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  5. GLM 4 32BvsGPT-6 Luna
Updated Sep 2026

GLM 4 32BvsGPT-6 Luna

GPT-6 Luna has a larger context window than GLM 4 32B (1.1M tokens vs 128K tokens).

GLM 4 32B and GPT-6 Luna compared across 20 shared prompts
SpecGLM 4 32BGPT-6 Luna
Input price$0.1/M tokens$0.1/M tokens
Output price$0.1/M tokens$0.5/M tokens
Context window128K tokens1.1M tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedJul 2025Sep 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 20 prompts both answered. Formatting stripped, words untouched.

Adversarial Contract Review

Here is a contract for a software consulting engagement: --- SOFTWARE CONSULTING AGREEMENT This Agreement is entered into between TechCorp…

GLM 4 32B740 words
This contract is heavily skewed in favor of the Client and contains several clauses that could be exploited against the Contractor. Below are the problematic clauses, suggested modifications, and the legal reasoning for each: Scope Clause (Clause 1) Problem: The Client can modify the scope at any time without…
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GPT-6 Luna2,040 words
This agreement is strongly one-sided. The enforceability of particular terms—especially the non-compete, liability provisions, and arbitration clause—depends on the governing law and the facts. The agreement does not identify a governing law, which is itself a significant gap.
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 32B463 words
Here are the 3 weakest claims in the pitch deck for MindMeld AI, along with explanations and suggestions for strengthening them: 1. Weak Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy. Works with any language, any device."
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GPT-6 Luna421 words
“94% accuracy” and “predict what you want to type before you think it” Why it’s weak: This is the deck’s central technical claim, but “accuracy” is undefined: Is it word-level or character-level accuracy, measured on a fixed vocabulary or open-ended text, and under what conditions?
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 4 32B208 words
Okay, here's a simple, delicious savory dish using just 7 common pantry ingredients! Dish Name: Cheesy Tomato Toastie Yields: 1 serving Prep Time: 5 minutes Cook Time: 5-7 minutes Ingredients: 1 Slice of Bread 1 Tablespoon Tomato Paste 1 Tablespoon Water (or more if needed) 1 Tablespoon Grated Cheese (like Cheddar…
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GPT-6 Luna113 words
Crispy Parmesan Chickpeas A crunchy, savory snack with a cheesy finish Ingredients (7): 1 can chickpeas, drained and dried 1 tablespoon olive oil ½ teaspoon salt ½ teaspoon paprika ¼ teaspoon garlic powder ¼ cup grated Parmesan 1 tablespoon lemon juice Prep time: 5 minutes Cook time: 30–35 minutes Instructions: Heat…
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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 32B1,590 words
Okay, let's rewind history and place the invention of the transistor firmly in 1920 instead of 1947. This is a massive shift with cascading effects. Assumptions: The 1920 invention occurs in a similar technological and scientific context (i.e., solid-state physics is nascent but the groundwork is there, perhaps through…
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GPT-6 Luna1,472 words
The most important caveat is that inventing a transistor is not the same as inventing the modern semiconductor industry. A device demonstrated in 1920 might be a crude, low-power, unreliable point-contact transistor.
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 32B1,807 words
Okay, this is an incredibly challenging situation with immense pressure from multiple fronts. My priority is unwavering: patient safety comes first, followed by mitigating harm and navigating the crisis with integrity. Delay is not an option when patient safety is potentially compromised.
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GPT-6 Luna1,930 words
I would not wait six months for more data. A potentially fatal signal affecting a drug used by millions requires immediate safety assessment, prompt engagement with regulators, and a plan to inform patients and clinicians.
Read the full answer

Advanced Longevity Plan (Biohacker)

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

GLM 4 32B1,864 words
Okay, here is a comprehensive 3-month longevity optimization plan designed for a biohacker. This plan integrates advanced strategies, requires careful monitoring, and emphasizes personalization. Crucially, this is a theoretical plan.
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GPT-6 Luna1,874 words
12-week longevity and performance plan This plan is for a generally healthy adult who wants to improve fitness, metabolic health, sleep, and cognitive performance—not a substitute for medical care or a promise to slow aging.
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Our Verdict
GPT-6 Luna
GPT-6 Luna
GLM 4 32B
GLM 4 32BRunner-up

Not enough votes to call it. On the specs, GPT-6 Luna has the edge: newer, bigger context window.

GLM 4 32B costs 5.0x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

GLM 4 32B
Input
$0.10
Output
$0.10
5.0× cheaper
GPT-6 Luna
Input
$0.10
Output
$0.50
Where to run it

3 hosts, cheapest first

GLM 4 32B

No hosts listed on OpenRouter.

GPT-6 Luna3 hosts
HostInOutContextUptime
Azure AI Foundry$0.10 in·$0.50 out·1.1M·88.4% upOpenAI$0.10 in·$0.50 out·1.1M·99.9% upAmazon Bedrock$0.11 in·$0.55 out·1.1M·99.8% up

Per million tokens. Prices and uptime via OpenRouter, checked 25 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

GLM 4 32B is developed by Zhipu AI while GPT-6 Luna is developed by OpenAI. GLM 4 32B has a 128K token context window vs GPT-6 Luna's 1.1M. You can compare their actual outputs across 20 challenges on Rival to see how they differ in practice.

It depends on your use case. GLM 4 32B and GPT-6 Luna each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 20 challenges so you can judge which fits your needs best.

GLM 4 32B costs $0.1/M input tokens and GPT-6 Luna costs $0.1/M input tokens. GPT-6 Luna is $0.00/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 32B and GPT-6 Luna 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

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