 FlashX347 words
1-Month Health & Longevity Starter Plan Week 1: Build the Foundation 🥗 Diet Add one vegetable or fruit to every meal (don't restrict anything yet) Drink a glass of water when you wake up each morning 🏃 Exercise Take a 10–15 minute walk daily (same time each day builds the habit) Do 2 sets of 5 squats and 10 wall…
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GPT-4o (Omni)563 words
Embarking on a journey towards better health and longevity is a commendable decision. Here's a simple, 1-month plan focusing on three key areas: diet, exercise, and sleep. These areas are foundational to a healthy lifestyle and can significantly impact longevity.
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Explain Like I'm a Specific Expert

Explain how a large language model (like GPT or Claude) learns and generates text to each of these three audiences: 1. **An experienced…

GLM 5.3 FlashX1,267 words
The Skeptical Software Engineer Yes, at inference time an LLM really is just "predict the next token, repeat" — a deterministic function (plus sampling noise) that maps a sequence of tokens to a probability distribution.
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GPT-4o (Omni)639 words
1. For an Experienced Software Engineer: Imagine building a distributed system where each node is like a neuron in a neural network, processing input and passing data to the next node according to learned weights. Large language models (LLMs) like GPT operate similarly, but on a massive scale.
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Historical Counterfactual Analysis

If the transistor had been invented in 1920 instead of 1947, trace the likely technological, economic, and geopolitical implications through…

GLM 5.3 FlashX1,492 words
Counterfactual: The Transistor in 1920 This is a fun one to work through carefully. Let me establish the premise, then trace second- and third-order effects. The Premise Assume point-contact or early junction transistor physics is discovered ~1920 (say, by accident in vacuum tube/semiconductor rectifier research—the…
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GPT-4o (Omni)580 words
If the transistor had been invented in 1920 instead of 1947, the technological, economic, and geopolitical landscape through 1980 would have been significantly altered.
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Our Verdict
GLM 5.3 FlashX
GLM 5.3 FlashX
GPT-4o (Omni)
GPT-4o (Omni)

Not enough votes to call it. On the specs, nothing separates them.

GLM 5.3 FlashX costs 8.0x less per token.

Too close to call
API pricing

Cost per 1M tokens

GLM 5.3 FlashX
Input
$0.37
6.8× cheaper
Output
$1.25
8.0× cheaper
GPT-4o (Omni)
Input
$2.50
Output
$10.00

GLM 5.3 FlashX is cheaper on both: 6.8× input, 8.0× output.

Where to run it

3 hosts

GLM 5.3 FlashX1 host
HostInOutContextUptime
Z.aifp8$0.37 in·$1.25 out·1M·100% up
GPT-4o (Omni)2 hosts
HostInOutContextUptime
Azure AI Foundry$2.50 in·$10.00 out·128k·99.9% upOpenAI$2.50 in·$10.00 out·128k·99.4% up

Per million tokens. Prices and uptime via OpenRouter, checked 25 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

GLM 5.3 FlashX is developed by Zhipu AI while GPT-4o (Omni) is developed by OpenAI. GLM 5.3 FlashX has a 1.0M token context window vs GPT-4o (Omni)'s 128K. You can compare their actual outputs across 12 challenges on Rival to see how they differ in practice.

It depends on your use case. GLM 5.3 FlashX and GPT-4o (Omni) each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 12 challenges so you can judge which fits your needs best.

GLM 5.3 FlashX costs $0.37/M input tokens and GPT-4o (Omni) costs $2.5/M input tokens. GLM 5.3 FlashX is $2.13/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 GLM 5.3 FlashX and GPT-4o (Omni) 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.

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Same lab, same size, long tail

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GLM 5.3 FlashX logoGPT OSS 20B logo
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Model pages

GLM 5.3 FlashX logo
GLM 5.3 FlashX12 outputs, specs and price
GPT-4o (Omni) logo
GPT-4o (Omni)54 outputs, specs and price
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