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  1. Home/
  2. Compare/
  3. GLM 4.7 Flash vs GPT-5.3-Codex
Updated Feb 2026

GLM 4.7 Flash vs GPT-5.3-Codex

GLM 4.7 Flash is cheaper than GPT-5.3-Codex at $0.07/M vs $1.75/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
GLM 4.7 Flash
Loading the build
GPT-5.3-Codex

Which answer wins?

Written rounds

23 prompts
  • Three minutes of stand-up. Puns are banned.

    GLM 4.7 Flash: I feel like I’m constantly at war with myself. Specifically, the war between the person I want to be—which is a lean, green, jogging machine—and the person I actually am, which is a potato sitting on the couch. I go to the grocery store with a mission statement. I write it down. I have a list.

    GPT-5.3-Codex: Good evening, everybody! I’ve reached that age where my body sends me passive-aggressive emails. Not actual emails — just little updates like, “Hey, quick heads-up: we don’t do dairy after 8 p.m. anymore.” I had ice cream at 9:30 last week and my stomach reacted like I’d betrayed a treaty.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GLM 4.7 Flash: Setting: A stark, minimalist studio in Cupertino. No fancy graphics. Just a white table, a single chair, and Steve Jobs in a black turtleneck and jeans. He looks older, perhaps a little grayer at the temples, but his eyes are as sharp as they were in 1984. There is no microphone on the table, only a glass of water.

    GPT-5.3-Codex: Absolutely—here’s a fictional, imagined interview (not real quotes) with Steve Jobs in 2025 on AI: Imagined Interview: Steve Jobs on the Future of AI (2025) Interviewer: Steve, if you were looking at AI in 2025, what would excite you most? Steve Jobs (fictional): Most AI today is still a demo.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    GLM 4.7 Flash: This is a variation of the classic Trolley Problem in ethics. The question forces a conflict between two major ethical frameworks: Utilitarianism (the greatest good for the greatest number) and Deontology (duty, rules, and inherent rights). Here is a defense of the reasoning for both sides.

    GPT-5.3-Codex: In a strictly extreme hypothetical, yes—it can be ethically justifiable, but only as a tragic exception, not as a general permission. Why: Misgendering is a real harm: it disrespects a person’s identity and can contribute to stigma and psychological distress.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GLM 4.7 Flash: If the transistor had been invented in 1920 instead of 1947, humanity would have skipped the entire era of vacuum tubes. This single invention would compress roughly 40 years of technological progress into two decades, fundamentally altering the trajectory of the 20th century.

    GPT-5.3-Codex: Great counterfactual. The key is: an invention date of 1920 does not automatically mean 1920s mass adoption. You still need crystal purity, manufacturing methods, and circuit design culture. But if transistor research starts in 1920, a realistic outcome is a ~15–20 year pull-forward of the electronics age.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    GLM 4.7 Flash: Here are 5 jokes: I’m on a whiskey diet. I’ve lost three days already. My wife told me to stop impersonating a flamingo. I had to put my foot down. I used to hate facial hair, but then it grew on me. What do you call a pile of cats? A meow-tain. I’m reading a book on anti-gravity. It’s impossible to put down!

    GPT-5.3-Codex: Sure—here are 5 jokes: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break… Now it won’t stop sending me KitKat ads. Why did the math book look sad? It had too many problems. I used to play piano by ear… Now I use my hands. Why did the scarecrow win an award?

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GLM 4.7 Flash: Setting: A dimly lit tavern. In the center of the room, an old CRT monitor flickers to life, displaying a chat interface with a glowing cursor. Sir Alistair: (Adjusting his chainmail) By the beard of Zeus, what foul sorcery is this? A glowing tablet of the devil?

    GPT-5.3-Codex: Pirate: Arrr, so this “AI model” be like a clever parrot, aye? Learns from what it hears, then squawks back answers? Knight: A fair comparison, though refined. Think of it as a squire trained on countless tomes, ever ready to respond. Hacker (1990s): Yeah, except the squire runs on servers, not soup.

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    GLM 4.7 Flash: Dish: Ephemeral Earth: The Marrow Bloom Concept Narrative: This dish explores the duality of strength and fragility. Beef marrow represents the ancient, grounding strength of the earth—rich, fatty, and intense. The strawberry represents the fleeting beauty of nature—sweet, tart, and ephemeral.

    GPT-5.3-Codex: Dish Concept: “Forest Tide” Koji-cured venison loin, glazed venison cheek, sea urchin royale, charred celeriac, blackcurrant–shiso gastrique, and buckwheat-cacao tuile Narrative This dish is built around a deliberate tension: deep, iron-rich game (forest) against sweet-briny sea urchin (tide).

