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  5. GLM 5.3vsNex-N2.5-Pro (free)
Updated Sep 2026

GLM 5.3vsNex-N2.5-Pro (free)

Nex-N2.5-Pro (free) is cheaper than GLM 5.3 at $0/M vs $0.6538/M input tokens.

GLM 5.3 and Nex-N2.5-Pro (free) compared across 12 shared prompts
SpecGLM 5.3Nex-N2.5-Pro (free)
Input price$0.6538/M tokensFree
Output price$2.0548/M tokensFree
Context window1.3M tokens262K tokens
WeightsOpen—
Free API (OpenRouter)NoYes (1 provider)
ReleasedAug 2026Sep 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 12 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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Nex-N2.5-Pro (free)119 words
Pantry Moon Bars A sweet, chewy peanut butter–chocolate oat treat made with only 7 pantry staples. Ingredients Rolled oats Creamy peanut butter Honey Chocolate chips Vanilla extract Ground cinnamon Salt Instructions Heat oven to 350°F / 175°C. Line an 8-inch square pan with parchment paper.
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…

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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Nex-N2.5-Pro (free)2,359 words
As CEO, I would not wait six months and I would not let the board delay disclosure while patients remain exposed to an unreported serious risk. I would treat this as a patient-safety, regulatory, legal, and trust crisis—not merely a financial-risk issue. My guiding decisions would be: Patient safety comes first.
Read the full answer

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.
Read the full answer
Nex-N2.5-Pro (free)593 words
The 3 weakest claims are the ones most likely to be challenged in diligence: Weakest claim Why it’s weak How to strengthen it 1. “94% accuracy… works with any language, any device.” This is the biggest scientific and product credibility risk.
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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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Nex-N2.5-Pro (free)2,726 words
Starting assumption Assume the 1920 “transistor” is a usable but crude solid-state amplifier/switch: reproducible enough for telecom and radio, but noisy, low-power, temperature-sensitive, and expensive at first.
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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 5.31,164 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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Nex-N2.5-Pro (free)802 words
To the experienced software engineer Think of an LLM as a giant probabilistic text service trained by repeatedly asking: “Given this sequence of tokens so far, what is the next token?”
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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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Nex-N2.5-Pro (free)3,042 words
Executive summary The biggest correctness risks are: Client-clock last-write-wins is unsafe: clock skew, malicious clients, ties, and out-of-order delivery can silently lose edits.
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Our Verdict
GLM 5.3
GLM 5.3
Nex-N2.5-Pro (free)
Nex-N2.5-Pro (free)Runner-up

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

Too close to call
API pricing

Cost per 1M tokens

GLM 5.3
Input
$0.65
Output
$2.05
Nex-N2.5-Pro (free)
Input
$0.000
Output
$0.000
Where to run it

31 hosts, cheapest first

GLM 5.330 hosts
HostInOutContextUptime
Baidu Qianfanfp8$0.65 in·$2.05 out·1M·99.8% upMMorph$0.71 in·$2.24 out·1M·99.8% upRRekafp8$0.76 in·$2.57 out·262k·99.4% upSSail Researchfp8$0.77 in·$4.00 out·1M·99.9% upNNovitafp8$0.78 in·$2.46 out·1M·99.9% upIio.netfp8$0.82 in·$2.77 out·262k·99.7% up
24 more hostsFewer hosts
PPhala$0.84 in·$2.64 out·1M·99.5% upDDeepInfrafp4$0.90 in·$3.00 out·1M·98% upIInferenceNetfp4$0.90 in·$3.00 out·1M·98% upDDigitalOcean$0.91 in·$2.86 out·1M·99.8% upIInceptronfp4$1.04 in·$3.39 out·1M·99.4% upGGMI Cloudfp8$1.05 in·$3.30 out·1M·99.5% upMMakorafp4$1.05 in·$4.20 out·980k·97.3% upSSiliconFlowfp8$1.12 in·$3.52 out·1M·99.7% upAlibaba Cloud$1.19 in·$3.74 out·1M·100% upDDecartfp4$1.19 in·$3.74 out·1M·99.1% 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% upBBasetenfp4$1.40 in·$4.40 out·1M·99.7% upCloudflare Workers AI$1.40 in·$4.40 out·1.3M·99.8% upCCrusoefp4$1.40 in·$4.40 out·1M·98.3% upFFireworks$1.40 in·$4.40 out·1M·99.5% upMistralnvfp4$1.40 in·$4.40 out·1M·99.7% upModal$1.40 in·$4.40 out·1M·99% upPParasailfp8$1.40 in·$4.40 out·1M·99.1% upTTogether$1.40 in·$4.40 out·1M·98.1% 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
Nex-N2.5-Pro (free)1 host
HostInOutContextUptime
NNex AGIfp8$0 in·$0 out·262k·99.4% up

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 Nex-N2.5-Pro (free) is developed by Nex AGI. GLM 5.3 has a 1.3M token context window vs Nex-N2.5-Pro (free)'s 262K. You can compare their actual outputs across 12 challenges on Rival to see how they differ in practice.

It depends on your use case. GLM 5.3 and Nex-N2.5-Pro (free) each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 12 challenges so you can judge which fits your needs best.

GLM 5.3 costs $0.6538/M input tokens and Nex-N2.5-Pro (free) costs $0/M input tokens. Nex-N2.5-Pro (free) is $0.65/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 Nex-N2.5-Pro (free) 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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Explore all of Rival

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