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  5. DeepSeek V3.2vsGLM 5.3
Updated Aug 2026

DeepSeek V3.2vsGLM 5.3

DeepSeek V3.2 is cheaper than GLM 5.3 at $0.28/M vs $0.6538/M input tokens.

DeepSeek V3.2 and GLM 5.3 compared across 13 shared prompts
SpecDeepSeek V3.2GLM 5.3
Input price$0.28/M tokens$0.6538/M tokens
Output price$0.42/M tokens$2.0548/M tokens
Context window131K tokens1.3M tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedDec 2025Aug 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 13 prompts both answered. Formatting stripped, words untouched.

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 V3.2171 words
Honey-Lemon Glazed Carrot Coins Sweet, tangy, and simple—perfect as a side dish or snack! Ingredients: 4 large carrots (peeled and sliced into 1/4-inch coins) 2 tablespoons olive oil 2 tablespoons honey 1 tablespoon lemon juice 1/4 teaspoon salt 1/4 teaspoon black pepper 1 teaspoon dried thyme (optional, for extra…
Read the full answer
GLM 5.3210 words
Golden Pantry Fried Rice Total Time: 20 minutes (5 min prep, 15 min cook) Ingredients (7 pantry staples) Cooked white rice (day-old is best) Eggs Soy sauce Garlic (minced or garlic powder) Frozen peas and carrots Canned corn Vegetable oil Instructions Prep (5 min): Break up cold rice with a fork. Drain the corn.
Read the full answer

Historical Counterfactual Analysis

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

DeepSeek V3.21,224 words
Excellent question. Advancing the invention of the transistor by 27 years, to 1920, would not merely accelerate our timeline—it would fundamentally reshape the 20th century in profound and cascading ways. Here is a trace of the likely implications through 1980.
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GLM 5.31,346 words
If the Transistor Had Arrived in 1920 The Premise: Why 1920 Was Nearly Impossible Before tracing effects, note the counterfactual requires heroic assumptions. The transistor depended on quantum mechanics (solid-state band theory, ~1928-1933), ultrapure semiconductor materials (zone refining, 1950s), and wartime radar…
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 V3.2609 words
Hour 0–4 (Immediate Actions) Secure all data Direct the research team to compile the complete dataset, methodology, and evidence into a confidential briefing document. Ensure legal counsel reviews it for attorney-client privilege where applicable.
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GLM 5.31,143 words
The Core Decision (Made Before Hour 1) The side effect is real, serious, and known to me now. Patients are currently taking this drug without informed consent about a ~1-in-8,000 liver failure risk. Everything else — stock price, board pressure, legal exposure — is secondary.
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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.…

DeepSeek V3.2611 words
Excellent pitch deck summary — it’s concise and hits key points, but several claims stretch credibility and would raise red flags for experienced investors. Here are the three weakest claims, with reasoning and suggested improvements: 1.
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GLM 5.3585 words
3 Weakest Claims in the MindMeld AI Pitch "Reads your brainwaves to predict what you want to type before you think it" Why it's weak: This claim is neurologically incoherent. EEG sensors detect electrical activity on the scalp after neural firing occurs — you cannot decode intent "before" the brain generates it.
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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 V3.2649 words
Quantum Longevity Protocol: A 3-Month Biohacker's Blueprint Phase 1: Diagnostic & Metabolic Reset (Weeks 1-4) Week 1: Comprehensive Biomarker Baseline Advanced Testing Panel: NMR Lipoprotein Profile (ApoB, Lp(a), LDL-P) GlycA Inflammation Marker Omega-3 Index (Target: >8%) Homocysteine (Target: <7 µmol/L) hs-CRP (<0.5…
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GLM 5.3851 words
3-Month Advanced Longevity & Performance Optimization Protocol Note: This is an educational framework. Get baseline bloodwork and consult a physician before starting supplements/fasting, especially with any medical conditions or medications.
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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 V3.2895 words
1. For the Experienced Software Engineer Think of a large language model as the ultimate compression algorithm for human knowledge and communication patterns, built via a statistical learning process rather than explicit code.
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GLM 5.31,164 words
The Software Engineer You've probably written autocomplete logic before, so you're right to be skeptical of the naive version: a Markov chain that looks up "what usually comes after 'the'" is trivially dumb.
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Our Verdict
GLM 5.3
GLM 5.3
DeepSeek V3.2
DeepSeek V3.2Runner-up

Not enough votes to call it. On the specs, GLM 5.3 has the edge: newer, bigger context window.

DeepSeek V3.2 costs 4.9x less per token.

