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  5. GLM 5.3vsMiniMax M2-her
Updated Aug 2026

GLM 5.3vsMiniMax M2-her

MiniMax M2-her is cheaper than GLM 5.3 at $0.3/M vs $0.6538/M input tokens.

GLM 5.3 and MiniMax M2-her compared across 13 shared prompts
SpecGLM 5.3MiniMax M2-her
Input price$0.6538/M tokens$0.3/M tokens
Output price$2.0548/M tokens$1.2/M tokens
Context window1.3M tokens66K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedAug 2026Jan 2026
Side by side

Same prompt, both answers

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

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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MiniMax M2-her127 words
adjusts tie Hour 1-2: Meet legal and ethics. Hour 3-4: Review data. Hour 5-6: Notify regulators. Hour 7-8: Draft patient letter. Hour 9-10: Prepare PR team. Hour 11-12: Inform board early. Hour 13-14: Train patient hotline. Hour 15-16: Call key investors. Hour 17-18: Draft earnings script.
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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…
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MiniMax M2-her67 words
The user wants a basic 1-month plan for better health and longevity. Let's think step by step. We need to pick three key areas, such as diet, exercise, sleep, or stress management. For each area, we can include specific, beginner-friendly tips. Let's start with nutrition, then physical activity, and sleep.
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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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MiniMax M2-her822 words
Alright, let’s rewind the clock and give the transistor a 1920s debut. This is going to reshape the world in some pretty wild ways. Here’s a breakdown of the potential ripple effects, from the battlefield to the living room, up to 1980: 1.
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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 5.3851 words
3-Month Advanced Longevity & Performance Optimization Protocol Note: This is an educational framework. Get baseline bloodwork and consult a physician before starting supplements/fasting, especially with any medical conditions or medications.
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MiniMax M2-her237 words
3-Month Longevity & Biohacking Protocol Month 1: Metabolic & Cellular Optimization Diet Protocol: Micronutrient Stack: Resveratrol (500mg BID) + NMN (500mg daily) + CoQ10 (200mg) + Omega-3s (2g EPA/DHA). Fasting Regimen: 16:8 IF daily + quarterly 72-hour fasts.
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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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MiniMax M2-her1,861 words
For the Experienced Software Engineer: Large language models learn by training on vast amounts of text data to predict the next word in a sequence. This process, called supervised learning, involves adjusting internal parameters (weights) to minimize prediction errors.
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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 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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MiniMax M2-her34 words
Okay, I'd love to help you create a simple recipe. Before I do, could you tell me a few ingredients you'd be happy to use? That'll help me come up with something you'll enjoy.
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Our Verdict
GLM 5.3
GLM 5.3
MiniMax M2-her
MiniMax M2-herRunner-up

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

Too close to call
API pricing

Cost per 1M tokens

GLM 5.3
Input
$0.65
Output
$2.05
MiniMax M2-her
Input
$0.30
2.2× cheaper
Output
$1.20
1.7× cheaper

MiniMax M2-her is cheaper on both: 2.2× input, 1.7× output.

Where to run it

31 hosts, cheapest first

GLM 5.330 hosts
HostInOutContextUptime
Baidu Qianfanfp8$0.65 in·$2.05 out·1M·99.8% upRRekafp8$0.76 in·$2.57 out·262k·99.4% upNNovitafp8$0.78 in·$2.46 out·1M·99.9% upIio.netfp8$0.82 in·$2.77 out·262k·99.7% upPPhala$0.84 in·$2.64 out·1M·99.5% upMMorph$0.86 in·$2.69 out·1M·99.8% up
24 more hostsFewer hosts
DDeepInfrafp4$0.90 in·$3.00 out·1M·98% upIInferenceNetfp4$0.90 in·$3.00 out·1M·97.9% upDDigitalOcean$0.91 in·$2.86 out·1M·99.7% upIInceptronfp4$1.01 in·$3.29 out·1M·99.3% upSSail Researchfp8$1.02 in·$3.29 out·1M·99.9% upGGMI Cloudfp8$1.05 in·$3.30 out·1M·99.5% upMMakorafp4$1.05 in·$4.20 out·980k·97.8% upSSiliconFlowfp8$1.12 in·$3.52 out·1M·99.6% upAlibaba Cloud$1.19 in·$3.74 out·1M·100% upDDecartfp4$1.19 in·$3.74 out·1M·99% 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·99.5% upBBasetenfp4$1.40 in·$4.40 out·1M·99.7% upCloudflare Workers AI$1.40 in·$4.40 out·1.3M·99.9% upCCrusoefp4$1.40 in·$4.40 out·1M·98.2% upFFireworks$1.40 in·$4.40 out·1M·99.6% upMistralnvfp4$1.40 in·$4.40 out·1M·99.8% upModal$1.40 in·$4.40 out·1M·99% upPParasailfp8$1.40 in·$4.40 out·1M·99.4% upTTogether$1.40 in·$4.40 out·1M·98.2% upVVenice$1.40 in·$4.40 out·1M·98.8% upWWafer$1.40 in·$4.40 out·1M·99.9% upZ.aifp8$1.40 in·$4.40 out·1M·99.9% up
MiniMax M2-her1 host
HostInOutContextUptime
MiniMax$0.30 in·$1.20 out·66k·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 is developed by Zhipu AI while MiniMax M2-her is developed by MiniMax. GLM 5.3 has a 1.3M token context window vs MiniMax M2-her's 66K. 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 MiniMax M2-her 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 MiniMax M2-her costs $0.3/M input tokens. MiniMax M2-her is $0.35/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 MiniMax M2-her 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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