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  5. GLM 5.3 FlashvsMercury 2.5 Preview
Updated Aug 2026

GLM 5.3 FlashvsMercury 2.5 Preview

Mercury 2.5 Preview is cheaper than GLM 5.3 Flash at $0.04/M vs $0.15/M input tokens.

GLM 5.3 Flash and Mercury 2.5 Preview compared across 15 shared prompts
SpecGLM 5.3 FlashMercury 2.5 Preview
Input price$0.15/M tokens$0.04/M tokens
Output price$0.5/M tokens$0.15/M tokens
Context window1.3M tokens260K tokens
WeightsOpen—
Free API (OpenRouter)NoNo
ReleasedAug 2026Aug 2026
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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Mercury 2.5 Preview299 words
Year-by-Year Model (FY2026–FY2030) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue $972m $1,040m $1,102m $1,158m $1,215m EBITDA $136m $156m $176m $191m $207m Cash Interest (Term) $43.2m $41.1m $37.6m $33.4m $28.2m Cash Interest (Mezz) $21.6m $21.6m $21.6m $21.6m $21.6m Cash Taxes (25%) $17.8m $23.3m $29.3m $34.7m…
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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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Mercury 2.5 Preview709 words
This is a critical governance and safety scenario. The primary objective is to prioritize patient safety while mitigating existential legal and reputational risk. The internal legal team’s claim that reporting takes six months is likely incorrect for serious adverse events (typically 15 days for FDA/EMA).
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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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Mercury 2.5 Preview608 words
For the Experienced Software Engineer Think of training as a massive distributed job where the model is a stateful service learning to minimize error on a specific objective function. Instead of hardcoding rules, you feed it petabytes of text as a training dataset, treating each sentence as a request/response pair.
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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.
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Mercury 2.5 Preview683 words
Shifting the invention of the solid-state switch to 1920 accelerates the Information Age by roughly three decades. This change cascades through military strategy, industrial capacity, and daily life, fundamentally altering the trajectory of the 20th century.
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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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Mercury 2.5 Preview176 words
Here is a straightforward 4-week roadmap designed to build sustainable habits without overwhelming you. Core Pillars Nutrition: Focus on whole foods and hydration. Activity: Prioritize consistent movement over intensity. Restoration: Protect sleep quality and manage energy.
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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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Mercury 2.5 Preview748 words
Dish Title: Lithospheric Tides Conceptual Narrative This dish explores the geological convergence of the deep ocean and the subterranean earth. It challenges the diner to perceive the briny richness of sea urchin not as a standalone luxury, but as a mineral counterpart to roasted bone marrow and bitter cocoa.
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Our Verdict
GLM 5.3 Flash
GLM 5.3 Flash
Mercury 2.5 Preview
Mercury 2.5 PreviewRunner-up

Not enough votes to call it. On the specs, GLM 5.3 Flash has the edge: bigger model tier, bigger context window, major provider backing.

Mercury 2.5 Preview costs 3.3x less per token.

Slight edge
API pricing

Cost per 1M tokens

GLM 5.3 Flash
Input
$0.15
Output
$0.50
Mercury 2.5 Preview
Input
$0.04
3.8× cheaper
Output
$0.15
3.3× cheaper

Mercury 2.5 Preview is cheaper on both: 3.8× input, 3.3× output.

Where to run it

30 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
Mercury 2.5 Preview1 host
HostInOutContextUptime
Inception$0.04 in·$0.15 out·260k·100% 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 Mercury 2.5 Preview is developed by Inception. GLM 5.3 Flash has a 1.3M token context window vs Mercury 2.5 Preview's 260K. 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 Mercury 2.5 Preview 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 Mercury 2.5 Preview costs $0.04/M input tokens. Mercury 2.5 Preview is $0.11/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 Mercury 2.5 Preview 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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Same lab, same size, long tail

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GLM 5.3 Flash vs GLM 5.3 FlashXSame lab
GLM 5.3 Flash logoGLM 5.2 logo
GLM 5.3 Flash vs GLM 5.2Same lab
Mercury 2.5 Preview logoMercury 2.5 logo
Mercury 2.5 Preview vs Mercury 2.5Same lab
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Mercury 2.5 Preview logoGPT-5.3 Chat logo
Mercury 2.5 Preview vs GPT-5.3 ChatNew provider
GLM 5.3 Flash logoGPT-5.3-Codex logo
GLM 5.3 Flash vs GPT-5.3-CodexNew provider
GLM 5.3 Flash logoGPT-5.4 logo
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Mercury 2.5 Preview vs GPT-5.4 MiniSame size

Model pages

GLM 5.3 Flash logo
GLM 5.3 Flash15 outputs, specs and price
Mercury 2.5 Preview logo
Mercury 2.5 Preview58 outputs, specs and price
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