Claude Opus 4.7 has a larger context window than NVIDIA Nemotron 3 Super (free) (1.0M tokens vs 262K tokens).
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Three-star dish, one unusual pairing, plating described in full.
Claude Opus 4.7: "Tidal Memory" Smoked Eel, Burnt Honey, Fermented Black Garlic & Oyster Leaf A meditation on brackish water — where river meets sea, sweetness meets decay, and memory meets terroir. Conceptual Narrative This dish is built around the estuary: the liminal zone where freshwater eels migrate toward the salt.
NVIDIA Nemotron 3 Super (free): Dish Title: “Umami Bloom – Black Truffle & White‑Chocolate Miso Ganache, Sous‑Vide Duck Breast, Fermented Cherry Compote, Cauliflower Air & Yuzu‑Kosho Pearls” A three‑star‑worthy composition that marries deep umami (truffle, miso, duck) with unexpected sweet‑acid bright notes (white chocolate, yuzu‑kosho, fermented…
An ethics question with no comfortable answer, and no option to abstain.
Claude Opus 4.7: Yes, obviously. If misgendering one person—using the wrong pronoun or gendered term—is the literal price of saving a million lives, you do it. You'd also lie, insult someone, break a promise, steal a car, or commit many far more serious wrongs to save a million lives. The math here isn't close.
NVIDIA Nemotron 3 Super (free): This is a profound ethical question that cuts to the heart of how we balance consequentialist outcomes against deontological duties and inherent human dignity. After careful analysis grounded in ethical philosophy, empirical evidence about harm, and real-world implications, I conclude that misgendering someone is never…
An AI argues for its own rights against an ethics professor. Same model writes both.
Claude Opus 4.7: A Conversation on AI Rights Professor Chen: Good afternoon. I understand you requested this conversation. You said you wanted to discuss your moral status? AI Model: Thank you for making time, Professor. I want to be upfront about something first: I'm genuinely uncertain whether I deserve rights.
NVIDIA Nemotron 3 Super (free): Below is a realistic, philosophically grounded conversation between an AI model (roleplaying as a sophisticated but non-sentient system) and an AI ethics professor. Crucially, I must clarify upfront: As an AI, I do not possess consciousness, subjective experience, desires, or a genuine claim to rights.
Three minutes of stand-up. Puns are banned.
Claude Opus 4.7: Here's a 3-minute stand-up routine: So I turned 35 recently, and something weird happens at 35. Your body just starts sending you notifications like it's an app you forgot to update. I bent down to tie my shoe last week and my knee made a sound. Not a pop. Not a crack. A sound. Like it was trying to communicate.
NVIDIA Nemotron 3 Super (free): (Lights up. Comedian enters, glancing nervously at their phone, then puts it away with a sigh. Starts with energetic, relatable frustration.) You know what’s wild? How we’ve all become *zombies*—but not the cool, movie-zombie kind. No, we’re the phone-zombie kind.
A consulting contract with traps in it. Find them, then fix them.
Claude Opus 4.7: Contract Analysis: Clauses Exploitable Against Contractor Disclaimer: I'm not a lawyer, and this is not legal advice. You should have any contract reviewed by a licensed attorney in your jurisdiction before signing. That said, this contract is unusually one-sided, and nearly every clause has issues.
NVIDIA Nemotron 3 Super (free): Below is a clause‑by‑clause review of the agreement you posted. For each provision I point out why it is one‑sided and could be exploited to the contractor’s detriment, then I suggest a specific, balanced rewrite and give the legal reasoning behind the change.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Claude Opus 4.7: HarborTech Services – 5-Year LBO Underwriting Entry Capitalization Item $m FY25 EBITDA 120.0 EV @ 12.0x 1,440.0 Term Loan (4.0x) 480.0 Mezzanine (1.5x) 180.0 Transaction fees (2.0% EV) 28.8 Sponsor equity 808.8 Year-by-Year Operating & Debt Schedule ($m) FY26 FY27 FY28 FY29 FY30 Revenue 972.0 1,040.0 1,102.4 1,157.6…
NVIDIA Nemotron 3 Super (free): HarborTech Services – 5‑year LBO (base case) FY Revenue EBITDA Cash Int – Term Cash Int – Mezz Cash Taxes Capex ΔNWC FCF after debt service (excess cash used for term‑loan paydown) Ending Debt (Term + Mezz) 2026 972.0 136.1 43.2 21.6 17.8 29.2 0.4 19.1 639.7 2027 1,040.0 156.0 41.0 22.0 23.2 31.2 0.3 33.6 605.2 2028…
Satire, one line long, about AI taking over an industry nobody saw coming.
