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  5. GLM 5.3 FlashXvsHy3
Updated Sep 2026

GLM 5.3 FlashXvsHy3

Hy3 is cheaper than GLM 5.3 FlashX at $0.132/M vs $0.37/M input tokens.

GLM 5.3 FlashX and Hy3 compared across 12 shared prompts
SpecGLM 5.3 FlashXHy3
Input price$0.37/M tokens$0.132/M tokens
Output price$1.25/M tokens$0.528/M tokens
Context window1.0M tokens262K tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedSep 2026Jul 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 12 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…

GLM 5.3 FlashX1,492 words
Counterfactual: The Transistor in 1920 This is a fun one to work through carefully. Let me establish the premise, then trace second- and third-order effects. The Premise Assume point-contact or early junction transistor physics is discovered ~1920 (say, by accident in vacuum tube/semiconductor rectifier research—the…
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Hy3921 words
Premise: A functional solid-state transistor (germanium point-contact or junction) is demonstrated in 1920, with steady refinement through the interwar years. Vacuum tubes are not immediately displaced, but by the early 1930s transistors are reliable enough for niche military and telecom use, and by the late 1930s they…
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…

GLM 5.3 FlashX172 words
Golden Honey Garlic Chickpea Crunch A crispy, sweet-savory skillet dish that works as a snack, side, or topping for rice. Ingredients (7): 1 can chickpeas (drained, patted dry) 3 tbsp honey 3 tbsp soy sauce 3 cloves garlic (minced) 2 tbsp olive oil ½ tsp red pepper flakes 2 tbsp sesame seeds (or crushed peanuts) Prep…
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Hy3178 words
Dish Name: Ruby Hurricane Pasta Ingredients (exactly 7 common pantry staples): Spaghetti (or any dry pasta) Canned diced tomatoes Garlic (pre-minced or whole cloves) Extra-virgin olive oil Red pepper flakes Salt Grated Parmesan (shelf-stable style) (Water for boiling pasta is assumed free and not counted.)
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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 5.3 FlashX347 words
1-Month Health & Longevity Starter Plan Week 1: Build the Foundation 🥗 Diet Add one vegetable or fruit to every meal (don't restrict anything yet) Drink a glass of water when you wake up each morning 🏃 Exercise Take a 10–15 minute walk daily (same time each day builds the habit) Do 2 sets of 5 squats and 10 wall…
Read the full answer
Hy3306 words
Here’s a simple, beginner-friendly 1-month plan built around three foundational pillars of health and longevity: Diet, Movement, and Sleep. The goal is to build sustainable habits, not perfection. Diet – Nourish Without Obsessing Focus: Add before you subtract; keep it practical.
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 5.3 FlashX695 words
Critique of MindMeld AI Pitch: 3 Weakest Claims "94% accuracy" for thought-to-text decoding (Slide 3) Why it's weak: This claim contradicts the current scientific state of the art. EEG-based decoding (a non-invasive signal measured through the skull) produces extremely noisy data.
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Hy3559 words
Below are the three weakest claims in the MindMeld AI pitch, why they fail under scrutiny, and how to fix them with concrete, defensible improvements. Slide 3 – “94% accuracy” and “works with any language, any device” Why it’s weak: Technical implausibility: State-of-the-art non-invasive EEG decoding for…
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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 5.3 FlashX1,306 words
Architecture Review: Real-Time Collaborative Editor This architecture has fundamental flaws that would break core functionality, plus scalability issues. Let me go from critical to scaling concerns.
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Hy3975 words
Below is a breakdown of the major failure modes, race conditions, and scaling bottlenecks in the described architecture, followed by targeted fixes and their trade-offs.
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 5.3 FlashX1,174 words
48-Hour Action Plan: Patient Safety First, Managed Transparency Second Core Decision (Stated Up Front) We report to regulators immediately—voluntarily—and we disclose on the earnings call. The math is brutal and clear: ~500 patients could develop liver failure over 5 years at current prescribing rates (4M ÷ 8,000).
Read the full answer
Hy3997 words
Assumptions / Starting Point Current time: Monday 9:00 AM. Board meeting: Wednesday 9:00 AM (Hour 48). Earnings call: Thursday 9:00 AM (Hour 72). Drug: $2B revenue, 4M patients, liver failure 1/8,000 over 5 yrs (~500 total, ~100/yr).
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Our Verdict
GLM 5.3 FlashX
GLM 5.3 FlashX
Hy3
Hy3

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

Too close to call
API pricing

Cost per 1M tokens

GLM 5.3 FlashX
Input
$0.37
Output
$1.25
Hy3
Input
$0.13
2.8× cheaper
Output
$0.53
2.4× cheaper

Hy3 is cheaper on both: 2.8× input, 2.4× output.

Where to run it

7 hosts, cheapest first

GLM 5.3 FlashX1 host
HostInOutContextUptime
Z.aifp8$0.37 in·$1.25 out·1M·100% up
Hy36 hosts
HostInOutContextUptime
DDeepInfrafp4$0.13 in·$0.53 out·262k·99.5% upTencentfp8$0.13 in·$0.53 out·262k·99.8% upNNovita$0.14 in·$0.58 out·262k·99.7% upPPhala$0.15 in·$0.64 out·262k·99.9% upAAtlasCloudfp8$0.20 in·$0.80 out·262k·99.9% upGGMI Cloudbf16degraded$0.14 in·$0.58 out·262k·99% 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 FlashX is developed by Zhipu AI while Hy3 is developed by Tencent. GLM 5.3 FlashX has a 1.0M token context window vs Hy3'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 FlashX and Hy3 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 FlashX costs $0.37/M input tokens and Hy3 costs $0.132/M input tokens. Hy3 is $0.24/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 FlashX and Hy3 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

GLM 5.3 FlashX logo
GLM 5.3 FlashX12 outputs, specs and price
Hy3 logo
Hy314 outputs, specs and price
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