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  5. Claude Opus 5.5vsGLM 5.1
Updated Sep 2026

Claude Opus 5.5vsGLM 5.1

GLM 5.1 is cheaper than Claude Opus 5.5 at $1.4/M vs $4/M input tokens.

Claude Opus 5.5 and GLM 5.1 compared across 18 shared prompts
SpecClaude Opus 5.5GLM 5.1
Input price$4/M tokens$1.4/M tokens
Output price$20/M tokens$4.4/M tokens
Context window1.0M tokens203K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Apr 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 18 prompts both answered. Formatting stripped, words untouched.

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 5.1499 words
Year-by-Year LBO Model Entry Sources & Uses Enterprise Value: $1,440.0m (12.0x $120m) Transaction Fees: $28.8m (2.0% of EV, funded by equity) Total Uses: $1,468.8m Term Loan (TL): $480.0m (4.0x) Mezzanine (Mezz): $180.0m (1.5x) Total Equity: $808.8m Operating & Cash Flow Projections ($ millions) Metric FY2026 FY2027…
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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 5.11,321 words
Dish Title: Resonance of the Littoral Zone Course: Main Course (Fish) Wine Pairing: Aged Hunter Valley Semillon or Coastal Jura Chardonnay Conceptual Narrative The littoral zone is the intersection of land and sea—a violent, beautiful threshold where tides batter ancient stone, and tenacious flora clings to saline…
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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 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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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 5.51,853 words
The Next 48 Hours: CEO Action Plan The Core Decision We disclose. The question is how to do it well, not whether. Before the schedule, here are the three facts that drive every decision below. 1. The harm is concrete.
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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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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 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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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 5.11,442 words
This contract is heavily one-sided and contains numerous clauses that are either inherently exploitative or give the Client excessive discretionary power to the detriment of the Contractor. Below is a clause-by-clause analysis of the exploitable terms, suggested modifications, and the legal reasoning behind them.
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Our Verdict
Claude Opus 5.5
Claude Opus 5.5
GLM 5.1
GLM 5.1Runner-up

Not enough votes to call it. On the specs, Claude Opus 5.5 has the edge: newer, bigger context window, major provider backing.

GLM 5.1 costs 4.5x 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 5.1
Input
$1.40
2.9× cheaper
Output
$4.40
4.5× cheaper

GLM 5.1 is cheaper on both: 2.9× input, 4.5× output.

Where to run it

18 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 5.114 hosts
HostInOutContextUptime
Baidu Qianfanfp8$0.96 in·$3.03 out·203k·99.9% upSStreamLakefp8$0.97 in·$3.04 out·200k·99.8% upCChutesfp8$0.98 in·$3.08 out·203k·91.3% upDDeepInfrafp4$1.05 in·$3.50 out·203k·99.9% upSSiliconFlowfp8$1.19 in·$3.74 out·205k·100% upPPhala$1.21 in·$4.20 out·203k·89.8% up
8 more hostsFewer hosts
AAtlasCloudfp8$1.26 in·$3.96 out·203k·99.3% upAlibaba Cloudfp8$1.33 in·$4.18 out·203k·99.7% upNNovitafp8$1.38 in·$4.40 out·205k·99.5% upFFriendli$1.40 in·$4.40 out·203k·100% upGGMI Cloudfp8$1.40 in·$4.40 out·203k·98.9% upNNebiusfp8$1.40 in·$4.40 out·203k·97.1% upZ.aifp8$1.40 in·$4.40 out·203k·99.9% upVVenicefp8$1.40 in·$4.40 out·200k·95.5% 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 5.1 is developed by Z.ai. Claude Opus 5.5 has a 1.0M token context window vs GLM 5.1's 203K. You can compare their actual outputs across 18 challenges on Rival to see how they differ in practice.

It depends on your use case. Claude Opus 5.5 and GLM 5.1 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 18 challenges so you can judge which fits your needs best.

Claude Opus 5.5 costs $4/M input tokens and GLM 5.1 costs $1.4/M input tokens. GLM 5.1 is $2.60/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 5.1 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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