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  5. GLM 5.3vsGrok 4.7
Updated Sep 2026

GLM 5.3vsGrok 4.7

GLM 5.3 is cheaper than Grok 4.7 at $0.6538/M vs $1.6/M input tokens.

GLM 5.3 and Grok 4.7 compared across 10 shared prompts
SpecGLM 5.3Grok 4.7
Input price$0.6538/M tokens$1.6/M tokens
Output price$2.0548/M tokens$4.8/M tokens
Context window1.3M tokens500K tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedAug 2026Sep 2026
Side by side

Same prompt, both answers

Opening lines from 5 of the 10 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
Grok 4.7129 words
Pantry Gold Honey Biscuits A sweet, buttery, slightly salty biscuit that tastes like it took more effort than it did. Ingredients (7) 2 cups all-purpose flour 1 tbsp baking powder ½ tsp salt ¼ cup sugar ½ cup butter (cold) ¾ cup milk 2 tbsp honey Time: about 10 minutes prep, 12–15 minutes bake Instructions Heat the…
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
Grok 4.71,399 words
This design will lose edits, split users into inconsistent views, and fall over under concurrent writing. The core problems are clock-based conflict resolution, per-server WebSocket fan-out, polling as the sync path, and treating documents as full HTML snapshots.
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
Grok 4.7442 words
1-month beginner plan for better health and longevity Focus on three foundations: nutrition, movement, and sleep. Aim for consistency over perfection. If you have a medical condition, check with a clinician before big changes. Week-by-week rhythm Week 1: Build awareness and one easy habit in each area.
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.
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Grok 4.71,173 words
1. Experienced software engineer An LLM is a stateless function from a token sequence to a probability distribution over the next token. Training is a giant batch job: you stream text, run a forward pass, compare the predicted distribution to the actual next token with cross-entropy, and push gradients through billions…
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
Grok 4.7599 words
Three weakest claims 1. “Predict what you want to type before you think it” (Slide 1) This is scientifically incoherent, not just ambitious. Non-invasive EEG decodes neural activity that is already underway (motor imagery, attempted speech, attention).
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Our Verdict
GLM 5.3
GLM 5.3
Grok 4.7
Grok 4.7

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
2.4× cheaper
Output
$2.05
2.3× cheaper
Grok 4.7
Input
$1.60
Output
$4.80

GLM 5.3 is cheaper on both: 2.4× input, 2.3× output.

Where to run it

31 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
Grok 4.71 host
HostInOutContextUptime
xAI$1.60 in·$4.80 out·500k·99.1% 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 Grok 4.7 is developed by xAI. GLM 5.3 has a 1.3M token context window vs Grok 4.7's 500K. You can compare their actual outputs across 10 challenges on Rival to see how they differ in practice.

It depends on your use case. GLM 5.3 and Grok 4.7 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 10 challenges so you can judge which fits your needs best.

GLM 5.3 costs $0.6538/M input tokens and Grok 4.7 costs $1.6/M input tokens. GLM 5.3 is $0.95/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 Grok 4.7 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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Model pages

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