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 5.3vsInkling
Updated Aug 2026

GLM 5.3vsInkling

GLM 5.3 is cheaper than Inkling at $0.6538/M vs $1/M input tokens.

GLM 5.3 and Inkling compared across 13 shared prompts
SpecGLM 5.3Inkling
Input price$0.6538/M tokens$1/M tokens
Output price$2.0548/M tokens$4.05/M tokens
Context window1.3M tokens1.0M tokens
WeightsOpenOpen
Free API (OpenRouter)NoYes (1 provider)
ReleasedAug 2026Jul 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 13 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…

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
Inkling186 words
Golden Jam Crumble Clouds A buttery, cinnamon-kissed oat crumble layered with sweet jam—like a hug from your pantry. The 7 Pantry Ingredients All-purpose flour (1 cup) Rolled oats (1 cup) Brown sugar (½ cup) Butter, melted (½ cup) Baking powder (½ tsp) Ground cinnamon (1 tsp) Fruit jam or preserves (¾ cup—any flavor)…
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
Inkling2,151 words
If a working point-contact transistor—small, cool, and solid-state—had emerged in 1920, the cascade would not merely “speed up” our timeline. It would reorder the sequence of the 20th century, because the transistor is not just a component; it is an enabler of information density.
Read the full answer

Startup Pitch Teardown

Here's a pitch deck summary for a startup called "MindMeld AI": **Slide 1 - Vision:** "We're building the future of human-AI collaboration.…

GLM 5.3585 words
3 Weakest Claims in the MindMeld AI Pitch "Reads your brainwaves to predict what you want to type before you think it" Why it's weak: This claim is neurologically incoherent. EEG sensors detect electrical activity on the scalp after neural firing occurs — you cannot decode intent "before" the brain generates it.
Read the full answer
Inkling856 words
Here are the three weakest claims, ordered by how severely they undermine credibility: The Core Technology Claim: 94% accuracy decoding free-form text via EEG, "before you think it," in any language (Slides 1 & 3) Why it’s weak: This violates established neuroscience and BCI engineering limits.
Read the full answer

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
Inkling1,866 words
This architecture contains fatal contradictions for real-time collaboration: server-local WebSocket state combined with round-robin load balancing, client-clock LWW, and a 2-second DB polling loop guarantee data loss, stale reads, and scaling collapse.
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
Inkling815 words
Here is a simple, 30-day “starter” plan built around the three highest-return pillars for longevity: Nutrition, Movement, and Sleep. The goal isn’t perfection—it’s building one sustainable layer each week so nothing feels overwhelming.
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
Inkling829 words
1. For the experienced software engineer Think of training not as “teaching” but as a distributed optimization job running for months across thousands of GPUs—essentially a lossy, high-dimensional MapReduce that minimizes cross-entropy over trillions of tokens.
Read the full answer
Our Verdict
GLM 5.3
GLM 5.3
Inkling
Inkling

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
2.0× cheaper
Inkling
Input
$1.00
Output
$4.05

GLM 5.3 is cheaper on both: 1.5× input, 2.0× output.

Where to run it

33 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
Inkling3 hosts
HostInOutContextUptime
DDeepInfrafp8$0.95 in·$4.05 out·524k·33.5% upBBasetenfp8$1.00 in·$4.05 out·1M·99.9% upTTogether$1.00 in·$4.05 out·524k·99.6% 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 Inkling is developed by Thinking Machines. GLM 5.3 has a 1.3M token context window vs Inkling's 1.0M. 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 Inkling 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 Inkling costs $1/M input tokens. GLM 5.3 is $0.35/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 Inkling 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
Inkling logoSolar Pro 4 logo
Inkling vs Solar Pro 4Landed Sep 2026
GLM 5.3 logoHy3 logo
GLM 5.3 vs Hy3Landed Sep 2026
Inkling logoQwen3.7 Flash logo
Inkling vs Qwen3.7 FlashLanded Sep 2026
GLM 5.3 logoLing 3.0 Flash logo
GLM 5.3 vs Ling 3.0 FlashLanded Sep 2026
Inkling logoMuse Glimmer 30B logo
Inkling vs Muse Glimmer 30BLanded Sep 2026
GLM 5.3 logoTernary Bonsai 2 27B logo
GLM 5.3 vs Ternary Bonsai 2 27BLanded Sep 2026
Inkling logoGLM 5.3 Flash logo
Inkling 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
Inkling logoClaude Opus 4.6 logo
Inkling vs Claude Opus 4.6Same size
Inkling logoHy3 logo
Inkling vs Hy3Same size
GLM 5.3 logoKimi K2.6 logo
GLM 5.3 vs Kimi K2.6Same size
GLM 5.3 logoKimi K2.7 Code logo
GLM 5.3 vs Kimi K2.7 CodeNew provider
GLM 5.3 logoKimi K3 logo
GLM 5.3 vs Kimi K3New provider
GLM 5.3 logoKimi Linear 48B A3B Instruct logo
GLM 5.3 vs Kimi Linear 48B A3B InstructNew provider

Model pages

GLM 5.3 logo
GLM 5.313 outputs, specs and price
Inkling logo
Inkling58 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