Skip to content
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare Models
  • All Models
  • Image Comparison
  • Audio Comparison
  • Image Generation
  • Best AI For...
  • Arena
  • API Pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model Updates
  • Provider Status
  • AI Creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy Policy
  • Terms
  • RSS Feed
  1. Home
  2. /
  3. Compare
  4. /
  5. GLM 5.3vsKimi K2.6
Updated Aug 2026

GLM 5.3vsKimi K2.6

GLM 5.3 is cheaper than Kimi K2.6 at $0.6538/M vs $0.95/M input tokens.

GLM 5.3 and Kimi K2.6 compared across 13 shared prompts
SpecGLM 5.3Kimi K2.6
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 2026Apr 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 13 prompts both answered. Formatting stripped, words untouched.

Debug This Architecture

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

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).
Read the full answer
Kimi K2.62,081 words
Here is a systematic breakdown of the critical flaws in this architecture, categorized by the type of risk they introduce. The "2-Second Blindness" – Cross-Server Sync via DB Polling Category: Race Condition / Scaling Bottleneck / Failure Mode Problem: Because WebSocket servers do not communicate with one another…
Read the full answer

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.
Read the full answer
Kimi K2.62,483 words
My north star: We disclose—fast, fully, and on our terms. The “wait for more data” option is a mirage. It exposes the company to criminal liability under FDA adverse-event reporting rules, potential DOJ investigation, securities fraud charges, and derivative litigation that could destroy the firm.
Read the full answer

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.
Read the full answer
Kimi K2.6286 words
The Blanket Fort Stew (Rustic One-Pot Pasta e Ceci) A warm, garlicky hug of a meal built from true shelf-stable staples. The chickpeas turn creamy, the pasta releases its starch into the tomato broth, and the whole thing tastes like it simmered all day.
Read the full answer

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…
Read the full answer
Kimi K2.6549 words
The Foundation Month: A 30-Day Longevity Starter Plan Philosophy: Don’t overhaul your life. Stack one small win at a time so habits stick. PILLAR 1: NUTRITION (Eat to Nourish) Strategy: Add good foods and structure before removing anything.
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…

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.
Read the full answer
Kimi K2.6877 words
1. Experienced Software Engineer Think of an LLM not as a program you write, but as a binary you compile from the entire internet. Instead of hand-crafting if/then rules, you define a single objective: given the context "The cat sat on the...", output the probability distribution over every possible next token, and…
Read the full answer

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…
Read the full answer
Kimi K2.62,095 words
Counterfactual: The Transistor, 1920–1980 Assume a working solid-state amplifying device—crude, germanium-based, poorly understood—is demonstrated at Bell Labs or GE in 1920, a decade before the quantum-mechanical theory that explains it.
Read the full answer
Our Verdict
GLM 5.3
GLM 5.3
Kimi K2.6
Kimi K2.6Runner-up

Not enough votes to call it. On the specs, GLM 5.3 has the edge: newer, bigger context window, major provider backing.

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 K2.6
Input
$0.95
Output
$4.00

