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  5. GLM 5.3vsQwen3 235B A22B 2507
Updated Aug 2026

GLM 5.3vsQwen3 235B A22B 2507

Qwen3 235B A22B 2507 is cheaper than GLM 5.3 at $0.00015/M vs $0.6538/M input tokens.

GLM 5.3 and Qwen3 235B A22B 2507 compared across 13 shared prompts
SpecGLM 5.3Qwen3 235B A22B 2507
Input price$0.6538/M tokens$0.00015/M tokens
Output price$2.0548/M tokens$0.00085/M tokens
Context window1.3M tokens—
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedAug 2026Jul 2025
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.
Read the full answer
Qwen3 235B A22B 25071,177 words
CEO Action Plan: The Next 48 Hours Balancing Ethics, Legal Duty, Patient Safety, and Business Sustainability Hour 0–6: Assess the Situation and Secure Critical Data Actions: Call Emergency Secure Meeting (Virtual) with Chief Medical Officer (CMO), Chief Scientific Officer (CSO), Head of Regulatory Affairs, and Lead…
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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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Qwen3 235B A22B 2507207 words
Dish Name: Golden Garbanzo Drizzle A cozy, savory-spiced chickpea stew with a honey-lime finish — simple, satisfying, and ready in minutes. Ingredients (7 common pantry staples): 1 can (15 oz) chickpeas (garbanzo beans), drained and rinsed 1 can (15 oz) diced tomatoes (undrained) 2 tbsp olive oil 1 tsp ground cumin ½…
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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.
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Qwen3 235B A22B 2507675 words
This pitch deck for MindMeld AI is compelling and ambitious, but three claims raise significant red flags in terms of credibility, plausibility, and investor due diligence. Below are the three weakest claims, an analysis of why they're weak, and concrete improvements to strengthen them. 1.
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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).
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Qwen3 235B A22B 25071,454 words
The described architecture for a real-time collaborative document editor has several critical failure modes, race conditions, and scaling bottlenecks that compromise consistency, availability, and scalability—especially under load or in edge network conditions.
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…
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Qwen3 235B A22B 2507585 words
Here’s a simple, actionable 1-month plan focused on three foundational pillars of health and longevity: Nutrition, Movement, and Sleep & Stress. Designed for beginners, it emphasizes small, sustainable changes to build lasting habits.
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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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Qwen3 235B A22B 25071,424 words
If the transistor had been invented in 1920—27 years earlier than its actual 1947 debut—it would have catalyzed a technological revolution far ahead of schedule, profoundly altering the trajectory of the 20th century.
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Our Verdict
GLM 5.3
GLM 5.3
Qwen3 235B A22B 2507
Qwen3 235B A22B 2507

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

Qwen3 235B A22B 2507 costs 2417x less per token.

Too close to call
API pricing

Cost per 1M tokens

GLM 5.3
Input
$0.65
Output
$2.05
Qwen3 235B A22B 2507
Input
$0.000
4359× cheaper
Output
$0.001
2417× cheaper

Qwen3 235B A22B 2507 is cheaper on both: 4359× input, 2417× output.

Where to run it

39 hosts, cheapest first

GLM 5.330 hosts
HostInOutContextUptime
DDeepInfrafp4$0.56 in·$2.50 out·1M·97.1% upMMorph$0.71 in·$2.24 out·1M·99.7% upRRekafp8$0.76 in·$2.57 out·262k·99.4% upSSail Researchfp8$0.77 in·$4.00 out·1M·99.8% upNNovitafp8$0.78 in·$2.46 out·1M·99.9% upIio.netfp8$0.82 in·$2.77 out·262k·99.8% up
24 more hostsFewer hosts
PPhala$0.84 in·$2.64 out·1M·99.4% upIInferenceNetfp4$0.90 in·$3.00 out·1M·98.2% upDDigitalOcean$0.91 in·$2.86 out·1M·99.7% upGGMI Cloudfp8$0.98 in·$3.08 out·1M·99.5% upIInceptronfp4$1.03 in·$3.73 out·1M·99.4% upMMakorafp4$1.05 in·$4.20 out·980k·97.1% upSSiliconFlowfp8$1.12 in·$3.52 out·1M·99.8% upDDecartfp4$1.19 in·$3.74 out·1M·99.2% 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·99.4% upBaidu Qianfanfp8$1.40 in·$4.40 out·1M·99.8% upBBasetenfp4$1.40 in·$4.40 out·1M·99.8% upCloudflare Workers AI$1.40 in·$4.40 out·1.3M·98.9% upCCrusoefp4$1.40 in·$4.40 out·1M·98.9% upFFireworks$1.40 in·$4.40 out·1M·99.5% upMistralnvfp4$1.40 in·$4.40 out·1M·99.4% upModal$1.40 in·$4.40 out·1M·99.1% upPParasailfp8$1.40 in·$4.40 out·1M·99.2% upTTogether$1.40 in·$4.40 out·1M·98.1% upVVenice$1.40 in·$4.40 out·1M·98.5% upWWafer$1.40 in·$4.40 out·1M·99.9% upZ.aifp8$1.40 in·$4.40 out·1M·99.9% upAlibaba Clouddegraded$1.19 in·$3.74 out·1M·99.5% up
Qwen3 235B A22B 25079 hosts
HostInOutContextUptime
GGMI Cloudfp8$0.09 in·$0.35 out·262k·98.6% upDDeepInfrafp8$0.09 in·$0.55 out·262k·97.9% upNNovitafp8$0.09 in·$0.58 out·131k·98.7% upPParasailfp8$0.14 in·$0.80 out·131k·99.8% upAlibaba Cloud$0.15 in·$0.60 out·131k·99.9% upVVenicefp8$0.15 in·$0.75 out·128k·98.3% up
3 more hostsFewer hosts
NNebiusfp8$0.20 in·$0.60 out·262k·94.2% upSStreamLake$0.21 in·$0.84 out·128k·98.9% upGoogle Vertex AI$0.22 in·$0.88 out·262k·99.7% up

Per million tokens. Prices and uptime via OpenRouter, checked 23 Sep 2026.

Research

What we learned reading every model

FAQ

Common questions

GLM 5.3 is developed by Zhipu AI while Qwen3 235B A22B 2507 is developed by Qwen. 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 Qwen3 235B A22B 2507 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 Qwen3 235B A22B 2507 costs $0.00015/M input tokens. Qwen3 235B A22B 2507 is $0.65/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 Qwen3 235B A22B 2507 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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GLM 5.3 vs GLM 5.3 FlashSame lab
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Qwen3 235B A22B 2507 vs Qwen3.8 Max (0902)Same lab
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Qwen3 235B A22B 2507 vs GLM 5Same size
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GLM 5.3 vs GLM 5 TurboNew provider
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Model pages

GLM 5.3 logo
GLM 5.313 outputs, specs and price
Qwen3 235B A22B 2507 logo
Qwen3 235B A22B 250736 outputs, specs and price
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