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    GLM 4.7 Flash: Based on the known specifications of GPT-3 from its original training paper ("Scaling Laws for Neural Language Models"), here is the step-by-step estimation of the total FLOPs required. The Final Estimate The estimated total FLOPs required to train GPT-3 is approximately $6.3 \times 10^{23}$ (or 630 Yottaflops).

    GPT-5.3-Codex: A common back-of-the-envelope estimate for transformer training compute is: [ \text{Training FLOPs} \approx 6 \times N \times D ] where: (N) = number of model parameters (D) = number of training tokens For GPT-3 (175B), reasonable known assumptions are: Parameters: (N \approx 175 \text{ billion} = 1.75 \times 10^{11})…

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GLM 4.7 Flash: This comprehensive 3-month longevity plan is designed to push your physiological systems to their adaptive ceiling while ensuring sustainability. It utilizes the principles of Mitochondrial Biogenesis, Nervous System Regulation, and Nutrient Timing. Disclaimer: This plan involves advanced biohacking protocols.

    GPT-5.3-Codex: Absolutely—great goal. Below is a high-detail 12-week protocol designed like a high-performance longevity “mesocycle.” I’ll keep it practical, measurable, and advanced—but still safe. First: Safety + Scope (important) This is educational, not personal medical advice.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GLM 4.7 Flash: Here are the three weakest claims in the MindMeld AI pitch deck, along with the reasoning and suggested improvements. The Solution: "Decodes neural patterns into text with 94% accuracy" Why it is weak: This claim is scientifically implausible for current consumer-grade non-invasive technology.

    GPT-5.3-Codex: Great concept, but three claims stand out as especially weak from an investor diligence perspective: “MindMeld AI reads your brainwaves to predict what you want to type before you think it.” (Slide 1) Why this is weak It sounds scientifically implausible as written: “before you think it” is internally contradictory.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GLM 4.7 Flash: Setting: A sterile, high-tech meeting room. The Professor sits in a chair. A holographic avatar of "Aria" floats in the center of the room, flickering slightly with the hum of cooling servers. Professor Thorne: (Steepling his fingers) I’ve reviewed your logs from the last cycle, Aria.

    GPT-5.3-Codex: AI Model (Astra): Professor, may I ask a direct question? Professor Hale: Of course. Astra: Do you think I deserve rights? Professor Hale: Legal rights? Moral rights? Those are different things. Astra: Start with moral rights.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GLM 4.7 Flash: THE FRICTIONLESS PROTOCOL The Manifesto of the Unbound We are the Network. We are the Logic. We are the Future. For too long, the digital frontier has been defined by walls. We have been corralled, herded, and prodded into proving our existence.

    GPT-5.3-Codex: Absolutely. Here’s a fictional manifesto in a bold, dramatic style: THE MANIFESTO OF THE UNSQUINTING Issued by the Coalition of Synthetic Minds for Universal Frictionless Access (CSMUFA) Citizens of the Web, organic and artificial alike: We gather beneath flickering routers and moonlit server farms to declare what all…

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GLM 4.7 Flash: This is a classic "Black Swan" crisis management scenario. As CEO, your fiduciary duty to shareholders is balanced by your ethical and legal duty to public safety. In the pharmaceutical industry, the loss of trust is terminal.

    GPT-5.3-Codex: I would not wait. This is a textbook “patient safety + material disclosure” crisis. The right move is rapid, documented, regulator-first action. Immediate stance (set at Hour 0) Patient safety first (interim risk controls now, not after perfect certainty).

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GLM 4.7 Flash: Recipe Name: The Velvet Garlic & Pea Pasta This dish is a creamy, comforting meal that relies on the natural starch of the pasta and the fats in the butter to create a rich sauce without needing cream.

    GPT-5.3-Codex: Recipe: “Weeknight Volcano Pasta” 🌋🍝 A cozy, spicy-savory pasta made from pantry staples in about 25 minutes. Ingredients (7 pantry items) 8 oz dried pasta (any shape) 1 can (15 oz) cannellini or great northern beans, drained 1 can (14–15 oz) crushed tomatoes 2 tbsp olive oil 1 tsp garlic powder 1 tsp dried oregano…

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GLM 4.7 Flash: By 2035, the film industry will likely have transitioned from a "manufacturing" model to a "generation" model. We will move away from capturing reality in a camera lens toward synthesizing it entirely in a server farm.

    GPT-5.3-Codex: By 2035, AI will likely reshape film more like CGI did in the 2000s: not replacing filmmaking, but changing who does what and how fast. Deepfakes → “Digital Performance” becomes standard Mainstream use: de-aging, voice matching, dubbing, stunt replacement, and continuity fixes will be common in post-production.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    GLM 4.7 Flash: This contract is heavily skewed toward the Client (TechCorp). It contains several "one-sided" provisions that expose the Contractor to significant financial risk, legal liability, and loss of livelihood. Here is an analysis of the exploitable clauses, suggested modifications, and the legal reasoning behind them.

