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  5. GLM 5.3 FlashvsQwen3.5 397B A17B
Updated Aug 2026

GLM 5.3 FlashvsQwen3.5 397B A17B

GLM 5.3 Flash is cheaper than Qwen3.5 397B A17B at $0.15/M vs $0.6/M input tokens.

GLM 5.3 Flash and Qwen3.5 397B A17B compared across 15 shared prompts
SpecGLM 5.3 FlashQwen3.5 397B A17B
Input price$0.15/M tokens$0.6/M tokens
Output price$0.5/M tokens$3.6/M tokens
Context window1.3M tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedAug 2026Feb 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 15 prompts both answered. Formatting stripped, words untouched.

Historical Counterfactual Analysis

If the transistor had been invented in 1920 instead of 1947, trace the likely technological, economic, and geopolitical implications through…

GLM 5.3 Flash1,314 words
Counterfactual: The Transistor in 1920 Preliminary Framing A 1920 transistor presumes vacuum-tube-era physics knowledge outpacing reality—quantum mechanics wasn't mature until 1926–28, so a working device would likely be an empirical oddity (like the actual point-contact transistor) imperfectly understood.
Read the full answer
Qwen3.5 397B A17B1,254 words
This scenario posits a 27-year technological head start (1920 vs. 1947). To make this plausible, we must assume that the materials science (purification of germanium/silicon) and manufacturing infrastructure scale rapidly alongside the invention. Here is the traced history of the "Silicon Twenties" through 1980.
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 5.3 Flash1,321 words
48-Hour Action Plan: Liver Failure Signal in Flagship Drug Guiding Principle First The side effect is real, the drug is in 4 million patients, and roughly 500 patients per year may develop liver failure (4M ÷ 8,000). Every day of delay is measured in preventable liver transplants and deaths.
Read the full answer
Qwen3.5 397B A17B1,322 words
This is a crisis scenario that defines a CEO's legacy. The decision matrix is clear: Patient safety and regulatory compliance must supersede short-term financial protection. Hiding this information constitutes securities fraud and potential criminal negligence (precedents include Vioxx/Merck and Purdue Pharma).
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 5.3 Flash1,276 words
The Experienced Software Engineer You know how a load balancer routes requests, how a cache stores frequently-accessed data, how a database index lets you find a needle without scanning the haystack? An LLM is a fundamentally different kind of system: it's a learned lookup, not a designed one.
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Qwen3.5 397B A17B569 words
The Experienced Software Engineer Think of training an LLM not as "teaching" it, but as extreme lossy compression. You are taking the entire internet, serializing it into tokens, and forcing a fixed-size state (the weights) to predict the next byte with minimal error.
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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 5.3 Flash327 words
1-Month Beginner Health & Longevity Plan 🥗 Area 1: Diet — "Add Before You Subtract" Week 1: Add one vegetable or fruit to every meal. Don't cut anything yet—just add. Week 2: Swap one sugary drink per day for water or unsweetened tea.
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Qwen3.5 397B A17B641 words
Here is a simple, actionable 1-month plan designed to build sustainable habits for health and longevity. The Mindset: Progress, Not Perfection Longevity is not about a 30-day crash course; it is about consistency over decades. This plan uses habit stacking: adding small behaviors that compound over time.
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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 5.3 Flash205 words
Golden Hour Garlic Butter Pasta A silky, savory pasta that comes together faster than delivery! Ingredients (serves 2): 8 oz spaghetti or any pasta 4 tbsp butter 4 cloves garlic, minced (or 1 tsp garlic powder) ½ cup grated Parmesan cheese ½ cup pasta water (reserved) 1 tsp red pepper flakes Salt Prep time: 5 minutes…
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Qwen3.5 397B A17B284 words
🌟 Golden Hour Glaze Bowls A sweet-and-savory dish that turns humble shelf-stable staples into a crispy, comforting meal. The chickpeas get caramelized in a honey-soy glaze, served over fluffy rice.
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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 5.3 Flash667 words
Three Weakest Claims in the MindMeld AI Pitch Slide 3: "94% accuracy" decoding brainwaves into text Why it's weak: The claim is meaningless without a baseline. 94% accuracy for what — character recognition? Word prediction? Compared against what task?
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Qwen3.5 397B A17B655 words
Here are the three weakest claims in the MindMeld AI pitch deck, along with an analysis of their weaknesses and recommendations for improvement. The Vision Claim: "Predict what you want to type before you think it."
Read the full answer
Our Verdict
GLM 5.3 Flash
GLM 5.3 Flash
Qwen3.5 397B A17B
Qwen3.5 397B A17B

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

GLM 5.3 Flash costs 7.2x less per token.

