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  5. Claude Opus 5.5vsKimi K2.7 Code
Updated Sep 2026

Claude Opus 5.5vsKimi K2.7 Code

Kimi K2.7 Code is cheaper than Claude Opus 5.5 at $0.95/M vs $4/M input tokens.

Claude Opus 5.5 and Kimi K2.7 Code compared across 19 shared prompts
SpecClaude Opus 5.5Kimi K2.7 Code
Input price$4/M tokens$0.95/M tokens
Output price$20/M tokens$4/M tokens
Context window1.0M tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedSep 2026Jun 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 19 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…

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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Kimi K2.7 Code218 words
Sunshine Chickpea & Rice Pilaf A cozy, one-pot pantry meal that’s earthy, lightly spiced, and satisfying. Ingredients (7 pantry staples) 1 can (15 oz) chickpeas, drained and rinsed 1 can (14.5 oz) diced tomatoes, with juices 1 cup long-grain white rice 1 small yellow onion, diced 2 cloves garlic, minced 2 tbsp olive…
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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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Kimi K2.7 Code1,291 words
Aurora over the Boreal Forest Arctic Char • Birch-Sap & Horseradish Meringue • Fermented Sea Buckthorn • Black Garlic–Parsnip Soil • Dill Ash • Rye-Malt Tuile A dish designed for a Michelin 3-star tasting menu: technically demanding, visually striking, and built around an unexpected Nordic flavor story—silky cold-water…
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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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Kimi K2.7 Code1,566 words
Counterfactual: The Transistor Invented in 1920 Core assumption: A practical solid-state amplifying/switching device—the transistor—is demonstrated in a major industrial lab around 1920–1922, is patented by 1925, and is in modest mass production by the early 1930s.
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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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Kimi K2.7 Code1,593 words
Disclaimer: This is a strategic role-play and crisis-management framework, not legal, medical, or securities advice. In a real situation I would rely on qualified FDA/regulatory, securities, and product-liability counsel, and the company’s Chief Medical Officer and Patient Safety team.
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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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Kimi K2.7 Code880 words
For the experienced software engineer You can think of a large language model as a distributed compression engine that has been forced to become a pattern-matching oracle. During training, it is shown trillions of tokens of text and is optimized for one task: predict the next token given all previous tokens.
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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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Kimi K2.7 Code2,205 words
Disclaimer: This is a general educational analysis of contract terms, not legal advice. Enforceability varies by jurisdiction, and a contractor should have a qualified attorney review and negotiate any agreement before signing.
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Our Verdict
Claude Opus 5.5
Claude Opus 5.5
Kimi K2.7 Code
Kimi K2.7 Code

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

Kimi K2.7 Code costs 5.0x 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
Kimi K2.7 Code
Input
$0.95
4.2× cheaper
Output
$4.00
5.0× cheaper

Kimi K2.7 Code is cheaper on both: 4.2× input, 5.0× output.

Where to run it

19 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
Kimi K2.7 Code15 hosts
HostInOutContextUptime
IInceptronint4$0.66 in·$3.30 out·262k·99.9% upDDeepInfrafp4$0.68 in·$3.40 out·262k·97.9% upCCoreWeaveint4$0.71 in·$3.50 out·262k·99.9% upSStreamLake$0.71 in·$3.00 out·256k·99.7% upVVeniceint4$0.75 in·$3.50 out·256k·90.9% upMModelRunfp4$0.85 in·$3.75 out·262k·99.9% up
9 more hostsFewer hosts
SSiliconFlowfp8$0.86 in·$3.80 out·262k·100% upNNovitaint4$0.91 in·$3.84 out·262k·100% upAlibaba Cloudfp8$0.95 in·$4.00 out·262k·99.3% upBBasetenfp4$0.95 in·$4.00 out·262k·100% upCloudflare Workers AI$0.95 in·$4.00 out·262k·100% upFFireworks$0.95 in·$4.00 out·262k·93% upGGMI Cloudfp8$0.95 in·$4.00 out·262k·100% upMoonshot AIint4$0.95 in·$4.00 out·262k·100% upNNebiusfp4$0.95 in·$4.00 out·262k·97.7% 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 Kimi K2.7 Code is developed by Moonshot AI. Claude Opus 5.5 has a 1.0M token context window vs Kimi K2.7 Code's 262K. 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 Kimi K2.7 Code 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 Kimi K2.7 Code costs $0.95/M input tokens. Kimi K2.7 Code is $3.05/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 Kimi K2.7 Code 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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