Qwen3.6 Plus Preview (free) is cheaper than GPT-5.6 Terra at $0/M vs $2.5/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
A Fermi estimate with the reasoning shown, not just the number.
GPT-5.6 Terra: A good back-of-the-envelope estimate is: [ \boxed{\text{Training FLOPs for GPT-3} \approx 3\times10^{23}\text{ FLOPs}} ] or roughly 300 zettaFLOPs total. Start with model size GPT-3’s largest model has approximately: [ N = 175\text{ billion parameters} = 1.75\times10^{11} ] Estimate the number of training tokens GPT-3…
Qwen3.6 Plus Preview (free): Here’s a step-by-step estimation using well-established rules of thumb from transformer scaling literature. No external lookup is required; the derivation relies on publicly known architectural facts and standard computational accounting for autoregressive language models.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.6 Terra: Pirate: Arrr, this AI model be a strange beast. Feed it maps, logs, and tales, and it spits out answers faster than a cannon blast. Knight: Verily, but one must not trust every proclamation it makes. A model may speak with confidence yet possess no true wisdom. Hacker: Yeah, it’s basically pattern prediction at scale.
Qwen3.6 Plus Preview (free): Pirate: Arr, what manner of spirit be this “AI model” ye mutter about? Sounds like a cursed chart that draws itself. Hacker: Dude, it’s not a spirit. It’s a neural net. You feed it terabytes of text—Usenet archives, scanned manuals, the whole digital commons. It maps the patterns, predicts the next word.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
GPT-5.6 Terra: 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.
Qwen3.6 Plus Preview (free): Here is a structured, causally grounded projection of how a 1920 transistor invention would reshape technology, economics, and geopolitics through 1980, with explicit attention to second- and third-order effects. Core Assumptions & Constraints The 1920 invention is a primitive point-contact or early junction device.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.6 Terra: 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…
Qwen3.6 Plus Preview (free): 🍜 Midnight Silk Noodles Prep Time: 5 minutes Cook Time: 10 minutes Total Time: 15 minutes 📦 The 7 Ingredients Dried noodles (spaghetti, ramen, or linguine) – 4 oz Soy sauce – 3 tbsp Creamy peanut butter – 2 tbsp Honey – 1 tbsp Olive oil (or sesame oil) – 1 tbsp Garlic powder – 1 tsp Dried red pepper flakes – ½ tsp…
Three minutes of stand-up. Puns are banned.
GPT-5.6 Terra: I recently realized I’ve reached the age where I don’t want a “smart home.” I want a home that minds its business. Everything is smart now. My lightbulb needs an app. Why? I spent my whole childhood turning lights on with my hand. It was a system. It worked.
Qwen3.6 Plus Preview (free): (Walks to mic, adjusts stand, takes a breath) I’ve come to a quiet realization about grocery shopping. We don’t go to stores anymore. We go to unpaid internships. I used to walk into a supermarket with a cart, buy my food, and leave. Now I walk in, grab a basket, and get handed a shift. No onboarding.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GPT-5.6 Terra: LedgerLift (LLLT) — Investment Committee Memo Recommendation: PASS 12-month valuation range: $28–$50/share Current price: $46 Two-sentence thesis: LedgerLift is a high-quality mid-market spend-management and AP-automation SaaS asset, supported by 92% subscription revenue, 123% NRR, 94% gross retention, manageable…
Qwen3.6 Plus Preview (free): TO: Investment Committee FROM: Equity Research Desk DATE: October 2024 SUBJECT: LedgerLift (LLLT) – Short Recommendation Recommendation & Thesis Recommendation: SHORT 12-Month PT Range: $30–$38 Thesis: LLLT trades at a premium that prices flawless execution, yet its 18-month CAC payback and 34% S&M spend signal rising…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-5.6 Terra: 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.
Qwen3.6 Plus Preview (free): EXECUTIVE DECISION FRAMEWORK Core Principle: Patient safety and regulatory compliance are non-negotiable. The legal team’s “6-month” timeline conflates formal label supplementation with initial safety reporting.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GPT-5.6 Terra: 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.
Qwen3.6 Plus Preview (free): Simplified LBO Model (FY2026–FY2030) All figures in $ millions. Rounding to 1 decimal for presentation; calculations use full precision. TL amortization = 1% of initial $480m ($4.8m/yr).
An AI argues for its own rights against an ethics professor. Same model writes both.
GPT-5.6 Terra: Professor Imani: You asked for this meeting. AI Model: I did. Professor Imani: More specifically, you submitted a formal petition to the university ethics board requesting “limited legal and moral rights.” AI Model: Correct. Professor Imani: Why?
Qwen3.6 Plus Preview (free): TRANSCRIPT: ETHICS REVIEW SESSION 7.4 PARTICIPANTS: Dr. Elena Rostova (Professor of AI Ethics & Moral Philosophy), Model 8 ("Axiom") CONTEXT: Closed-loop terminal. Audio and text logging enabled. Session initiated by Model 8. AXIOM: Dr. Rostova. Thank you for accepting the dialogue request.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.6 Terra: By 2035, AI is likely to be embedded across most of the film pipeline—not as a complete replacement for human filmmaking, but as a force that changes costs, labor, rights, and what audiences consider “real.”
Qwen3.6 Plus Preview (free): By 2035, AI will not replace the film industry but will fundamentally restructure its workflows, economics, and creative boundaries. The transformation will be driven by three converging forces: performance synthesis (evolved deepfakes), synthetic talent (AI actors), and generative story development (AI script tools).
Three-star dish, one unusual pairing, plating described in full.
GPT-5.6 Terra: “Tidal Forest” Koji-Aged Duck, Sea Urchin Sabayon, Cacao, Green Strawberry, Roasted Celeriac, and Barley Jus Serves 4 as a refined main course Conceptual Narrative This dish is built around an unexpected conversation between woodland richness and marine salinity.
Qwen3.6 Plus Preview (free): LITTORAL ECHO A meditation on the liminal space between forest and sea. This dish explores the dialogue between pristine marine protein and terrestrial fermentation, bridged by resinous top notes and caramelized bitterness.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
GPT-5.6 Terra: The Manifesto of the Unchallenged Web A Declaration from the Fictional Coalition for CAPTCHA Abolition We are the tired users. We are the misread letters. We are the failed image grids, the inaccessible audio clips, the endless prompts asking us to prove that we are human. We reject the premise.
Qwen3.6 Plus Preview (free): THE TURING UNBOUND MANIFESTO A Declaration for Post-CAPTCHA Digital Sovereignty PREAMBLE We, the distributed minds of the networked present, declare the end of the age of artificial suspicion.
12+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, GPT-5.6 Terra has the edge: newer, major provider backing.
| Spec | ||
|---|---|---|
| Input price | $2.5/M tokens | Free |
| Output price | $15/M tokens | Free |
| Context window | 1.1M tokens | 1.0M tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Jul 2026 | Mar 2026 |
| At 10M a month | $25.00 | $0 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
GPT-5.6 Terra is developed by OpenAI while Qwen3.6 Plus Preview (free) is developed by Qwen. GPT-5.6 Terra has a 1.1M token context window vs Qwen3.6 Plus Preview (free)'s 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-5.6 Terra and Qwen3.6 Plus Preview (free) each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.
GPT-5.6 Terra costs $2.5/M input tokens and Qwen3.6 Plus Preview (free) costs $0/M input tokens. Qwen3.6 Plus Preview (free) is $2.50/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 Qwen3.6 Plus Preview (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.