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  5. GLM 5.1vsGLM 5.3
Updated Aug 2026

GLM 5.1vsGLM 5.3

GLM 5.3 is cheaper than GLM 5.1 at $0.6538/M vs $1.4/M input tokens.

GLM 5.1 and GLM 5.3 compared across 13 shared prompts
SpecGLM 5.1GLM 5.3
Input price$1.4/M tokens$0.6538/M tokens
Output price$4.4/M tokens$2.0548/M tokens
Context window203K tokens1.3M tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedApr 2026Aug 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 13 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 5.1265 words
Creative Name: Midnight Maple Peanut Butter Bars Prep time: 10 minutes Cook time: 0 minutes (Chill time: 30 minutes) Ingredients (Exactly 7): Rolled oats (1 cup) Creamy peanut butter (1/2 cup) Maple syrup (1/3 cup) Semi-sweet chocolate chips (1/4 cup) Vanilla extract (1 tsp) Ground cinnamon (1/2 tsp) Kosher salt (1/4…
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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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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 5.11,378 words
As CEO, my north star in this crisis is unequivocally patient safety. The "wait for more data" approach is a catastrophic trap—both ethically and legally. History (e.g., Vioxx, Fen-Phen) shows that delaying disclosure of a known severe adverse event transforms a medical safety issue into corporate fraud, manslaughter…
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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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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 5.1717 words
This 1-month plan is designed to build a foundation for longevity without overwhelming you. The secret to long-term success is consistency over intensity. Instead of overhauling your life overnight, you will add one small, manageable habit each week across three core pillars: Movement, Nourishment, and Sleep.
Read the full answer
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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Historical Counterfactual Analysis

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

GLM 5.11,208 words
To envision the invention of the transistor in 1920, we must first resolve a historical anomaly: quantum mechanics—the theoretical foundation of semiconductors—did not yet exist. For this timeline to work, we must assume a serendipitous empirical leap.
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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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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 5.1805 words
1. The Experienced Software Engineer Think of an LLM not as a chatbot, but as a massive, distributed probabilistic state machine. During training, it ingests terabytes of text and runs a continuous optimization loop to adjust billions of floating-point weights.
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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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Advanced Longevity Plan (Biohacker)

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

GLM 5.1410 words
This is a comprehensive, aggressive, and cutting-edge 3-month longevity protocol designed for an experienced biohacker. It integrates synergistic systems—metabolic flexibility, mitochondrial biogenesis, cellular senescence mitigation, and neuroplasticity—to optimize both healthspan and performance.
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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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Our Verdict
GLM 5.3
GLM 5.3
GLM 5.1
GLM 5.1Runner-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 5.1
Input
$1.40
Output
$4.40
GLM 5.3
Input
$0.65
2.1× cheaper
Output
$2.05
2.1× cheaper

GLM 5.3 is cheaper on both: 2.1× input, 2.1× output.

Where to run it

44 hosts, cheapest first

GLM 5.114 hosts
HostInOutContextUptime
Baidu Qianfanfp8$0.96 in·$3.03 out·203k·99.8% upSStreamLakefp8$0.97 in·$3.04 out·200k·99.5% upCChutesfp8$0.98 in·$3.08 out·203k·75.6% upDDeepInfrafp4$1.05 in·$3.50 out·203k·99.7% upSSiliconFlowfp8$1.19 in·$3.74 out·205k·99.9% upPPhala$1.21 in·$4.20 out·203k·74.4% up
8 more hostsFewer hosts
AAtlasCloudfp8$1.26 in·$3.96 out·203k·99.6% upAlibaba Cloudfp8$1.33 in·$4.18 out·203k·100% upNNovitafp8$1.38 in·$4.40 out·205k·99.7% upFFriendli$1.40 in·$4.40 out·203k·100% upGGMI Cloudfp8$1.40 in·$4.40 out·203k·99.1% upZ.aifp8$1.40 in·$4.40 out·203k·99.6% upVVenicefp8$1.40 in·$4.40 out·200k·97.9% upNNebiusfp8degraded$1.40 in·$4.40 out·203k·96% up
GLM 5.330 hosts
HostInOutContextUptime
Baidu Qianfanfp8$0.65 in·$2.05 out·1M·99.8% upMMorph$0.71 in·$2.24 out·1M·99.8% upRRekafp8$0.76 in·$2.57 out·262k·99.4% upSSail Researchfp8$0.77 in·$4.00 out·1M·99.9% upNNovitafp8$0.78 in·$2.46 out·1M·99.9% upIio.netfp8$0.82 in·$2.77 out·262k·99.7% up
24 more hostsFewer hosts
PPhala$0.84 in·$2.64 out·1M·99.5% upDDeepInfrafp4$0.90 in·$3.00 out·1M·98% upIInferenceNetfp4$0.90 in·$3.00 out·1M·98% upDDigitalOcean$0.91 in·$2.86 out·1M·99.8% upIInceptronfp4$1.04 in·$3.39 out·1M·99.4% upGGMI Cloudfp8$1.05 in·$3.30 out·1M·99.5% upMMakorafp4$1.05 in·$4.20 out·980k·97.3% upSSiliconFlowfp8$1.12 in·$3.52 out·1M·99.7% upAlibaba Cloud$1.19 in·$3.74 out·1M·100% upDDecartfp4$1.19 in·$3.74 out·1M·99.1% 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% upBBasetenfp4$1.40 in·$4.40 out·1M·99.7% upCloudflare Workers AI$1.40 in·$4.40 out·1.3M·99.8% upCCrusoefp4$1.40 in·$4.40 out·1M·98.3% upFFireworks$1.40 in·$4.40 out·1M·99.5% upMistralnvfp4$1.40 in·$4.40 out·1M·99.7% upModal$1.40 in·$4.40 out·1M·99% upPParasailfp8$1.40 in·$4.40 out·1M·99.1% upTTogether$1.40 in·$4.40 out·1M·98.1% 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

Per million tokens. Prices and uptime via OpenRouter, checked 22 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

GLM 5.1 is developed by Z.ai while GLM 5.3 is developed by Zhipu AI. GLM 5.1 has a 203K token context window vs GLM 5.3's 1.3M. 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 5.1 and GLM 5.3 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 5.1 costs $1.4/M input tokens and GLM 5.3 costs $0.6538/M input tokens. GLM 5.3 is $0.75/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 5.1 and GLM 5.3 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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  • Research downloads
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