Too close to call
API pricing

Cost per 1M tokens

GLM 5.3 Flash
Input
$0.15
4.0× cheaper
Output
$0.50
7.2× cheaper
Qwen3.5 397B A17B
Input
$0.60
Output
$3.60

GLM 5.3 Flash is cheaper on both: 4.0× input, 7.2× output.

Where to run it

39 hosts, cheapest first

GLM 5.3 Flash29 hosts
HostInOutContextUptime
DDeepInfrafp4$0.07 in·$0.25 out·1M·99% upIInferenceNetfp4$0.09 in·$0.28 out·1M·97.8% upGGMI Cloudfp8$0.09 in·$0.30 out·1M·99.2% upWWafer$0.10 in·$0.35 out·1M·99.8% upRRelace$0.10 in·$0.36 out·1M·99.9% upOOpenInferencefp4$0.10 in·$0.50 out·1M·99.2% up
23 more hostsFewer hosts
PPhalafp8$0.13 in·$0.42 out·1M·99.6% upNNovitafp8$0.13 in·$0.44 out·1M·99.5% upSStreamLakefp8$0.14 in·$0.47 out·1M·99.1% upAAtlasCloudfp8$0.15 in·$0.50 out·1M·99.4% upBBasetenfp8$0.15 in·$0.50 out·1M·98.8% upCCoreWeavenvfp4$0.15 in·$0.50 out·1M·99.6% upDDigitalOcean$0.15 in·$0.50 out·1M·95.2% upFFireworks$0.15 in·$0.50 out·1M·99% upFFriendli$0.15 in·$0.50 out·1M·98.6% upIInceptronfp8$0.15 in·$0.50 out·1M·98.5% upIio.netfp8$0.15 in·$0.50 out·262k·99.1% upNNear AIfp8$0.15 in·$0.50 out·1M·99.1% upPParasailfp8$0.15 in·$0.50 out·1M·98.7% upRRekafp8$0.15 in·$0.50 out·262k·99% upSSiliconFlowfp8$0.15 in·$0.50 out·1M·99.7% upTTogether$0.15 in·$0.50 out·1M·99.6% upVVenice$0.15 in·$0.50 out·1M·99.1% upZ.aifp8$0.15 in·$0.50 out·1M·96.2% upNNextBitfp8$0.18 in·$0.60 out·1M·97.9% upModalfp8$0.45 in·$1.50 out·1M·99.6% upMMorphdegraded$0.08 in·$0.28 out·1M·95.9% upCCrusoefp4degraded$0.15 in·$0.50 out·1M·93% upCloudflare Workers AIdegraded$0.30 in·$1.00 out·1.3M·99.6% up
Qwen3.5 397B A17B10 hosts
HostInOutContextUptime
Alibaba Cloud$0.39 in·$2.34 out·262k·99.9% upDDeepInfrafp8$0.45 in·$3.00 out·262k·97% upPParasailfp8$0.50 in·$3.60 out·262k·99.2% upAAtlasCloudfp8$0.55 in·$3.50 out·262k·96% upDDigitalOcean$0.55 in·$3.50 out·131k·90.3% upPPhala$0.55 in·$3.50 out·262k·98.7% up
4 more hostsFewer hosts
GGMI Cloudfp8$0.60 in·$3.60 out·262k·83.5% upNNovita$0.60 in·$3.60 out·262k·97.4% upSStreamLake$0.60 in·$3.60 out·256k·97.4% upVVenice$0.75 in·$4.50 out·128k·73.2% 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 Flash is developed by Zhipu AI while Qwen3.5 397B A17B is developed by Qwen. GLM 5.3 Flash has a 1.3M token context window vs Qwen3.5 397B A17B's 262K. You can compare their actual outputs across 15 challenges on Rival to see how they differ in practice.

It depends on your use case. GLM 5.3 Flash and Qwen3.5 397B A17B each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 15 challenges so you can judge which fits your needs best.

GLM 5.3 Flash costs $0.15/M input tokens and Qwen3.5 397B A17B costs $0.6/M input tokens. GLM 5.3 Flash is $0.45/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 Flash and Qwen3.5 397B A17B 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

GLM 5.3 Flash logo
GLM 5.3 Flash15 outputs, specs and price
Qwen3.5 397B A17B logo
Qwen3.5 397B A17B53 outputs, specs and price
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Explore all of Rival

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