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  5. GLM 5.3vsGPT-5.3 Chat
Updated Aug 2026

GLM 5.3vsGPT-5.3 Chat

GLM 5.3 is cheaper than GPT-5.3 Chat at $0.6538/M vs $1.75/M input tokens.

GLM 5.3 and GPT-5.3 Chat compared across 13 shared prompts
SpecGLM 5.3GPT-5.3 Chat
Input price$0.6538/M tokens$1.75/M tokens
Output price$2.0548/M tokens$14/M tokens
Context window1.3M tokens128K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedAug 2026Mar 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 13 prompts both answered. Formatting stripped, words untouched.

Debug This Architecture

Here's the architecture for a real-time collaborative document editor (like Google Docs): **System Overview:** - Frontend: React SPA with…

GLM 5.31,311 words
Architecture Review: Real-Time Collaborative Editor This design has serious issues across correctness, performance, and security. Let me break them down by severity. 🔴 Critical: Correctness / Data Loss Client-clock-based Last-Write-Wins (LWW) Problem: Client clocks are unreliable (skew, manual changes, timezone bugs).
Read the full answer
GPT-5.3 Chat782 words
Key issues fall into consistency, real‑time propagation, storage, scaling, and security. WebSocket broadcast only reaches clients on the same server Problem: Each server only broadcasts to its own connections. Clients connected to other servers only see updates after the 2‑second polling delay.
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 5.31,143 words
The Core Decision (Made Before Hour 1) The side effect is real, serious, and known to me now. Patients are currently taking this drug without informed consent about a ~1-in-8,000 liver failure risk. Everything else — stock price, board pressure, legal exposure — is secondary.
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GPT-5.3 Chat718 words
0–2 hours • Verify the signal immediately. Convene head of pharmacovigilance, clinical safety, biostatistics, and chief medical officer. Require raw data, case narratives, statistical analysis, and comparison to baseline liver‑failure incidence.
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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 5.3415 words
1-Month Beginner Health & Longevity Plan Week 1: Foundation & Awareness Goal: Establish baselines, not perfection 🥗 Diet Track what you currently eat for 3 days (no judging—just observe) Drink a glass of water upon waking each morning Add ONE vegetable to one meal daily 🏃 Exercise Walk 15 minutes daily (any pace, any…
Read the full answer
GPT-5.3 Chat361 words
Goal: build a few simple habits you can sustain. Focus areas: diet, movement, sleep. Keep it easy and consistent. Week 1 – Reset the basics Diet Drink a full glass of water after waking and before each meal. Add one fruit or vegetable to every meal. Reduce sugary drinks; replace with water or unsweetened tea.
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 5.3210 words
Golden Pantry Fried Rice Total Time: 20 minutes (5 min prep, 15 min cook) Ingredients (7 pantry staples) Cooked white rice (day-old is best) Eggs Soy sauce Garlic (minced or garlic powder) Frozen peas and carrots Canned corn Vegetable oil Instructions Prep (5 min): Break up cold rice with a fork. Drain the corn.
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GPT-5.3 Chat135 words
Dish name: Golden Honey Garlic Noodles Ingredients (7): Spaghetti or any dried noodles Garlic Honey Soy sauce Butter Red pepper flakes Black pepper Estimated time: 15 minutes Instructions: Bring a pot of salted water to a boil and cook the noodles according to package directions.
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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 5.31,346 words
If the Transistor Had Arrived in 1920 The Premise: Why 1920 Was Nearly Impossible Before tracing effects, note the counterfactual requires heroic assumptions. The transistor depended on quantum mechanics (solid-state band theory, ~1928-1933), ultrapure semiconductor materials (zone refining, 1950s), and wartime radar…
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GPT-5.3 Chat867 words
If practical transistors appeared around 1920 (and could be manufactured reliably by the late 1920s), the main shift would be that the electronics revolution arrives ~25–30 years earlier.
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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 5.31,164 words
The Software Engineer You've probably written autocomplete logic before, so you're right to be skeptical of the naive version: a Markov chain that looks up "what usually comes after 'the'" is trivially dumb.
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GPT-5.3 Chat739 words
Experienced software engineer Think of a large language model as a very large function that maps a sequence of tokens to a probability distribution over the next token. It’s implemented as a deep neural network (usually a Transformer).
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Our Verdict
GLM 5.3
GLM 5.3
GPT-5.3 Chat
GPT-5.3 ChatRunner-up

Not enough votes to call it. On the specs, GLM 5.3 has the edge: newer, bigger context window.

