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  5. Claude Opus 5.5vsGLM 4.6
Updated Sep 2026

Claude Opus 5.5vsGLM 4.6

GLM 4.6 is cheaper than Claude Opus 5.5 at $0.4/M vs $4/M input tokens.

Claude Opus 5.5 and GLM 4.6 compared across 19 shared prompts
SpecClaude Opus 5.5GLM 4.6
Input price$4/M tokens$0.4/M tokens
Output price$20/M tokens$1.75/M tokens
Context window1.0M tokens203K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Sep 2025
Side by side

Same prompt, both answers

Opening lines from 6 of the 19 prompts both answered. Formatting stripped, words untouched.

Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

Claude Opus 5.52,253 words
"Hive & Tide" Langoustine, Beeswax, White Chocolate & Oscietra Caviar, Hay-Baked Celeriac, Fermented Green Strawberry, Sea Buckthorn I. The Concept Most coastal menus celebrate the meeting of sea and land. This dish is about a stranger, quieter meeting: the meadow and the seabed, the bee and the langoustine.
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GLM 4.61,480 words
Michelin 3-Star Dish: "Tidal Echo" Conceptual Narrative "Tidal Echo" is a poetic interpretation of the moment a wave recedes from a remote, mineral-rich shore at dusk. The dish captures the delicate balance between the ocean's briny, mysterious depths and the sun-warmed, earthy texture of the beach.
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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 5.5300 words
Midnight Silk Noodles Creamy, tangy peanut noodles with a gentle kick, ready faster than takeout. Serves: 2 Prep time: 5 minutes Cook time: 10 minutes Total time: 15 minutes The 7 Ingredients 8 oz (225 g) spaghetti (or any long noodle) ¼ cup creamy peanut butter 3 tablespoons soy sauce 1 tablespoon honey (or sugar) 1…
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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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Mini LBO Underwrite

You are underwriting a 5-year LBO for a private equity investment committee. Company (fictional): HarborTech Services (HTS) –…

Claude Opus 5.5900 words
HarborTech Services: 5-Year LBO Underwriting Conventions: $m. Interest is charged on beginning-of-year balances, which avoids circularity. Term Loan (TL) amortization is 1% of the original $480m, or $4.8m per year. Mezz PIK accrues to principal. All FCF after mandatory debt service sweeps to the TL.
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GLM 4.6764 words
1. Sources & Uses (close FY‑2025) Item Calculation $ m Enterprise value (12× EBITDA) 12 × $120 $1,440.0 Transaction fees (2 % of EV) 0.02 × $1,440 $28.8 Total debt (5.5× EBITDA) 5.5 × $120 $660.0 – Term loan (4× EBITDA) 4 × $120 $480.0 – Mezzanine (1.5× EBITDA) 1.5 × $120 $180.0 Equity required EV – Debt + Fees $808.8…
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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…

Claude Opus 5.53,435 words
The Transistor in 1920: A Counterfactual Through 1980 First, a Reality Check on the Premise A transistor "invented" in 1920 would not have changed the world in 1920. The actual 1947 transistor rested on three foundations that did not exist yet: Quantum theory of solids.
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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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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 5.51,442 words
How Large Language Models Work: Three Explanations For the Experienced Software Engineer Think of an LLM as a single, very large pure function: f(tokens[0..n]) → probability distribution over tokens[n+1]. Text is chunked into tokens (roughly word fragments, from a vocabulary of about 100k).
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GLM 4.6793 words
For the Experienced Software Engineer Think of an LLM's training process as a massive, distributed compression and compilation task. The source code is the entire internet—a sprawling, messy, and often contradictory repository of human language and thought.
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Adversarial Contract Review

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

Claude Opus 5.54,420 words
Contractor-Side Review of the Software Consulting Agreement Overall assessment: This agreement is heavily one-sided. Nearly every clause shifts risk, cost, or control to the Contractor, and several provisions interact to create compounding exposure.
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GLM 4.61,669 words
Of course. This contract is exceptionally one-sided and contains several clauses that are highly exploitable and could be financially devastating for the contractor. Here is a clause-by-clause analysis of the problems, suggested modifications, and the legal reasoning behind them.
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Our Verdict
Claude Opus 5.5
Claude Opus 5.5
GLM 4.6
GLM 4.6

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

GLM 4.6 costs 11x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

Claude Opus 5.5
Input
$4.00
Output
$20.00
GLM 4.6
Input
$0.40
10× cheaper
Output
$1.75
11× cheaper

GLM 4.6 is cheaper on both: 10× input, 11× output.

Where to run it

8 hosts, cheapest first

Claude Opus 5.54 hosts
HostInOutContextUptime
Amazon Bedrock$4.00 in·$20.00 out·1M·99.8% upAzure AI Foundry$4.00 in·$20.00 out·1M·100% upAnthropic$4.00 in·$20.00 out·1M·100% upGoogle Vertex AI$4.00 in·$20.00 out·1M·100% up
GLM 4.64 hosts
HostInOutContextUptime
VVenicefp4$0.43 in·$1.75 out·198k·99.9% upDDeepInfrafp4$0.50 in·$2.00 out·203k·99.8% upNNovitabf16$0.55 in·$2.20 out·205k·95.2% upZ.aifp4$0.60 in·$2.20 out·203k·99% up

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

Research

What we learned reading every model

FAQ

Common questions

Claude Opus 5.5 is developed by Anthropic while GLM 4.6 is developed by Zhipu AI. Claude Opus 5.5 has a 1.0M token context window vs GLM 4.6's 203K. You can compare their actual outputs across 19 challenges on Rival to see how they differ in practice.

It depends on your use case. Claude Opus 5.5 and GLM 4.6 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 19 challenges so you can judge which fits your needs best.

Claude Opus 5.5 costs $4/M input tokens and GLM 4.6 costs $0.4/M input tokens. GLM 4.6 is $3.60/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 5.5 and GLM 4.6 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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