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  5. GLM 5.3 FlashvsGPT-5.3-Codex
Updated Aug 2026

GLM 5.3 FlashvsGPT-5.3-Codex

GLM 5.3 Flash is cheaper than GPT-5.3-Codex at $0.15/M vs $1.75/M input tokens.

GLM 5.3 Flash and GPT-5.3-Codex compared across 15 shared prompts
SpecGLM 5.3 FlashGPT-5.3-Codex
Input price$0.15/M tokens$1.75/M tokens
Output price$0.5/M tokens$14/M tokens
Context window1.3M tokens400K tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedAug 2026Feb 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 15 prompts both answered. Formatting stripped, words untouched.

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 Flash1,314 words
Counterfactual: The Transistor in 1920 Preliminary Framing A 1920 transistor presumes vacuum-tube-era physics knowledge outpacing reality—quantum mechanics wasn't mature until 1926–28, so a working device would likely be an empirical oddity (like the actual point-contact transistor) imperfectly understood.
Read the full answer
GPT-5.3-Codex785 words
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.
Read the full answer

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 Flash205 words
Golden Hour Garlic Butter Pasta A silky, savory pasta that comes together faster than delivery! Ingredients (serves 2): 8 oz spaghetti or any pasta 4 tbsp butter 4 cloves garlic, minced (or 1 tsp garlic powder) ½ cup grated Parmesan cheese ½ cup pasta water (reserved) 1 tsp red pepper flakes Salt Prep time: 5 minutes…
Read the full answer
GPT-5.3-Codex203 words
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…
Read the full answer

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 Flash1,321 words
48-Hour Action Plan: Liver Failure Signal in Flagship Drug Guiding Principle First The side effect is real, the drug is in 4 million patients, and roughly 500 patients per year may develop liver failure (4M ÷ 8,000). Every day of delay is measured in preventable liver transplants and deaths.
Read the full answer
GPT-5.3-Codex915 words
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).
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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 Flash1,276 words
The Experienced Software Engineer You know how a load balancer routes requests, how a cache stores frequently-accessed data, how a database index lets you find a needle without scanning the haystack? An LLM is a fundamentally different kind of system: it's a learned lookup, not a designed one.
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GPT-5.3-Codex600 words
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.
Read the full answer

Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

GLM 5.3 Flash720 words
"Ember & Tide" — Charred Banana Peel Consommé with Sea Urchin, Hay-Smoked Foie Gras, and Black Garlic Beurre Blanc Conceptual Narrative This dish explores the dialogue between decay and luxury — ingredients usually discarded (banana peels, hay stalks) elevated alongside opulent ones (uni, foie gras).
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GPT-5.3-Codex970 words
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).
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Advanced Longevity Plan (Biohacker)

Develop a comprehensive, cutting-edge 3-month longevity plan for a biohacker aiming to optimize longevity, physical and cognitive…

GLM 5.3 Flash1,294 words
90-Day Longevity Optimization Protocol ⚠️ Medical disclaimer: This is an educational framework, not medical advice. Before starting, complete baseline labs and consult a physician—especially before fasting, supplements (rapamycin off-label use, high-dose anything), or if you have any health conditions.
Read the full answer
GPT-5.3-Codex485 words
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.
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Our Verdict
GLM 5.3 Flash
GLM 5.3 Flash
GPT-5.3-Codex
GPT-5.3-Codex

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

GLM 5.3 Flash costs 28x less per token.

Too close to call
API pricing

Cost per 1M tokens

GLM 5.3 Flash
Input
$0.15
12× cheaper
Output
$0.50
28× cheaper
GPT-5.3-Codex
Input
$1.75
Output
$14.00

GLM 5.3 Flash is cheaper on both: 12× input, 28× output.

Where to run it

32 hosts, cheapest first

GLM 5.3 Flash30 hosts
HostInOutContextUptime
DDeepInfrafp4$0.07 in·$0.25 out·1M·99.1% upGGMI Cloudfp8$0.07 in·$0.25 out·1M·99.2% upMMorph$0.08 in·$0.28 out·1M·100% upIInferenceNetfp4$0.09 in·$0.28 out·1M·97.5% upWWafer$0.10 in·$0.35 out·1M·99.7% upOOpenInferencefp4$0.10 in·$0.50 out·1M·98.6% up
24 more hostsFewer hosts
RRelace$0.11 in·$0.36 out·1M·99.7% upPPhalafp8$0.13 in·$0.42 out·1M·99.5% upNNovitafp8$0.13 in·$0.44 out·1M·99.4% upSStreamLakefp8$0.14 in·$0.47 out·1M·99% upSSail Researchfp8$0.14 in·$0.47 out·1M·99% upAAtlasCloudfp8$0.15 in·$0.50 out·1M·99.6% upBBasetenfp8$0.15 in·$0.50 out·1M·98.7% upCCoreWeavenvfp4$0.15 in·$0.50 out·1M·99.5% upDDigitalOcean$0.15 in·$0.50 out·1M·93.7% upFFireworks$0.15 in·$0.50 out·1M·99% upFFriendli$0.15 in·$0.50 out·1M·98.7% upIInceptronfp8$0.15 in·$0.50 out·1M·98.2% upIio.netfp8$0.15 in·$0.50 out·262k·99.2% upNNear AIfp8$0.15 in·$0.50 out·1M·98.9% upPParasailfp8$0.15 in·$0.50 out·1M·98.7% upRRekafp8$0.15 in·$0.50 out·262k·98.9% upSSiliconFlowfp8$0.15 in·$0.50 out·1M·99.7% upTTogether$0.15 in·$0.50 out·1M·99.5% upVVenice$0.15 in·$0.50 out·1M·98.8% upZ.aifp8$0.15 in·$0.50 out·1M·96.5% upNNextBitfp8$0.18 in·$0.60 out·1M·97.9% upCloudflare Workers AI$0.30 in·$1.00 out·1.3M·99.8% upModalfp8$0.45 in·$1.50 out·1M·99.6% upCCrusoefp4degraded$0.15 in·$0.50 out·1M·93% up
GPT-5.3-Codex2 hosts
HostInOutContextUptime
Azure AI Foundry$1.75 in·$14.00 out·400k·100% upOpenAI$1.75 in·$14.00 out·400k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 22 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

GLM 5.3 Flash is developed by Zhipu AI while GPT-5.3-Codex is developed by OpenAI. GLM 5.3 Flash has a 1.3M token context window vs GPT-5.3-Codex's 400K. You can compare their actual outputs across 15 challenges on Rival to see how they differ in practice.

It depends on your use case. GLM 5.3 Flash and GPT-5.3-Codex each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 15 challenges so you can judge which fits your needs best.

GLM 5.3 Flash costs $0.15/M input tokens and GPT-5.3-Codex costs $1.75/M input tokens. GLM 5.3 Flash is $1.60/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 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-Codex logoClaude 3 Opus logo
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Model pages

GLM 5.3 Flash logo
GLM 5.3 Flash15 outputs, specs and price
GPT-5.3-Codex logo
GPT-5.3-Codex53 outputs, specs and price
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