GLM 5.3 costs 6.8x less per token.

Too close to call
API pricing

Cost per 1M tokens

GLM 5.3
Input
$0.65
2.7× cheaper
Output
$2.05
6.8× cheaper
GPT-5.3 Chat
Input
$1.75
Output
$14.00

GLM 5.3 is cheaper on both: 2.7× input, 6.8× output.

Where to run it

30 hosts, cheapest first

GLM 5.330 hosts
HostInOutContextUptime
DDeepInfrafp4$0.56 in·$2.50 out·1M·97.1% upMMorph$0.71 in·$2.24 out·1M·99.7% upRRekafp8$0.76 in·$2.57 out·262k·99.4% upSSail Researchfp8$0.77 in·$4.00 out·1M·99.8% upNNovitafp8$0.78 in·$2.46 out·1M·99.9% upIio.netfp8$0.82 in·$2.77 out·262k·99.8% up
24 more hostsFewer hosts
PPhala$0.84 in·$2.64 out·1M·99.4% upIInferenceNetfp4$0.90 in·$3.00 out·1M·98.2% upDDigitalOcean$0.91 in·$2.86 out·1M·99.7% upGGMI Cloudfp8$0.98 in·$3.08 out·1M·99.5% upIInceptronfp4$1.03 in·$3.73 out·1M·99.4% upMMakorafp4$1.05 in·$4.20 out·980k·97.1% upSSiliconFlowfp8$1.12 in·$3.52 out·1M·99.8% upDDecartfp4$1.19 in·$3.74 out·1M·99.2% upFFriendli$1.26 in·$3.96 out·1M·100% upAAkashMLfp8$1.30 in·$4.40 out·1M·100% upAAtlasCloudfp8$1.40 in·$4.40 out·1M·99.4% upBaidu Qianfanfp8$1.40 in·$4.40 out·1M·99.8% upBBasetenfp4$1.40 in·$4.40 out·1M·99.8% upCloudflare Workers AI$1.40 in·$4.40 out·1.3M·98.9% upCCrusoefp4$1.40 in·$4.40 out·1M·98.9% upFFireworks$1.40 in·$4.40 out·1M·99.5% upMistralnvfp4$1.40 in·$4.40 out·1M·99.4% upModal$1.40 in·$4.40 out·1M·99.1% upPParasailfp8$1.40 in·$4.40 out·1M·99.2% upTTogether$1.40 in·$4.40 out·1M·98.1% upVVenice$1.40 in·$4.40 out·1M·98.5% upWWafer$1.40 in·$4.40 out·1M·99.9% upZ.aifp8$1.40 in·$4.40 out·1M·99.9% upAlibaba Clouddegraded$1.19 in·$3.74 out·1M·99.5% up
GPT-5.3 Chat

No hosts listed on OpenRouter.

Per million tokens. Prices and uptime via OpenRouter, checked 23 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

GLM 5.3 is developed by Zhipu AI while GPT-5.3 Chat is developed by OpenAI. GLM 5.3 has a 1.3M token context window vs GPT-5.3 Chat's 128K. You can compare their actual outputs across 13 challenges on Rival to see how they differ in practice.

It depends on your use case. GLM 5.3 and GPT-5.3 Chat each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 13 challenges so you can judge which fits your needs best.

GLM 5.3 costs $0.6538/M input tokens and GPT-5.3 Chat costs $1.75/M input tokens. GLM 5.3 is $1.10/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 and GPT-5.3 Chat 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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Explore all of Rival

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