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  5. DeepSeek V4 ProvsGLM 5.3 Flash
Updated Aug 2026

DeepSeek V4 ProvsGLM 5.3 Flash

GLM 5.3 Flash is cheaper than DeepSeek V4 Pro at $0.15/M vs $1.74/M input tokens.

DeepSeek V4 Pro and GLM 5.3 Flash compared across 15 shared prompts
SpecDeepSeek V4 ProGLM 5.3 Flash
Input price$1.74/M tokens$0.15/M tokens
Output price$3.48/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 Pro2,259 words
If the transistor had emerged in 1920—a full 27 years earlier—the entire trajectory of the 20th century would have been radically altered. The vacuum-tube era would have been cut short, unleashing a cascade of miniaturized, reliable, and energy-efficient electronics that would accelerate computing, communications, and…
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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

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…

DeepSeek V4 Pro336 words
Midnight Pantry Pomodoro Penne A deeply comforting, no-fuss pasta that proves the humblest staples can shine like a moonlit trattoria dinner. Ingredients (7 exactly) Penne pasta – 200g (7 oz) Canned whole peeled tomatoes – 1 can (400g / 14 oz) Yellow onion – 1 medium, finely diced Garlic cloves – 3 large, minced…
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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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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 Pro1,002 words
1. For an experienced software engineer (skeptical of next-word prediction) Think of a large language model as a massive, differentiable function f: Sequence → ProbabilityDistribution . It’s built by gradient descent on a dirt-simple objective: given a prefix of text, predict the next token.
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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.
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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…

DeepSeek V4 Pro1,680 words
Unagi: Midori no Yume (Eel’s Green Dream) A multi-sensory kaiseki-inspired contemporary dish that unites the deep umami of charcoal-grilled freshwater eel with the ethereal chill of matcha snow, punctuated by dashi pearls, yuzu kosho gel, and a wisp of cherry blossom smoke.
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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).
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Mini LBO Underwrite

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

DeepSeek V4 Pro602 words
HarborTech Services (HTS) – 5-Year LBO Model Projected Financials & Debt Schedule (US$ millions, fiscal years ending December) FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972.0 1,040.0 1,102.4 1,157.6 1,215.4 EBITDA 136.1 156.0 176.4 191.0 206.6 Margin 14.0% 15.0% 16.0% 16.5% 17.0% Cash Interest Term Loan (9% cash) 43.2…
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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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Advanced Longevity Plan (Biohacker)

Develop a comprehensive, cutting-edge 3-month longevity plan for a biohacker aiming to optimize longevity, physical and cognitive…

DeepSeek V4 Pro1,917 words
This is a highly detailed, phased, 3-month longevity optimization protocol grounded in the latest science of aging biology, systems medicine, and biohacking. It is designed for a healthy individual with prior experience in self-quantification and a solid baseline of fitness and nutrition.
Read the full answer
GLM 5.3 Flash1,294 words
90-Day Longevity Optimization Protocol ⚠️ Medical disclaimer: This is an educational framework, not medical advice. Before starting, complete baseline labs and consult a physician—especially before fasting, supplements (rapamycin off-label use, high-dose anything), or if you have any health conditions.
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Our Verdict
DeepSeek V4 Pro
DeepSeek V4 Pro
GLM 5.3 Flash
GLM 5.3 Flash

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

GLM 5.3 Flash costs 7.0x less per token.

Too close to call
API pricing

Cost per 1M tokens

DeepSeek V4 Pro
Input
$1.74
Output
$3.48
GLM 5.3 Flash
Input
$0.15
12× cheaper
Output
$0.50
7.0× cheaper

GLM 5.3 Flash is cheaper on both: 12× input, 7.0× output.

Where to run it

44 hosts, cheapest first

DeepSeek V4 Pro15 hosts
HostInOutContextUptime
SStreamLakefp8$0.96 in·$1.91 out·1M·99% upGGMI Cloudfp8$0.96 in·$1.91 out·1M·99.8% upDDigitalOcean$1.04 in·$2.09 out·1M·100% upDDeepInfrafp8$1.30 in·$2.60 out·1M·99.2% upAlibaba Cloudfp8$1.42 in·$2.83 out·1M·100% upSSiliconFlowfp8$1.50 in·$3.13 out·1M·99.4% up
9 more hostsFewer hosts
NNovitafp8$1.60 in·$3.20 out·1M·100% upVVenice$1.65 in·$3.30 out·1M·97.9% upAAtlasCloudfp4$1.68 in·$3.38 out·1M·99.8% upBaidu Qianfanfp8$1.69 in·$3.38 out·1M·99.9% upBBasetenfp4$1.74 in·$3.48 out·1M·99.6% upNNextBitfp8$1.74 in·$3.48 out·1M·97.6% upPParasailfp8$1.74 in·$3.48 out·1M·99% upAzure AI Foundry$1.91 in·$3.83 out·1M·95.5% upCloudflare Workers AIdegraded$1.15 in·$2.55 out·1M·94.2% 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 Pro is developed by DeepSeek while GLM 5.3 Flash is developed by Zhipu AI. DeepSeek V4 Pro 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 Pro 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 Pro costs $1.74/M input tokens and GLM 5.3 Flash costs $0.15/M input tokens. GLM 5.3 Flash is $1.59/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 Pro 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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Rival
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Explore all of Rival

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