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  5. GLM 4.6vsGLM 5.3 FlashX
Updated Sep 2026

GLM 4.6vsGLM 5.3 FlashX

GLM 5.3 FlashX is cheaper than GLM 4.6 at $0.37/M vs $0.4/M input tokens.

GLM 4.6 and GLM 5.3 FlashX compared across 12 shared prompts
SpecGLM 4.6GLM 5.3 FlashX
Input price$0.4/M tokens$0.37/M tokens
Output price$1.75/M tokens$1.25/M tokens
Context window203K tokens1.0M tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedSep 2025Sep 2026
Side by side

Same prompt, both answers

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

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 4.6288 words
Of course! Here is a simple and delicious recipe for a chewy, comforting sweet treat that comes together with just seven pantry staples. Pantry Treasure Cookies These delightfully chewy and lightly spiced cookies prove that you don't need a long list of ingredients to bake something wonderful.
Read the full answer
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…
Read the full answer

Historical Counterfactual Analysis

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

GLM 4.61,573 words
This is a fascinating and complex scenario. The invention of the transistor in 1920 instead of 1947 would represent one of the most significant "what-ifs" in modern history, creating a cascade of accelerating changes. Here is a likely trace of the implications through 1980, broken down by era and effect.
Read the full answer
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…
Read the full answer

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 4.6918 words
Of course! Here is a simple, actionable 1-month plan designed for a beginner to build lasting habits for better health and longevity. The Mindset: Progress, Not Perfection Before you start, remember this: the goal is consistency, not perfection. You will have off days. That's normal.
Read the full answer
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…
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 4.61,502 words
This is a defining moment. The decision made in the next 48 hours will determine not only the company's financial future but its soul. My guiding principle is simple: We will control the narrative by doing the right thing, immediately.
Read the full answer
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

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 4.6793 words
For the Experienced Software Engineer Think of an LLM's training process as a massive, distributed compression and compilation task. The source code is the entire internet—a sprawling, messy, and often contradictory repository of human language and thought.
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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.
Read the full answer

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 4.61,025 words
Excellent. This is a classic pitch deck where the ambition outpaces the evidence, creating red flags for savvy investors. Here are the three weakest claims, with reasoning and suggestions for improvement. The "Consumer-Grade" vs.
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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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Our Verdict
GLM 4.6
GLM 4.6
GLM 5.3 FlashX
GLM 5.3 FlashX

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

Too close to call
API pricing

Cost per 1M tokens

GLM 4.6
Input
$0.40
Output
$1.75
GLM 5.3 FlashX
Input
$0.37
1.1× cheaper
Output
$1.25
1.4× cheaper

GLM 5.3 FlashX is cheaper on both: 1.1× input, 1.4× output.

Where to run it

5 hosts, cheapest first

GLM 4.64 hosts
HostInOutContextUptime
VVenicefp4$0.43 in·$1.75 out·198k·99.9% upDDeepInfrafp4$0.50 in·$2.00 out·203k·99.6% upNNovitabf16$0.55 in·$2.20 out·205k·98.8% upZ.aifp4$0.60 in·$2.20 out·203k·99.7% up
GLM 5.3 FlashX1 host
HostInOutContextUptime
Z.aifp8$0.37 in·$1.25 out·1M·100% up

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

Research

What we learned reading every model

FAQ

Common questions

Both are developed by Zhipu AI but target different use cases. GLM 4.6 has a 203K token context window vs GLM 5.3 FlashX's 1.0M. 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 4.6 and GLM 5.3 FlashX 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 4.6 costs $0.4/M input tokens and GLM 5.3 FlashX costs $0.37/M input tokens. GLM 5.3 FlashX is $0.03/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 4.6 and GLM 5.3 FlashX 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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