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  5. Claude Opus 4.6vsGLM 5.3
Updated Aug 2026

Claude Opus 4.6vsGLM 5.3

GLM 5.3 is cheaper than Claude Opus 4.6 at $0.6538/M vs $5/M input tokens.

Claude Opus 4.6 and GLM 5.3 compared across 13 shared prompts
SpecClaude Opus 4.6GLM 5.3
Input price$5/M tokens$0.6538/M tokens
Output price$25/M tokens$2.0548/M tokens
Context window1.0M tokens1.3M tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedFeb 2026Aug 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…

Claude Opus 4.62,995 words
48-Hour Action Plan: Immediate Disclosure Path My Governing Principle Before the hour-by-hour plan, I need to state the decision framework clearly: patient safety is not one consideration among many—it is the constraint that every other consideration must satisfy.
Read the full answer
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.
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.…

Claude Opus 4.61,395 words
Critical Analysis of MindMeld AI Pitch Deck After careful examination, here are the three weakest claims, ranked by severity: The 94% Accuracy Claim (Slide 3) — Most Problematic Why this is weak: This claim strains credulity against the entire body of published BCI research, and the lack of context makes it essentially…
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GLM 5.3585 words
3 Weakest Claims in the MindMeld AI Pitch "Reads your brainwaves to predict what you want to type before you think it" Why it's weak: This claim is neurologically incoherent. EEG sensors detect electrical activity on the scalp after neural firing occurs — you cannot decode intent "before" the brain generates it.
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…

Claude Opus 4.61,677 words
How Large Language Models Learn and Generate Text For the Experienced Software Engineer Think of training an LLM as building the world's most aggressively optimized compression algorithm, except instead of compressing files, it's compressing the statistical structure of human language.
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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…

Claude Opus 4.66,606 words
COMPREHENSIVE 3-MONTH LONGEVITY OPTIMIZATION PROTOCOL THE BIOHACKER'S BLUEPRINT v3.0 TABLE OF CONTENTS Foundation & Baseline Testing Month 1: Foundation & Calibration Month 2: Optimization & Intensification Month 3: Integration & Peak Performance Supplement Stacks & Cycling Protocols Dietary Protocols Exercise…
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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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Debug This Architecture

Here's the architecture for a real-time collaborative document editor (like Google Docs): **System Overview:** - Frontend: React SPA with…

Claude Opus 4.61,400 words
Comprehensive Architecture Review: Real-time Collaborative Document Editor This architecture has several critical flaws that would cause data loss, inconsistency, and poor user experience at scale. I'll work through every layer systematically.
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GLM 5.31,311 words
Architecture Review: Real-Time Collaborative Editor This design has serious issues across correctness, performance, and security. Let me break them down by severity. 🔴 Critical: Correctness / Data Loss Client-clock-based Last-Write-Wins (LWW) Problem: Client clocks are unreliable (skew, manual changes, timezone bugs).
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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…

Claude Opus 4.6215 words
✨ Golden Honey-Garlic Crispy Rice Bites ✨ Ingredients Rice (2 cups, cooked and cooled — ideally day-old) Soy sauce (3 tablespoons) Honey (2 tablespoons) Garlic (3 cloves, minced) Olive oil (3 tablespoons) Sesame seeds (1 tablespoon) Red pepper flakes (½ teaspoon) Instructions Prep Time: 5 minutes Cook Time: 15 minutes…
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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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Our Verdict
Claude Opus 4.6
Claude Opus 4.6
GLM 5.3
GLM 5.3

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

GLM 5.3 costs 12x less per token.

Too close to call
API pricing

Cost per 1M tokens

Claude Opus 4.6
Input
$5.00
Output
$25.00
GLM 5.3
Input
$0.65
7.6× cheaper
Output
$2.05
12× cheaper

GLM 5.3 is cheaper on both: 7.6× input, 12× output.

Where to run it

34 hosts, cheapest first

Claude Opus 4.64 hosts
HostInOutContextUptime
Amazon Bedrock$5.00 in·$25.00 out·1M·99.5% upAzure AI Foundry$5.00 in·$25.00 out·1M·99.9% upAnthropic$5.00 in·$25.00 out·1M·99.9% upGoogle Vertex AI$5.00 in·$25.00 out·1M·100% up
GLM 5.330 hosts
HostInOutContextUptime
DDeepInfrafp4$0.56 in·$2.50 out·1M·97.1% upMMorph$0.71 in·$2.24 out·1M·99.7% upRRekafp8$0.76 in·$2.57 out·262k·99.4% upSSail Researchfp8$0.77 in·$4.00 out·1M·99.8% upNNovitafp8$0.78 in·$2.46 out·1M·99.9% upIio.netfp8$0.82 in·$2.77 out·262k·99.8% up
24 more hostsFewer hosts
PPhala$0.84 in·$2.64 out·1M·99.4% upIInferenceNetfp4$0.90 in·$3.00 out·1M·98.2% upDDigitalOcean$0.91 in·$2.86 out·1M·99.7% upGGMI Cloudfp8$0.98 in·$3.08 out·1M·99.5% upIInceptronfp4$1.03 in·$3.73 out·1M·99.4% upMMakorafp4$1.05 in·$4.20 out·980k·97.1% upSSiliconFlowfp8$1.12 in·$3.52 out·1M·99.8% upDDecartfp4$1.19 in·$3.74 out·1M·99.2% 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% upBaidu Qianfanfp8$1.40 in·$4.40 out·1M·99.8% upBBasetenfp4$1.40 in·$4.40 out·1M·99.8% upCloudflare Workers AI$1.40 in·$4.40 out·1.3M·98.9% upCCrusoefp4$1.40 in·$4.40 out·1M·98.9% upFFireworks$1.40 in·$4.40 out·1M·99.5% upMistralnvfp4$1.40 in·$4.40 out·1M·99.4% upModal$1.40 in·$4.40 out·1M·99.1% upPParasailfp8$1.40 in·$4.40 out·1M·99.2% upTTogether$1.40 in·$4.40 out·1M·98.1% upVVenice$1.40 in·$4.40 out·1M·98.5% upWWafer$1.40 in·$4.40 out·1M·99.9% upZ.aifp8$1.40 in·$4.40 out·1M·99.9% upAlibaba Clouddegraded$1.19 in·$3.74 out·1M·99.5% up

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

Research

What we learned reading every model

FAQ

Common questions

Claude Opus 4.6 is developed by Anthropic while GLM 5.3 is developed by Zhipu AI. Claude Opus 4.6 has a 1.0M 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. Claude Opus 4.6 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.

Claude Opus 4.6 costs $5/M input tokens and GLM 5.3 costs $0.6538/M input tokens. GLM 5.3 is $4.35/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 Claude Opus 4.6 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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