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  5. GLM 5.3vsNVIDIA Nemotron Nano 9B V2
Updated Aug 2026

GLM 5.3vsNVIDIA Nemotron Nano 9B V2

NVIDIA Nemotron Nano 9B V2 is cheaper than GLM 5.3 at $0.04/M vs $0.6538/M input tokens.

GLM 5.3 and NVIDIA Nemotron Nano 9B V2 compared across 13 shared prompts
SpecGLM 5.3NVIDIA Nemotron Nano 9B V2
Input price$0.6538/M tokens$0.04/M tokens
Output price$2.0548/M tokens$0.16/M tokens
Context window1.3M tokens131K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedAug 2026Sep 2025
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…

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.
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NVIDIA Nemotron Nano 9B V2175 words
Dish Name: Pantry-Powered Pasta Primavera Ingredients (7 common pantry items): Pasta (any shape) Canned tomatoes (diced or crushed) Olive oil Salt Garlic (minced, if available; otherwise skip) Dried herbs (oregano, basil, or parsley, if available) Canned beans (e.g., kidney or black beans, for added protein)…
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Debug This Architecture

Here's the architecture for a real-time collaborative document editor (like Google Docs): **System Overview:** - Frontend: React SPA with…

GLM 5.31,311 words
Architecture Review: Real-Time Collaborative Editor This design has serious issues across correctness, performance, and security. Let me break them down by severity. 🔴 Critical: Correctness / Data Loss Client-clock-based Last-Write-Wins (LWW) Problem: Client clocks are unreliable (skew, manual changes, timezone bugs).
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NVIDIA Nemotron Nano 9B V21,511 words
Okay, let's tackle this problem. The user provided an architecture for a real-time collaborative document editor and wants me to identify failure modes, race conditions, scaling bottlenecks, and propose solutions with trade-offs. Hmm, where to start? First, I need to understand the system thoroughly.
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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 5.31,143 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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NVIDIA Nemotron Nano 9B V2756 words
Hour-by-Hour Action Plan for the Next 48 Hours (Focus: Patient Safety, Ethical Obligations, and Strategic Risk Mitigation) Hours 0–2: Immediate Data Verification and Internal Alignment Action: Confirm the accuracy of the internal research team’s findings (e.g., liver failure rate, timeline, patient demographics).
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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 5.31,346 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…
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NVIDIA Nemotron Nano 9B V2934 words
If the transistor had been invented in 1920 instead of 1947, the technological, economic, and geopolitical landscape by 1980 would be profoundly altered. Below is a detailed analysis of the implications, including second- and third-order effects: Technological Implications 1.
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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 5.3415 words
1-Month Beginner Health & Longevity Plan Week 1: Foundation & Awareness Goal: Establish baselines, not perfection 🥗 Diet Track what you currently eat for 3 days (no judging—just observe) Drink a glass of water upon waking each morning Add ONE vegetable to one meal daily 🏃 Exercise Walk 15 minutes daily (any pace, any…
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NVIDIA Nemotron Nano 9B V2310 words
1-Month Health & Longevity Plan Focus on diet, exercise, and sleep—three foundational pillars for health. Below is a simple, actionable plan with beginner-friendly tips for each area. 1. Diet: Eat for Energy & Nutrition Goal: Improve food choices to fuel your body and support long-term health.
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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.…

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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NVIDIA Nemotron Nano 9B V2658 words
Three Weakest Claims in the Pitch Deck Here are the three weakest claims, along with explanations of their weaknesses and actionable suggestions to strengthen them: 1. Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy."
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Our Verdict
GLM 5.3
GLM 5.3
NVIDIA Nemotron Nano 9B V2
NVIDIA Nemotron Nano 9B V2Runner-up

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

NVIDIA Nemotron Nano 9B V2 costs 13x less per token.

Slight edge
API pricing

Cost per 1M tokens

GLM 5.3
Input
$0.65
Output
$2.05
NVIDIA Nemotron Nano 9B V2
Input
$0.04
16× cheaper
Output
$0.16
13× cheaper

NVIDIA Nemotron Nano 9B V2 is cheaper on both: 16× input, 13× output.

Where to run it

30 hosts, cheapest first

GLM 5.330 hosts
HostInOutContextUptime
Baidu Qianfanfp8$0.65 in·$2.05 out·1M·99.8% upRRekafp8$0.76 in·$2.57 out·262k·99.4% upNNovitafp8$0.78 in·$2.46 out·1M·99.9% upIio.netfp8$0.82 in·$2.77 out·262k·99.6% upPPhala$0.84 in·$2.64 out·1M·99.5% upMMorph$0.86 in·$2.69 out·1M·99.8% up
24 more hostsFewer hosts
DDeepInfrafp4$0.90 in·$3.00 out·1M·98% upIInferenceNetfp4$0.90 in·$3.00 out·1M·97.9% upDDigitalOcean$0.91 in·$2.86 out·1M·99.7% upIInceptronfp4$1.01 in·$3.29 out·1M·99.3% upSSail Researchfp8$1.02 in·$3.29 out·1M·99.9% upGGMI Cloudfp8$1.05 in·$3.30 out·1M·99.5% upMMakorafp4$1.05 in·$4.20 out·980k·97.8% upSSiliconFlowfp8$1.12 in·$3.52 out·1M·99.6% upAlibaba Cloud$1.19 in·$3.74 out·1M·100% upDDecartfp4$1.19 in·$3.74 out·1M·99% 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·99.5% upBBasetenfp4$1.40 in·$4.40 out·1M·99.7% upCloudflare Workers AI$1.40 in·$4.40 out·1.3M·99.9% upCCrusoefp4$1.40 in·$4.40 out·1M·98.2% upFFireworks$1.40 in·$4.40 out·1M·99.6% upMistralnvfp4$1.40 in·$4.40 out·1M·99.8% upModal$1.40 in·$4.40 out·1M·99% upPParasailfp8$1.40 in·$4.40 out·1M·99.4% upTTogether$1.40 in·$4.40 out·1M·98.3% upVVenice$1.40 in·$4.40 out·1M·98.8% upWWafer$1.40 in·$4.40 out·1M·99.9% upZ.aifp8$1.40 in·$4.40 out·1M·99.9% up
NVIDIA Nemotron Nano 9B V2

No hosts listed on OpenRouter.

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 is developed by Zhipu AI while NVIDIA Nemotron Nano 9B V2 is developed by NVIDIA. GLM 5.3 has a 1.3M token context window vs NVIDIA Nemotron Nano 9B V2's 131K. You can compare their actual outputs across 13 challenges on Rival to see how they differ in practice.

It depends on your use case. GLM 5.3 and NVIDIA Nemotron Nano 9B V2 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.

GLM 5.3 costs $0.6538/M input tokens and NVIDIA Nemotron Nano 9B V2 costs $0.04/M input tokens. NVIDIA Nemotron Nano 9B V2 is $0.61/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 and NVIDIA Nemotron Nano 9B V2 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 vs Gemini 3.5 FlashSame size
GLM 5.3 logoGemini 3.6 Flash logo
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GLM 5.3 vs Gemini 3.7 FlashSame size
GLM 5.3 logoGemini 3.8 Flash logo
GLM 5.3 vs Gemini 3.8 FlashSame size

Model pages

GLM 5.3 logo
GLM 5.313 outputs, specs and price
NVIDIA Nemotron Nano 9B V2 logo
NVIDIA Nemotron Nano 9B V259 outputs, specs and price
Rival
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Explore all of Rival

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