Too close to call
API pricing

Cost per 1M tokens

DeepSeek V3.2
Input
$0.28
2.3× cheaper
Output
$0.42
4.9× cheaper
GLM 5.3
Input
$0.65
Output
$2.05

DeepSeek V3.2 is cheaper on both: 2.3× input, 4.9× output.

Where to run it

45 hosts, cheapest first

DeepSeek V3.215 hosts
HostInOutContextUptime
GGMI Cloudfp8$0.21 in·$0.31 out·164k·99.9% upSStreamLakefp8$0.21 in·$0.32 out·128k·99.6% upSSiliconFlowfp8$0.26 in·$0.42 out·164k·98.6% upAAtlasCloudfp8$0.26 in·$0.38 out·164k·95.7% upDDeepInfrafp4$0.26 in·$0.38 out·164k·99.3% upVVenice$0.27 in·$0.39 out·160k·98.9% up
9 more hostsFewer hosts
NNovitafp8$0.27 in·$0.40 out·164k·100% upBaidu Qianfanfp8$0.28 in·$0.42 out·131k·99% upAlibaba Cloudfp8$0.37 in·$1.11 out·131k·98.8% upFFriendli$0.50 in·$1.50 out·164k·100% upGoogle Vertex AI$0.56 in·$1.68 out·164k·99.4% upPPhala$1.00 in·$1.00 out·164k·99.6% upMMara$3.00 in·$4.50 out·33k·94.5% upSSambaNova$3.00 in·$4.50 out·33k·97.2% upDDigitalOceandegraded$0.30 in·$0.96 out·164k·98.7% up
GLM 5.330 hosts
HostInOutContextUptime
DDeepInfrafp4$0.56 in·$2.50 out·1M·97.1% upMMorph$0.71 in·$2.24 out·1M·99.7% upRRekafp8$0.76 in·$2.57 out·262k·99.4% upSSail Researchfp8$0.77 in·$4.00 out·1M·99.8% upNNovitafp8$0.78 in·$2.46 out·1M·99.9% upIio.netfp8$0.82 in·$2.77 out·262k·99.8% up
24 more hostsFewer hosts
PPhala$0.84 in·$2.64 out·1M·99.4% upIInferenceNetfp4$0.90 in·$3.00 out·1M·98.2% upDDigitalOcean$0.91 in·$2.86 out·1M·99.7% upGGMI Cloudfp8$0.98 in·$3.08 out·1M·99.5% upIInceptronfp4$1.03 in·$3.73 out·1M·99.4% upMMakorafp4$1.05 in·$4.20 out·980k·97.1% upSSiliconFlowfp8$1.12 in·$3.52 out·1M·99.8% upDDecartfp4$1.19 in·$3.74 out·1M·99.2% upFFriendli$1.26 in·$3.96 out·1M·100% upAAkashMLfp8$1.30 in·$4.40 out·1M·100% upAAtlasCloudfp8$1.40 in·$4.40 out·1M·99.4% upBaidu Qianfanfp8$1.40 in·$4.40 out·1M·99.8% upBBasetenfp4$1.40 in·$4.40 out·1M·99.8% upCloudflare Workers AI$1.40 in·$4.40 out·1.3M·98.9% upCCrusoefp4$1.40 in·$4.40 out·1M·98.9% upFFireworks$1.40 in·$4.40 out·1M·99.5% upMistralnvfp4$1.40 in·$4.40 out·1M·99.4% upModal$1.40 in·$4.40 out·1M·99.1% upPParasailfp8$1.40 in·$4.40 out·1M·99.2% upTTogether$1.40 in·$4.40 out·1M·98.1% upVVenice$1.40 in·$4.40 out·1M·98.5% upWWafer$1.40 in·$4.40 out·1M·99.9% upZ.aifp8$1.40 in·$4.40 out·1M·99.9% upAlibaba Clouddegraded$1.19 in·$3.74 out·1M·99.5% up

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

Research

What we learned reading every model

FAQ

Common questions

DeepSeek V3.2 is developed by DeepSeek while GLM 5.3 is developed by Zhipu AI. DeepSeek V3.2 has a 131K token context window vs GLM 5.3's 1.3M. You can compare their actual outputs across 13 challenges on Rival to see how they differ in practice.

It depends on your use case. DeepSeek V3.2 and GLM 5.3 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 13 challenges so you can judge which fits your needs best.

DeepSeek V3.2 costs $0.28/M input tokens and GLM 5.3 costs $0.6538/M input tokens. DeepSeek V3.2 is $0.37/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 V3.2 and GLM 5.3 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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