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  5. DeepSeek V4 FlashvsGLM 5.3 Flash
Updated Aug 2026

DeepSeek V4 FlashvsGLM 5.3 Flash

DeepSeek V4 Flash is cheaper than GLM 5.3 Flash at $0.14/M vs $0.15/M input tokens.

DeepSeek V4 Flash and GLM 5.3 Flash compared across 15 shared prompts
SpecDeepSeek V4 FlashGLM 5.3 Flash
Input price$0.14/M tokens$0.15/M tokens
Output price$0.28/M tokens$0.5/M tokens
Context window1.0M tokens1.3M tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedApr 2026Aug 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…

DeepSeek V4 Flash1,987 words
If the transistor had been invented in 1920—a full 27 years earlier—its impact would ripple through every layer of technology, economics, and geopolitics, fundamentally reshaping the 20th century. Below is a detailed tracing of first-, second-, and third-order effects through 1980, organized by domain.
Read the full answer
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

Mini LBO Underwrite

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

DeepSeek V4 Flash442 words
LBO Model: HarborTech Services (HTS) – Base Case & Sensitivity Year-by-Year Financial Projections (FY2026–FY2030) ($ millions) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.00 1,040.04 1,102.44 1,157.56 1,215.44 EBITDA 136.08 156.01 176.39 191.00 206.63 Less: Cash Interest (64.80) (63.08) (60.08) (55.69) (50.16) –…
Read the full answer
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…
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…

DeepSeek V4 Flash967 words
This is a fantastic goal. The key for a beginner is consistency over intensity. Trying to overhaul your entire life overnight is a recipe for burnout. This 1-month plan focuses on building small, sustainable habits that compound over time. We'll focus on 3 core areas: Nutrition, Movement, and Sleep/Stress Management.
Read the full answer
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.
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…

DeepSeek V4 Flash1,120 words
To an experienced software engineer (skeptical of "next word prediction") Think of a large language model not as a brain, but as a massive, shared cache of probabilistic completions built from trillions of examples.
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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.
Read the full answer

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…

DeepSeek V4 Flash1,455 words
Here is a conceptual recipe for a three-Michelin-star-level dish that deconstructs a classic pairing into something utterly unexpected, using advanced techniques and a narrative of geological wonder.
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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).
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…

DeepSeek V4 Flash1,972 words
CEO’s 48-Hour Action Plan Context: I’ve just learned that our flagship chronic pain drug has a rare but serious liver failure risk (1 in 8,000 patients over 5 years), previously unknown. I have 48 hours until the board meeting and 72 hours until the earnings call.
Read the full answer
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
Our Verdict
DeepSeek V4 Flash
DeepSeek V4 Flash
GLM 5.3 Flash
GLM 5.3 Flash

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

Too close to call
API pricing

Cost per 1M tokens

DeepSeek V4 Flash
Input
$0.14
1.1× cheaper
Output
$0.28
1.8× cheaper
GLM 5.3 Flash
Input
$0.15
Output
$0.50

DeepSeek V4 Flash is cheaper on both: 1.1× input, 1.8× output.

Where to run it

44 hosts, cheapest first

DeepSeek V4 Flash15 hosts
HostInOutContextUptime
OOpenInferencefp8$0.04 in·$0.50 out·1M·99.7% upSStreamLakefp8$0.09 in·$0.18 out·1M·97.7% upDDeepInfrafp8$0.09 in·$0.18 out·1M·99.7% upGGMI Cloudfp8$0.09 in·$0.18 out·1M·99.3% upVVenice$0.10 in·$0.19 out·1M·98.9% upDDigitalOcean$0.10 in·$0.20 out·1M·99.9% up
9 more hostsFewer hosts
SSiliconFlowfp8$0.13 in·$0.28 out·1M·98.9% upAlibaba Cloudfp8$0.13 in·$0.27 out·1M·99.5% upAAtlasCloudfp4$0.14 in·$0.28 out·1M·99.9% upBaidu Qianfanfp8$0.14 in·$0.28 out·1M·96.2% upNNovitafp8$0.14 in·$0.28 out·1M·100% upPParasailfp8$0.14 in·$0.28 out·1M·99.6% upNNextBitfp8$0.15 in·$0.30 out·1M·97.6% upMMancerfp8$0.19 in·$0.50 out·1M·97.7% upAzure AI Foundrydegraded$0.21 in·$0.56 out·1M·94.1% up
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

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

Research

What we learned reading every model

FAQ

Common questions

DeepSeek V4 Flash is developed by DeepSeek while GLM 5.3 Flash is developed by Zhipu AI. DeepSeek V4 Flash has a 1.0M token context window vs GLM 5.3 Flash's 1.3M. You can compare their actual outputs across 15 challenges on Rival to see how they differ in practice.

It depends on your use case. DeepSeek V4 Flash and GLM 5.3 Flash 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.

DeepSeek V4 Flash costs $0.14/M input tokens and GLM 5.3 Flash costs $0.15/M input tokens. DeepSeek V4 Flash is $0.01/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 DeepSeek V4 Flash and GLM 5.3 Flash 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

DeepSeek V4 Flash logo
DeepSeek V4 Flash58 outputs, specs and price
GLM 5.3 Flash logo
GLM 5.3 Flash15 outputs, specs and price
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