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

Where to run it

51 hosts, cheapest first

GLM 5.330 hosts
HostInOutContextUptime
Baidu Qianfanfp8$0.65 in·$2.05 out·1M·99.8% upRRekafp8$0.76 in·$2.57 out·262k·99.3% upNNovitafp8$0.78 in·$2.46 out·1M·99.9% upIio.netfp8$0.82 in·$2.77 out·262k·99.7% upPPhala$0.84 in·$2.64 out·1M·99.5% upMMorph$0.86 in·$2.69 out·1M·99.8% up
24 more hostsFewer hosts
DDeepInfrafp4$0.90 in·$3.00 out·1M·98% upIInferenceNetfp4$0.90 in·$3.00 out·1M·97.9% upDDigitalOcean$0.91 in·$2.86 out·1M·99.7% upIInceptronfp4$1.01 in·$3.29 out·1M·99.3% upSSail Researchfp8$1.02 in·$3.29 out·1M·99.9% upGGMI Cloudfp8$1.05 in·$3.30 out·1M·99.5% upMMakorafp4$1.05 in·$4.20 out·980k·97.8% upSSiliconFlowfp8$1.12 in·$3.52 out·1M·99.7% upAlibaba Cloud$1.19 in·$3.74 out·1M·100% upDDecartfp4$1.19 in·$3.74 out·1M·99.1% 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·99.5% upBBasetenfp4$1.40 in·$4.40 out·1M·99.6% upCloudflare Workers AI$1.40 in·$4.40 out·1.3M·99.9% upCCrusoefp4$1.40 in·$4.40 out·1M·98.2% 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·99% upTTogether$1.40 in·$4.40 out·1M·98.2% upVVenice$1.40 in·$4.40 out·1M·98.9% upWWafer$1.40 in·$4.40 out·1M·99.9% upZ.aifp8$1.40 in·$4.40 out·1M·99.9% upPParasailfp8degraded$1.40 in·$4.40 out·1M·99.2% up
Kimi K2.621 hosts
HostInOutContextUptime
Baidu Qianfanfp4$0.43 in·$1.82 out·262k·100% upIInceptronint4$0.43 in·$2.38 out·262k·99.4% upCChutesint4$0.50 in·$2.85 out·262k·98.4% upDDigitalOcean$0.57 in·$2.40 out·262k·98.6% upDDecartfp4$0.59 in·$2.47 out·262k·94.2% upSStreamLakefp8$0.60 in·$2.52 out·256k·98.5% up
15 more hostsFewer hosts
CCoreWeavefp4$0.65 in·$3.41 out·262k·99.8% upCCrusoebf16$0.70 in·$3.50 out·262k·98.9% upDDeepInfrafp4$0.75 in·$3.50 out·262k·96.8% upPParasailint4$0.75 in·$3.50 out·262k·99.6% upVVeniceint4$0.75 in·$3.50 out·256k·86.9% upSSiliconFlowfp8$0.77 in·$3.40 out·262k·99.8% upNNovita$0.80 in·$3.40 out·262k·99.7% upAAtlasCloudint4$0.95 in·$4.00 out·262k·96.5% upBBasetenfp4$0.95 in·$4.00 out·262k·98.2% upCloudflare Workers AI$0.95 in·$4.00 out·262k·99.9% upFFireworks$0.95 in·$4.00 out·262k·0% upMoonshot AIint4$0.95 in·$4.00 out·262k·99.9% upSSail Researchint4$1.00 in·$4.00 out·262k·100% upPPhala$1.09 in·$4.60 out·262k·99.5% upGGMI Cloudfp8degraded$0.85 in·$3.60 out·262k·89% 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 K2.6 is developed by Moonshot AI. GLM 5.3 has a 1.3M token context window vs Kimi K2.6'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 K2.6 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 K2.6 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 K2.6 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.

Keep exploring

More comparisons

Against the newest arrivals

GLM 5.3 logoDeepSeek V4 Flash Vision Exp logo
GLM 5.3 vs DeepSeek V4 Flash Vision ExpLanded Sep 2026
Kimi K2.6 logoSolar Pro 4 logo
Kimi K2.6 vs Solar Pro 4Landed Sep 2026
GLM 5.3 logoHy3 logo
GLM 5.3 vs Hy3Landed Sep 2026
Kimi K2.6 logoQwen3.7 Flash logo
Kimi K2.6 vs Qwen3.7 FlashLanded Sep 2026
GLM 5.3 logoLing 3.0 Flash logo
GLM 5.3 vs Ling 3.0 FlashLanded Sep 2026
Kimi K2.6 logoMuse Glimmer 30B logo
Kimi K2.6 vs Muse Glimmer 30BLanded Sep 2026
GLM 5.3 logoTernary Bonsai 2 27B logo
GLM 5.3 vs Ternary Bonsai 2 27BLanded Sep 2026
Kimi K2.6 logoGLM 5.3 Flash logo
Kimi K2.6 vs GLM 5.3 FlashLanded Sep 2026

Same lab, same size, long tail

GLM 5.3 logoGLM 5.3 Flash logo
GLM 5.3 vs GLM 5.3 FlashSame lab
GLM 5.3 logoGLM 5.3 FlashX logo
GLM 5.3 vs GLM 5.3 FlashXSame lab
Kimi K2.6 logoKimi K3 logo
Kimi K2.6 vs Kimi K3Same lab
Kimi K2.6 logoKimi K2.7 Code logo
Kimi K2.6 vs Kimi K2.7 CodeSame lab
Kimi K2.6 logoGPT-1 logo
Kimi K2.6 vs GPT-1New provider
Kimi K2.6 logoOptimus Alpha logo
Kimi K2.6 vs Optimus AlphaSame size
GLM 5.3 logoOwl Alpha logo
GLM 5.3 vs Owl AlphaSame size
GLM 5.3 logoOx Alpha logo
GLM 5.3 vs Ox AlphaSame size

Model pages

GLM 5.3 logo
GLM 5.313 outputs, specs and price
Kimi K2.6 logo
Kimi K2.658 outputs, specs and price
Rival
How it worksPrivacyTerms
Explore all of Rival

Explore

  • Compare Models
  • All Models
  • Image Comparison
  • Audio Comparison
  • Image Generation
  • Best AI For...
  • Arena
  • API Pricing
  • Challenges

Discover

  • SubjectiveBench
  • Default Index
  • Research
  • Research downloads
  • Rival Kits
  • Find your AI taste
  • UI Glow-Up
  • VoiceLock
  • Cost Cutter
  • Agent skills
  • Benchmarks vs Vibes
  • Brief
  • Jailbreak
  • Model Updates
  • Provider Status
  • AI Creators

Connect

  • Methodology
  • Advertise
  • Partnerships
  • Privacy Policy
  • Terms
  • RSS Feed