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  5. GLM 5.3vsKimi K2.7 Code
Updated Aug 2026

GLM 5.3vsKimi K2.7 Code

GLM 5.3 is cheaper than Kimi K2.7 Code at $0.6538/M vs $0.95/M input tokens.

GLM 5.3 and Kimi K2.7 Code compared across 13 shared prompts
SpecGLM 5.3Kimi K2.7 Code
Input price$0.6538/M tokens$0.95/M tokens
Output price$2.0548/M tokens$4/M tokens
Context window1.3M tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedAug 2026Jun 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…

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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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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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 5.3210 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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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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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 5.3415 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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Kimi K2.7 Code596 words
30-Day Health & Longevity Starter Plan Core idea: Don’t overhaul everything at once. Build 3 small, repeatable habits in Nutrition, Movement, and Sleep/Stress Recovery. Aim for “better most days,” not perfect. Nutrition: Eat Mostly Whole Foods, Protein & Plants This week: Add before you subtract.
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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 5.31,346 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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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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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 5.31,164 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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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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Advanced Longevity Plan (Biohacker)

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

GLM 5.3851 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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Kimi K2.7 Code2,819 words
3‑Month Advanced Longevity & Performance Protocol for the Serious Biohacker Disclaimer: This is an educational, high‑information blueprint, not medical advice. Many interventions below (strict ketosis, prolonged fasting, high‑dose supplements, off‑label medications, intense training) have contraindications.
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Our Verdict
GLM 5.3
GLM 5.3
Kimi K2.7 Code
Kimi K2.7 Code

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

Too close to call
API pricing

Cost per 1M tokens

GLM 5.3
Input
$0.65
1.5× cheaper
Output
$2.05
1.9× cheaper
Kimi K2.7 Code
Input
$0.95
Output
$4.00

GLM 5.3 is cheaper on both: 1.5× input, 1.9× output.

Where to run it

44 hosts, cheapest first

GLM 5.330 hosts
HostInOutContextUptime
Baidu Qianfanfp8$0.65 in·$2.05 out·1M·99.8% upMMorph$0.65 in·$2.06 out·1M·99.6% upRRekafp8$0.76 in·$2.57 out·262k·98.5% upNNovitafp8$0.78 in·$2.46 out·1M·96.4% upIio.netfp8$0.82 in·$2.77 out·262k·99.4% upPPhala$0.84 in·$2.64 out·1M·99.5% up
24 more hostsFewer hosts
DDeepInfrafp4$0.90 in·$3.00 out·1M·97.9% upDDigitalOcean$0.91 in·$2.86 out·1M·80.2% upIInceptronfp4$1.01 in·$3.29 out·1M·98.8% upSSail Researchfp8$1.02 in·$3.29 out·1M·96.7% upGGMI Cloudfp8$1.05 in·$3.30 out·1M·99.1% upSSiliconFlowfp8$1.12 in·$3.52 out·1M·99.6% upAlibaba Cloud$1.19 in·$3.74 out·1M·100% upFFriendli$1.26 in·$3.96 out·1M·100% upAAkashMLfp8$1.30 in·$4.40 out·1M·99.9% upAAtlasCloudfp8$1.40 in·$4.40 out·1M·99.2% upBBasetenfp4$1.40 in·$4.40 out·1M·99.6% upCloudflare Workers AI$1.40 in·$4.40 out·1.3M·100% upCCrusoefp4$1.40 in·$4.40 out·1M·97.4% upFFireworks$1.40 in·$4.40 out·1M·99.6% upMistralnvfp4$1.40 in·$4.40 out·1M·99.8% upModal$1.40 in·$4.40 out·1M·97.7% upPParasailfp8$1.40 in·$4.40 out·1M·98.8% upTTogether$1.40 in·$4.40 out·1M·97.7% upVVenice$1.40 in·$4.40 out·1M·77.5% upWWafer$1.40 in·$4.40 out·1M·99.2% upZ.aifp8$1.40 in·$4.40 out·1M·99.9% upIInferenceNetfp4degraded$0.90 in·$3.00 out·1M·95.8% upMMakorafp4degraded$1.05 in·$4.20 out·980k·92.9% upDDecartfp4degraded$1.19 in·$3.74 out·1M·97.8% up
Kimi K2.7 Code14 hosts
HostInOutContextUptime
DDeepInfrafp4$0.68 in·$3.40 out·262k—IInceptronint4$0.71 in·$3.30 out·262k·99.8% upCCoreWeaveint4$0.71 in·$3.50 out·262k·99.9% upSStreamLake$0.71 in·$3.00 out·256k·99.8% upVVeniceint4$0.75 in·$3.50 out·256k·95.9% upMModelRunfp4$0.85 in·$3.75 out·262k·100% up
8 more hostsFewer hosts
SSiliconFlowfp8$0.86 in·$3.80 out·262k·99.9% upNNovitaint4$0.91 in·$3.84 out·262k·100% upAlibaba Cloudfp8$0.95 in·$4.00 out·262k·99.9% upBBasetenfp4$0.95 in·$4.00 out·262k·99.9% upCloudflare Workers AI$0.95 in·$4.00 out·262k·100% upFFireworks$0.95 in·$4.00 out·262k·95.6% upGGMI Cloudfp8$0.95 in·$4.00 out·262k·100% upMoonshot AIint4$0.95 in·$4.00 out·262k·100% up

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

Research

What we learned reading every model

FAQ

Common questions

GLM 5.3 is developed by Zhipu AI while Kimi K2.7 Code is developed by Moonshot AI. GLM 5.3 has a 1.3M token context window vs Kimi K2.7 Code's 262K. 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 5.3 and Kimi K2.7 Code 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 5.3 costs $0.6538/M input tokens and Kimi K2.7 Code costs $0.95/M input tokens. GLM 5.3 is $0.30/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 5.3 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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