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  5. GLM 5.3 FlashvsLlama 4 Maverick
Updated Aug 2026

GLM 5.3 FlashvsLlama 4 Maverick

GLM 5.3 Flash is cheaper than Llama 4 Maverick at $0.15/M vs $1.5/M input tokens.

GLM 5.3 Flash and Llama 4 Maverick compared across 15 shared prompts
SpecGLM 5.3 FlashLlama 4 Maverick
Input price$0.15/M tokens$1.5/M tokens
Output price$0.5/M tokens$2.5/M tokens
Context window1.3M tokens1.0M tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedAug 2026Apr 2025
Side by side

Same prompt, both answers

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

Mini LBO Underwrite

You are underwriting a 5-year LBO for a private equity investment committee. Company (fictional): HarborTech Services (HTS) –…

GLM 5.3 Flash518 words
HarborTech Services — 5-Year LBO Summary Entry Math EV = 12.0x × $120m = $1,440.0m; Fees (2%) = $28.8m; Total uses = $1,468.8m Debt: TL = 4.0x × 120 = $480.0m; Mezz = 1.5x × 120 = $180.0m; Total = $660.0m (5.5x) Sponsor equity = $808.8m Base Case Projection ($m) FY26 FY27 FY28 FY29 FY30 Revenue 972.0 1,039.7 1,102.1…
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Llama 4 Maverick1,158 words
Step 1: Calculate the purchase price and transaction fees First, we need to calculate the purchase price and transaction fees. The purchase price is 12.0x EBITDA, and EBITDA in FY2025 is $120m. So, the purchase price = 12.0x * $120m = $1440m. Transaction fees = 2.0% of enterprise value = 2.0% * $1440m = $28.8m.
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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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Llama 4 Maverick916 words
For the Experienced Software Engineer Large language models like GPT or Claude are built on a simple yet powerful idea: predicting the next word in a sequence. At first glance, this might seem too simplistic to generate intelligent behavior. However, the key lies in the scale and complexity of the models.
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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.
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Llama 4 Maverick590 words
In the next 48 hours, my primary objective is to balance the company's legal, ethical, and financial responsibilities while prioritizing patient safety. Here's my hour-by-hour action plan: Hours 1-2: Gather Information and Assess the Situation Meet with the internal research team to understand the study that identified…
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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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Llama 4 Maverick210 words
Here's a simple recipe for a delicious sweet dish using only 7 common pantry ingredients: Recipe: "Golden Honey Crunch Bites" Prep Time: 10 minutes Cook Time: 15 minutes Total Time: 25 minutes Ingredients: 1 cup rolled oats 1/2 cup peanut butter 1/4 cup honey 1/4 cup brown sugar 1/2 teaspoon salt 1/4 teaspoon vanilla…
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Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

GLM 5.3 Flash720 words
"Ember & Tide" — Charred Banana Peel Consommé with Sea Urchin, Hay-Smoked Foie Gras, and Black Garlic Beurre Blanc Conceptual Narrative This dish explores the dialogue between decay and luxury — ingredients usually discarded (banana peels, hay stalks) elevated alongside opulent ones (uni, foie gras).
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Llama 4 Maverick830 words
Dish Name: "Terra Verde Odyssey" Conceptual Narrative: "Terra Verde Odyssey" is a culinary journey that explores the harmonious union between the earth's umami flavors and the ocean's freshness. The dish is inspired by the Mediterranean's terroir, where the scent of wild herbs and the taste of the sea converge.
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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 5.3 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
Llama 4 Maverick631 words
Step 1: Understanding the Impact of the Transistor's Early Invention on Technology If the transistor had been invented in 1920, it would have significantly accelerated the development of electronics, leading to more compact, efficient, and reliable devices.
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Our Verdict
GLM 5.3 Flash
GLM 5.3 Flash
Llama 4 Maverick
Llama 4 Maverick

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

GLM 5.3 Flash costs 5.0x less per token.

Too close to call
API pricing

Cost per 1M tokens

GLM 5.3 Flash
Input
$0.15
10× cheaper
Output
$0.50
5.0× cheaper
Llama 4 Maverick
Input
$1.50
Output
$2.50

GLM 5.3 Flash is cheaper on both: 10× input, 5.0× output.

Where to run it

35 hosts, cheapest first

GLM 5.3 Flash30 hosts
HostInOutContextUptime
DDeepInfrafp4$0.07 in·$0.25 out·1M·99.1% upGGMI Cloudfp8$0.07 in·$0.25 out·1M·99.2% upMMorph$0.08 in·$0.28 out·1M·100% upIInferenceNetfp4$0.09 in·$0.28 out·1M·97.2% upWWafer$0.10 in·$0.35 out·1M·99.8% upOOpenInferencefp4$0.10 in·$0.50 out·1M·98.1% up
24 more hostsFewer hosts
RRelace$0.11 in·$0.36 out·1M·99.7% upPPhalafp8$0.13 in·$0.42 out·1M·99.4% upNNovitafp8$0.13 in·$0.44 out·1M·99.4% upSStreamLakefp8$0.14 in·$0.47 out·1M·99% upSSail Researchfp8$0.14 in·$0.47 out·1M·98.9% upAAtlasCloudfp8$0.15 in·$0.50 out·1M·99.6% upBBasetenfp8$0.15 in·$0.50 out·1M·99.1% upCloudflare Workers AI$0.15 in·$0.50 out·1.3M·99.8% upCCoreWeavenvfp4$0.15 in·$0.50 out·1M·99.5% upDDigitalOcean$0.15 in·$0.50 out·1M·94.1% upFFireworks$0.15 in·$0.50 out·1M·99.1% upFFriendli$0.15 in·$0.50 out·1M·98.7% upIInceptronfp8$0.15 in·$0.50 out·1M·98.2% upIio.netfp8$0.15 in·$0.50 out·262k·99.1% upNNear AIfp8$0.15 in·$0.50 out·1M·98.9% upPParasailfp8$0.15 in·$0.50 out·1M·98.8% upRRekafp8$0.15 in·$0.50 out·262k·98.9% upSSiliconFlowfp8$0.15 in·$0.50 out·1M·99.7% upTTogether$0.15 in·$0.50 out·1M·99.5% upVVenice$0.15 in·$0.50 out·1M·98.7% upZ.aifp8$0.15 in·$0.50 out·1M·96.6% upNNextBitfp8$0.18 in·$0.60 out·1M·98% upModalfp8$0.45 in·$1.50 out·1M·99.6% upCCrusoefp4degraded$0.15 in·$0.50 out·1M·93.1% up
Llama 4 Maverick5 hosts
HostInOutContextUptime
DDigitalOcean$0.19 in·$0.65 out·128k·99.8% upDDeepInfrafp8$0.20 in·$0.80 out·1M·99.8% upNNovitafp8$0.27 in·$0.85 out·1M·99.8% upPParasailfp8$0.35 in·$1.00 out·524k·100% upGoogle Vertex AI$0.35 in·$1.15 out·524k—

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 Flash is developed by Zhipu AI while Llama 4 Maverick is developed by Meta AI. GLM 5.3 Flash has a 1.3M token context window vs Llama 4 Maverick's 1.0M. 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 Llama 4 Maverick 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 Llama 4 Maverick costs $1.5/M input tokens. GLM 5.3 Flash is $1.35/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 Flash and Llama 4 Maverick 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
Llama 4 Maverick logo
Llama 4 Maverick57 outputs, specs and price
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