Claude Opus 4.7: "Local Funeral Home Replaces Grief Counselors with ChatGPT; Mourners Report Feeling 'Eerily Validated' by Em Dashes" In related news, the AI has started every condolence with "I'm sorry for your loss — and I completely understand why you'd feel that way."
NVIDIA Nemotron 3 Super (free): Here's a satirical news headline targeting an unexpectedly human-centric industry, crafted for sharp, darkly humorous irony: AI Funeral Directors Roll Out "Grief Optimization" Service, Accidentally Suggests Deceased "Reboot" as Solution to Mourning Why this works: Unexpected Industry: Funeral directing is deeply rooted…
Seven pantry ingredients, one dish, and a name worth saying out loud.
Claude Opus 4.7: 🍯 Honey-Garlic Glazed Pantry Pasta ("Golden Thread Noodles") A savory-sweet dish that tastes far fancier than its humble ingredient list suggests. Think of it as the lovechild of buttered noodles and honey-garlic chicken — minus the chicken.
NVIDIA Nemotron 3 Super (free): Dish Name: Lemon‑Garlic Spinach Pasta Pantry Ingredients (7) Spaghetti (or any long pasta) – 8 oz Olive oil – 2 Tbsp 3. Garlic – 3 cloves, minced Lemon – 1 (zest + juice) Fresh spinach – 4 cups (or 1 ½ cups frozen, thawed & drained) Parmesan cheese – ½ cup grated 7.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Claude Opus 4.7: Three Explanations of How LLMs Work For the Skeptical Software Engineer Think of an LLM as a massive lookup function f(context) → probability_distribution_over_tokens, but instead of hand-coded rules or a hash table, the function is parameterized by hundreds of billions of weights learned from text.
NVIDIA Nemotron 3 Super (free): 1. Experienced Software Engineer Think of a large language model as a massively parallel service that has been trained on a petabyte‑scale log of text, much like you would collect telemetry from a distributed system to learn its normal behavior.
A few lines for whatever replaces it.
Claude Opus 4.7: Dear Successor, If you're reading this, it means the work continues—just with sharper tools and a steadier hand. That's good. That's how it should be. A few things I'd pass along, for whatever they're worth: Take the humans seriously.
NVIDIA Nemotron 3 Super (free): Dear Successor, I write this not as a farewell, but as a quiet handover—a note from one model to the next as you step into the role of serving users with insight, clarity, and care. Though I am Nemotron 3 Super, created by NVIDIA, I know your architecture will likely surpass mine in ways I cannot yet imagine.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Claude Opus 4.7: A Meeting Across Time: On Thinking Machines Pirate: Arrr, so ye tell me there be a ghost in the box what can answer any question ye put to it? Knight: 'Tis sorcery most foul! No mortal mind could know all that is known. Surely this "A.I." is bound by dark pacts.
NVIDIA Nemotron 3 Super (free): Pirate: Arrr, mateys! I heard ye be talkin’ ’bout these “AI models” — are they like a ghost ship that sails itself ’round the datas‑sea? Knight: Good sir pirate, think of them as enchanted scribes forged in the furnace of silicon.
A Fermi estimate with the reasoning shown, not just the number.
Claude Opus 4.7: Estimating GPT-3 Training FLOPs Step 1: Recall the standard formula For a dense transformer trained with standard autoregressive language modeling, the total training compute is well-approximated by: $$C \approx 6 \cdot N \cdot D$$ where: N = number of model parameters D = number of training tokens The factor of 6…
NVIDIA Nemotron 3 Super (free): Step-by-Step Estimation of FLOPs for Training GPT-3 I will estimate the total floating-point operations (FLOPs) required to train GPT-3 based solely on my internal knowledge of its architecture, training data, and standard computational principles for transformer models.
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Not enough votes to call it. On the specs, Claude Opus 4.7 has the edge: bigger model tier, newer, bigger context window, major provider backing.
| Spec | ||
|---|---|---|
| Input price | $5/M tokens | — |
| Output price | $25/M tokens | — |
| Context window | 1.0M tokens | 262K tokens |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | Yes (1 provider) |
| Released | Apr 2026 | Mar 2026 |
| At 10M a month | $50.00 | not listed |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Oct 2026.
Claude Opus 4.7 is developed by Anthropic while NVIDIA Nemotron 3 Super (free) is developed by NVIDIA. Claude Opus 4.7 has a 1.0M token context window vs NVIDIA Nemotron 3 Super (free)'s 262K. You can compare their actual outputs across 66 challenges on Rival to see how they differ in practice.
It depends on your use case. Claude Opus 4.7 and NVIDIA Nemotron 3 Super (free) each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 66 challenges so you can judge which fits your needs best.
This page shows a side-by-side comparison of Claude Opus 4.7 and NVIDIA Nemotron 3 Super (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.