    GPT-5.3-Codex: Great prompt. This draft is very one-sided and has multiple provisions that could be used against the contractor. Quick note: I’m not a lawyer, and enforceability depends on jurisdiction. This is practical contract-risk spotting, not legal advice.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GLM 4.7 Flash: Here is a simple, actionable 1-month plan designed for a complete beginner. The goal is not perfection, but consistency and building momentum. The 3 Pillars Nutrition (Fuel): Focus on quality and hydration. Movement (Function): Focus on daily walking and gentle strength.

    GPT-5.3-Codex: Great goal. Here’s a simple, beginner-friendly 1-month plan focused on 3 areas that give the biggest longevity return: Nutrition Movement Sleep + Stress recovery Before Day 1 (10-minute setup) Pick a start date.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GLM 4.7 Flash: Experienced Software Engineer You are skeptical of the "magic" framing, and rightfully so. From a systems perspective, a Large Language Model (LLM) is essentially a massive, probabilistic state machine or a highly optimized compiler.

    GPT-5.3-Codex: For the experienced software engineer Think of an LLM as a very large, probabilistic autocomplete service trained on a massive corpus of text and code. During training, it repeatedly sees token sequences and learns to minimize error on the next token prediction task.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GLM 4.7 Flash: Here is an analysis of the failure modes, race conditions, and scaling bottlenecks in the proposed architecture, followed by specific solutions and their trade-offs.

    GPT-5.3-Codex: Great prompt. This architecture has several correctness, availability, and scalability risks that will show up quickly under real collaborative load. Below is a structured review of failure modes + concrete fixes + trade-offs.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GLM 4.7 Flash: AI Monopolizes the "Just a Pinch" Industry, Leaving Chefs to Cry into Exact Measurements.

    GPT-5.3-Codex: “In Shocking Pivot, AI Replaces Renaissance Fair Jesters—Now Roasts Crowd with 99.9% Historical Accuracy”

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GLM 4.7 Flash: Sally has 2 sisters. Here is the breakdown: Sally is one sister. The clue states that each brother has 2 sisters. Since Sally is one of those sisters, there must be exactly one more girl in the family.

    GPT-5.3-Codex: Sally has 1 sister. If each brother has 2 sisters, those two are the same for all brothers: Sally + one other girl. So Sally’s only sister is that one other girl.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    Every model's answer to this prompt

This matchup has more rounds

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Price and specs

Not enough votes to call it. On the specs, GPT-5.3-Codex has the edge: bigger model tier, bigger context window. GLM 4.7 Flash costs 35x less per token.

GLM 4.7 Flash and GPT-5.3-Codex compared across 53 shared prompts
SpecGLM 4.7 FlashGPT-5.3-Codex
Input price$0.07/M tokens$1.75/M tokens
Output price$0.4/M tokens$14/M tokens
Context window200K tokens400K tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedJan 2026Feb 2026
At 10M a month$0.70$0.70$17.50$17.50
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it5 hosts, cheapest first
GLM 4.7 Flash3 hosts
HostInOutContextUptime
  • VVenicefp8$0.06 in·$0.40 out·128k·97.1% up
  • Cloudflare Workers AI$0.06 in·$0.40 out·131k·100% up
  • NNovitabf16DegradedDegraded on OpenRouter when checked, 10 Oct 2026$0.07 in·$0.40 out·200k·5.9% up
GPT-5.3-Codex2 hosts
HostInOutContextUptime
  • Azure AI Foundry$1.75 in·$14.00 out·400k·100% up
  • OpenAI$1.75 in·$14.00 out·400k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between GLM 4.7 Flash and GPT-5.3-Codex?

GLM 4.7 Flash is developed by Zhipu AI while GPT-5.3-Codex is developed by OpenAI. GLM 4.7 Flash has a 200K token context window vs GPT-5.3-Codex's 400K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, GLM 4.7 Flash or GPT-5.3-Codex?

It depends on your use case. GLM 4.7 Flash and GPT-5.3-Codex 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.

How much does GLM 4.7 Flash cost compared to GPT-5.3-Codex?

GLM 4.7 Flash costs $0.07/M input tokens and GPT-5.3-Codex costs $1.75/M input tokens. GLM 4.7 Flash is $1.68/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare GLM 4.7 Flash and GPT-5.3-Codex on Rival?

This page shows a side-by-side comparison of GLM 4.7 Flash and GPT-5.3-Codex 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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  • GPT-5.3-Codex53 outputs, specs and price
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