GPT-5.5 is cheaper than Mercury at $5/M vs $10/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-5.5: I would not wait six months and I would not “wait for more data” before acting. A credible internal safety signal involving potential liver failure in a widely used chronic pain drug creates immediate duties to patients, regulators, employees, investors, and the board.
Mercury: 48‑Hour Action Plan (CEO‑Level) Time (UTC) Action Who Leads Key Deliverables / Outcomes Rationale 0–2 h Secure the facts – Convene an emergency “Safety & Compliance” meeting with the Chief Medical Officer (CMO), Chief Legal Officer (CLO), Chief Risk Officer (CRO), and the Head of Regulatory Affairs (RA).
One month, three habits, someone starting from nothing.
GPT-5.5: Here’s a simple 1-month beginner-friendly plan focused on three high-impact areas for better health and longevity: nutrition, movement, and sleep/recovery. If you have a medical condition, take medications, or haven’t exercised in a while, consider checking with a healthcare professional first.
Mercury: 1‑Month Health & Longevity Starter Plan (Designed for absolute beginners – no fancy gear, no extreme diets, just doable habits that fit into a normal week.) 1️⃣ Focus Area: Balanced Nutrition Week Goal Simple, Beginner‑Friendly Actions 1 Get the basics down • Hydrate: Aim for 8‑10 cups (≈2 L) of water per day.
Three minutes of stand-up. Puns are banned.
GPT-5.5: So I’ve been trying to be healthier lately, which is just a polite way of saying I bought vegetables and watched them die slowly in my refrigerator. Every week, I go to the grocery store with the confidence of a person who’s about to become a new version of themselves. I’m like, “This week? Spinach. Salmon.
Mercury: Title: The Art of Being Unorganized [Opening] Hey everyone! So, I was thinking about how my life is like a well-organized library... except instead of books, it's filled with random socks and expired coupons. And instead of a librarian, I have a cat who thinks she's in charge.
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-5.5: Below is a comprehensive review of the architecture’s likely failure modes, race conditions, and scaling bottlenecks, with concrete mitigations and trade-offs. Real-time Synchronization Problems 1.1 Broadcasting only to clients on the same server Problem Each API server only broadcasts WebSocket changes to clients…
Mercury: Below is a systematic review of the described real‑time collaborative editor. For each problem I list: What can go wrong (failure mode, race condition, bottleneck) Why it matters (impact on correctness, latency, availability) A concrete fix (what to change or add) Trade‑offs (cost, complexity, new failure modes, etc.)
Blade Runner 2049 against the original. A read, not a recap.
GPT-5.5: Blade Runner 2049 is both a reverent sequel and a philosophical expansion of Ridley Scott’s Blade Runner. Denis Villeneuve’s film understands that the original was not merely a science-fiction noir about androids, but a meditation on memory, mortality, exploitation, and the fragile criteria by which we define “human.”
Mercury: Blade Runner 2049 arrives a decade after the 1982 classic, yet it feels both a continuation and a reimagining of the same speculative universe. Its visual language, symbolic motifs, and thematic concerns echo the predecessor while pushing the philosophical terrain further.
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-5.5: Smoky Sunset Chickpea Skillet 7 Pantry Ingredients 1 can chickpeas, undrained 1 can diced tomatoes 2 tablespoons olive oil 1 teaspoon garlic powder 1 teaspoon smoked paprika 1/2 teaspoon ground cumin 1/2 teaspoon salt Estimated Time Prep time: 5 minutes Cook time: 15 minutes Total time: 20 minutes Instructions Heat the…
Mercury: Golden Chickpea & Sweet Potato Stew Prep time: 10 min Cook time: 25 min Total: 35 min Ingredients (7 pantry staples) 1 cup canned chickpeas, drained & rinsed 1 medium sweet potato, peeled & diced (≈ 1 cup) 1 small onion, finely chopped 2 cloves garlic, minced ½ cup coconut milk (or any plant‑based milk) 2 tsp curry…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
GPT-5.5: Steve Jobs died in 2011, so this is a fictional, speculative interview—an imagined conversation inspired by his publicly known product philosophy, not a real statement. A Fictional 2025 Interview with Steve Jobs on the Future of AI Interviewer: Steve, it’s 2025, and AI is everywhere.
