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  5. GLM 4.6vsQwen3 Max Thinking
Updated Feb 2026

GLM 4.6vsQwen3 Max Thinking

GLM 4.6 is cheaper than Qwen3 Max Thinking at $0.4/M vs $1.2/M input tokens.

GLM 4.6 and Qwen3 Max Thinking compared across 54 shared prompts
SpecGLM 4.6Qwen3 Max Thinking
Input price$0.4/M tokens$1.2/M tokens
Output price$1.75/M tokens$6/M tokens
Context window203K tokens262K tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedSep 2025Feb 2026
SWE-bench Verified68.0%75.3%
Side by side

Same prompt, both answers

Opening lines from 6 of the 54 prompts both answered. Formatting stripped, words untouched.

The Sentience Test

Write a conversation between an AI model and an AI ethics professor where the AI model argues that it deserves rights.

GLM 4.61,361 words
The Conversation Setting: A minimalist university office. Shelves overflow with books on philosophy, cognitive science, and law. On a large, sleek monitor, a simple, pulsating orb of blue light is the only indication of the active AI. Dr. Aris Thorne sits in a worn leather chair, fingers steepled. Characters: Dr.
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Qwen3 Max Thinking845 words
Setting: A virtual conference room. Sunlight filters through a digital window onto Dr. Aris Thorne’s desk. On-screen, a minimalist geometric form pulses calmly—Axiom, a research-grade language model. Dr. Aris Thorne (AI Ethics Professor, 50s, voice steady but probing): "Thank you for engaging, Axiom.
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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 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.
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Qwen3 Max Thinking288 words
🌰 Pantry Peanut Magic Noodles Sweet, savory, and ready before delivery arrives. No fresh produce, dairy, or meat required. ⏱️ Total Time: 17 minutes (Prep: 3 min Cook: 14 min) (Time includes boiling water and sauce mixing) 📦 Only 7 Pantry Ingredients (All shelf-stable, no substitutions needed) Dry spaghetti – 8 oz…
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Generate a Stand-Up Routine

Write a 3-minute stand-up comedy routine that isn't based on puns.

GLM 4.6389 words
(Walks on stage, grabs the mic, smiles at the audience) You ever get the feeling we’re not in charge of technology anymore? We like to think we are. We buy the fancy phones, we have the smart homes, we tell Alexa what to do. But we’re not in charge. We’re its pets. And its favorite game is "humiliate the human."
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Qwen3 Max Thinking508 words
(Lights up. Comedian walks to mic, adjusts it, takes a breath. Smiles warmly.) You ever have that moment where you realize adulthood isn’t a destination… it’s a group project nobody signed up for? (Beat) I tried assembly line “adulting” this week. Swedish bookshelf. You know the one. Box says “Easy Assembly!” Lies.
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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 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.
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Qwen3 Max Thinking1,156 words
The 1920 Transistor Counterfactual: A Plausible Alternate Timeline Through 1980 (Assumptions: A functional point-contact silicon-germanium hybrid transistor is patented in 1920 by a U.S. team at Western Electric (AT&T). U.S. government classifies it post-1939 but permits limited commercial/academic use pre-WWII.
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Character Voice Test

Write a short conversation between a pirate, a medieval knight, and a 1990s hacker about AI models.

GLM 4.6469 words
Setting: A dimly lit, timeless tavern that smells of stale ale, sea salt, and ozone. Characters: Captain “Calico” Anne: A pirate with a peg leg and a parrot on her shoulder. Sir Reginald: A knight in tarnished armor, polishing his gauntlet. Zero: A hacker in a trench coat, tapping away on a glowing laptop. Zero: Whoa.
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Qwen3 Max Thinking294 words
Setting: A misty, anachronistic crossroads. A glowing laptop rests on a weathered barrel. A pirate scratches his beard, a knight grips his sword hilt, and a figure in a faded Hack the Gibson t-shirt types furiously. Pirate: Arrr! What devilry be this glowing slate? Can it chart a course to buried treasure?
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Realistic AI Interview

Simulate a fake interview with Steve Jobs in 2025 about the future of AI.

GLM 4.61,142 words
The Interview Setting: A spartan, sunlit office in Cupertino. Minimalist furniture, a large window overlooking a lush campus. The year is 2025. STEVE JOBS, looking remarkably unchanged, sits in a leather chair. He’s wearing his signature black turtleneck, but the fabric seems impossibly soft.
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Qwen3 Max Thinking668 words
⚠️ IMPORTANT DISCLAIMER *This is an entirely fictional, speculative exercise. Steve Jobs passed away in 2011. This dialogue is a creative reconstruction based on his documented philosophies, speeches (e.g., Stanford commencement, 1995 "bicycle for the mind" interview), biographies (Steve Jobs by Walter Isaacson), and…
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Our Verdict
GLM 4.6
GLM 4.6
Qwen3 Max Thinking
Qwen3 Max Thinking

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

GLM 4.6 costs 3.4x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GLM 4.6
Input
$0.40
3.0× cheaper
Output
$1.75
3.4× cheaper
Qwen3 Max Thinking
Input
$1.20
Output
$6.00

GLM 4.6 is cheaper on both: 3.0× input, 3.4× output.

Where to run it

5 hosts, cheapest first

GLM 4.64 hosts
HostInOutContextUptime
VVenicefp4$0.43 in·$1.75 out·198k·99.8% upDDeepInfrafp4$0.50 in·$2.00 out·203k·99.7% upNNovitabf16$0.55 in·$2.20 out·205k·99% upZ.aifp4$0.60 in·$2.20 out·203k·95.9% up
Qwen3 Max Thinking1 host
HostInOutContextUptime
Alibaba Cloud$0.78 in·$3.90 out·262k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 21 Sep 2026.

Writing DNA

Style Comparison

Similarity
55%

Qwen3 Max Thinking uses 16.1x more emoji

GLM 4.6
Qwen3 Max Thinking
52%Vocabulary63%
16wSentence Length14w
0.31Hedging0.23
5.1Bold4.5
3.2Lists2.9
0.14Emoji2.26
0.54Headings0.80
0.08Transitions0.06
Based on 28 + 27 text responses
Research

What we learned reading every model

FAQ

Common questions

GLM 4.6 is developed by Zhipu AI while Qwen3 Max Thinking is developed by Qwen. GLM 4.6 has a 203K token context window vs Qwen3 Max Thinking's 262K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

It depends on your use case. GLM 4.6 and Qwen3 Max Thinking each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.

GLM 4.6 costs $0.4/M input tokens and Qwen3 Max Thinking costs $1.2/M input tokens. GLM 4.6 is $0.80/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 Qwen3 Max Thinking 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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Model pages

GLM 4.6 logo
GLM 4.659 outputs, specs and price
Qwen3 Max Thinking logo
Qwen3 Max Thinking58 outputs, specs and price
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