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  5. GPT-5.6 TerravsHy3
Updated Jul 2026

GPT-5.6 TerravsHy3

Hy3 is cheaper than GPT-5.6 Terra at $0.132/M vs $2.5/M input tokens.

GPT-5.6 Terra and Hy3 compared across 14 shared prompts
SpecGPT-5.6 TerraHy3
Input price$2.5/M tokens$0.132/M tokens
Output price$15/M tokens$0.528/M tokens
Context window1.1M tokens262K tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedJul 2026Jul 2026
Side by side

Same prompt, both answers

Opening lines from 6 of the 14 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…

GPT-5.6 Terra146 words
Golden Crunch Cinnamon Toast Bites Ingredients (7 pantry staples): Bread slices Butter Sugar Ground cinnamon Salt Vanilla extract Honey Prep time: 5 minutes Cook time: 8 minutes Total time: 13 minutes Instructions Make cinnamon sugar: In a small bowl, mix 2 tablespoons sugar, 1 teaspoon cinnamon, and a tiny pinch of…
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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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Historical Counterfactual Analysis

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

GPT-5.6 Terra2,959 words
The answer depends heavily on what “invented in 1920” means. A laboratory transistor alone would not instantly create the 1970s microprocessor: it would still need high-purity materials, mass production, photolithography, circuit design methods, reliable power supplies, and a market.
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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…
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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…

GPT-5.6 Terra4,058 words
Guiding decision I would not wait for more data before acting. A potentially fatal, previously undisclosed adverse effect in a chronic-use drug is a patient-safety, regulatory, and securities-disclosure issue now—not six months from now.
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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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Mini LBO Underwrite

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

GPT-5.6 Terra696 words
All figures in $m unless noted. Assumptions used: Term Loan mandatory amortization = 1.0% of original principal annually ($4.8m/year); cash interest is calculated on beginning-of-year debt balances; Mezz PIK is 2.0% of beginning Mezz balance.
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Hy3354 words
1) Simplified LBO Model (FY2026–FY2030, $m) Entry (end FY25): EBITDA $120m, EV = 12.0x = $1,440m. Fees 2% = $28.8m. Debt: TL $480m (9% cash, 1% amort), Mezz $180m (12% cash + 2% PIK). Equity = 1,440+28.8–660 = $808.8m. FY Revenue EBITDA TL Int Mezz Int Cash Tax* Capex ΔNWC FCF after req. svc (opt.
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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.…

GPT-5.6 Terra1,229 words
“Our EEG headband decodes neural patterns into text with 94% accuracy. Works with any language, any device.” Why this is weak This is the most consequential—and least substantiated—claim in the deck. Non-invasive EEG has major signal-quality limits.
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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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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…

GPT-5.6 Terra1,113 words
Experienced software engineer Think of an LLM as a very large, learned function approximator for sequences. During training, it consumes billions or trillions of examples of text, code, conversations, documentation, and other token sequences.
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Hy3816 words
For the Experienced Software Engineer (distributed systems/APIs, no ML, skeptical) You’re used to building systems where explicit logic, endpoints, and state machines handle requests.
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Our Verdict
GPT-5.6 Terra
GPT-5.6 Terra
Hy3
Hy3

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

Hy3 costs 28x less per token.

Too close to call
API pricing

Cost per 1M tokens

GPT-5.6 Terra
Input
$2.50
Output
$15.00
Hy3
Input
$0.13
19× cheaper
Output
$0.53
28× cheaper

Hy3 is cheaper on both: 19× input, 28× output.

Where to run it

9 hosts, cheapest first

GPT-5.6 Terra3 hosts
HostInOutContextUptime
Azure AI Foundry$2.00 in·$12.00 out·1.1M·99.9% upOpenAI$2.00 in·$12.00 out·1.1M·100% upAmazon Bedrock$2.20 in·$13.20 out·1.1M·100% up
Hy36 hosts
HostInOutContextUptime
DDeepInfrafp4$0.13 in·$0.53 out·262k·99.7% upTencentfp8$0.13 in·$0.53 out·262k·99.9% upGGMI Cloudbf16$0.14 in·$0.58 out·262k·98.6% upNNovita$0.14 in·$0.58 out·262k·100% upPPhala$0.15 in·$0.64 out·262k·100% upAAtlasCloudfp8$0.20 in·$0.80 out·262k·99.9% up

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

Research

What we learned reading every model

FAQ

Common questions

GPT-5.6 Terra is developed by OpenAI while Hy3 is developed by Tencent. GPT-5.6 Terra has a 1.1M token context window vs Hy3's 262K. You can compare their actual outputs across 14 challenges on Rival to see how they differ in practice.

It depends on your use case. GPT-5.6 Terra and Hy3 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 14 challenges so you can judge which fits your needs best.

GPT-5.6 Terra costs $2.5/M input tokens and Hy3 costs $0.132/M input tokens. Hy3 is $2.37/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 GPT-5.6 Terra 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

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