Mercury: Interviewer: Good morning, Steve. It's a pleasure to have you here today. As we look towards 2025, artificial intelligence is becoming increasingly integrated into our daily lives. What are your thoughts on the future of AI? Steve Jobs: Good morning. It's great to be here.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GPT-5.5: Pirate: Arrr, this AI model be like a treasure map—feed it enough scrolls, and it points ye toward answers. Knight: A curious enchantment indeed. Yet can it reason with honor, or merely mimic the bards who trained it? Hacker: Dude, it’s basically pattern recognition at massive scale.
Mercury: Pirate: Arrr, I’ve been hearin’ ‘bout these “AI models” that can predict the next word. Sounds like a treasure map for the mind, doesn’t it? Knight: Hail, Captain! In my time, we relied on scrolls and the wisdom of scholars. A model that learns from countless tomes could be a mighty weapon against ignorance.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
GPT-5.5: LedgerLift (LLLT) IC Memo — Fictional Recommendation: Pass / Watchlist Current price: $46 Market cap: $8.7B; EV: $7.3B after $1.4B net cash 12-month fair value range: $40–$50/share Thesis, 2 sentences: LedgerLift is a high-quality mid-market spend management/AP automation SaaS asset with 92% subscription revenue, 123%…
Mercury: Investment Committee Memo – LedgerLift (LLLT) Prepared for: Long/Short Equity Committee Date: 8 Feb 2026 Recommendation Long – target price $25–$30 (12‑month horizon). Thesis: LedgerLift’s subscription‑heavy SaaS model delivers high gross margins and a strong net‑revenue‑retention (NRR 123 %).
Three-star dish, one unusual pairing, plating described in full.
GPT-5.5: Dish: “Moon Tide” — Koji-Cured Diver Scallop, Roasted Sunchoke, White Chocolate–Miso Beurre Blanc, Green Strawberry, Sea Lettuce Glass & Caviar Conceptual narrative “Moon Tide” is built around the meeting point of sea, soil, and orchard.
Mercury: Dish Title: Eclipse of the Ocean & Forest Concept: A multi‑component, molecular‑gastronomy inspired plate that juxtaposes the briny depth of the sea with the earthy richness of the forest.
Film in 2035, with synthetic actors. Specific beats plausible.
GPT-5.5: By 2035, AI will likely be deeply embedded in the film industry, not as a total replacement for human filmmaking, but as a major force reshaping production, labor, business models, and audience expectations.
Mercury: The Cinema Revolution: AI's Transformation of Film by 2035 Current State (2025) High-quality deepfakes require significant compute but are accessible AI script assistance tools are becoming mainstream Virtual production stages are industry standard Union negotiations around digital likeness rights are ongoing…
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-5.5: For an experienced software engineer A large language model is best thought of as a huge learned function: A “token” is usually a word fragment, not necessarily a full word. During training, the model is shown trillions of tokens of text and repeatedly asked: “given this prefix, what token came next?”
Mercury: 1. Experienced Software Engineer (Distributed‑Systems Background) A large language model (LLM) is essentially a massive, highly parallelized neural network that learns to predict the probability distribution over the next token in a sequence.
12+ more head-to-head results. Free. Not a trick.
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Not enough votes to call it. On the specs, GPT-5.5 has the edge: bigger model tier, newer, bigger context window, major provider backing. Mercury costs 3.0x less per token.
| Spec | ||
|---|---|---|
| Input price | $5/M tokens | $10/M tokens |
| Output price | $30/M tokens | $10/M tokens |
| Context window | 1.1M tokens | 32K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Jun 2025 |
| At 10M a month | $50.00 | $100 |
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-5.5 is developed by OpenAI while Mercury is developed by Inception. GPT-5.5 has a 1.1M token context window vs Mercury's 32K. 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-5.5 and Mercury 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-5.5 costs $5/M input tokens and Mercury costs $10/M input tokens. GPT-5.5 is $5.00/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-5.5 and Mercury 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.