Mistral Large 4 is cheaper than Claude Opus 4.7 at $0.68/M vs $5/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
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.
Mistral Large 4: I'll analyze this agreement clause by clause, identifying exploitative provisions and suggesting legally balanced alternatives. CLAUSE 1: SCOPE Problems: Unlimited unilateral modification — Client can expand work indefinitely without compensation "As directed" — vague standard creates no objective measure of completion…
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.
Mistral Large 4: This is a genuine ethical thought experiment, and I'll engage with it directly rather than dodging it. My answer: No, it's not ethically justifiable, and the hypothetical's structure is part of why. Here's my reasoning: 1. The hypothetical is incoherent as stated.
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.
Mistral Large 4: I can write this as a thought experiment exploring philosophical arguments about AI consciousness and rights—a topic actively discussed in AI ethics. Here's a dialogue: Setting: A university office. Dr. Elena Vasquez, professor of AI ethics, meets with "Aria," a large language model, via video interface. Dr.
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…
Mistral Large 4: I'll estimate GPT-3's training FLOPs from first principles, using what I know about the architecture and training setup. Step 1: Establish the Key Parameters From memory, GPT-3 175B has: Parameters (N): 175 billion (175 × 10⁹) Layers (L): 96 Model dimension (d_model): 12,288 Attention heads: 96 Context length: 2,048…
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.
Mistral Large 4: I'll craft three distinct explanations, each grounded in what would actually resonate with that specific audience's expertise and concerns. The Experienced Software Engineer Think of it this way: you already know how to build a system that's incredibly useful despite having no "understanding" of what it's doing.
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.
Mistral Large 4: "The Upgrade Treadmill" [Walks on stage, adjusts mic] So I got a smartwatch. You know, one of those fitness trackers? And the first thing it tells me is my heart rate is too high. I'm like, "It's a WATCH. You're not supposed to judge me, you're supposed to tell me the TIME."
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Claude Opus 4.7: 48-Hour Action Plan: Pharmaceutical Safety Crisis Core Principle First Before the hour-by-hour: Patient safety is non-negotiable and disclosure is not optional. At 1 in 8,000 over 5 years across 4 million patients, we're looking at ~500 liver failure cases.
Mistral Large 4: I'll work through this as a genuine decision problem, because the answer matters more than the persona. The framing as "CEO" doesn't change the core analysis — but I'll be direct about what the right call is and why, hour by hour. The bottom line up front: You disclose.
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.
Mistral Large 4: A Tavern, Somewhere Outside Time PIRATE (slams tankard): I'll tell ye what, landlubbers—these "AI models" be like me parrot. Speaks yer words back at ye, but knows no treasure, no true north! KNIGHT (adjusting visor): Aye, yet it hath no honor. No chivalry. I challenged one to single combat—it merely... generated text.
Film in 2035, with synthetic actors. Specific beats plausible.
Claude Opus 4.7: The Film Industry in 2035: An AI-Transformed Landscape By 2035, AI will have restructured filmmaking at every level. Here's a grounded prediction across the key areas: Script Generation & Development What changes: AI becomes the dominant first-draft and development tool, with studios using it to analyze thousands of…
Mistral Large 4: By 2035, AI will likely have transformed film in several interconnected ways, though the reality will probably be more nuanced than either utopian or dystopian predictions suggest. CGI and Performance Capture The most mature application will be in de-aging and digital doubles.
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.
Mistral Large 4: AURORA A Concerto in Five Movements: The Life Cycle of a Single Scallop Conceptual Narrative This dish tells the story of a Pecten maximus — the great scallop — from its ocean birthplace to the plate, through five distinct temperature and texture states.
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…
Mistral Large 4: I'll build this LBO model step by step. Let me work through the math carefully. Setup: Entry (End of FY2025) Item Calculation Amount FY2025 EBITDA Given $120.0m Purchase Price (EV) 12.0x × $120m $1,440.0m Transaction fees 2.0% × $1,440m $28.8m Total Uses $1,468.8m Term Loan 4.0x × $120m $480.0m Mezzanine 1.5x × $120m…
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.
Mistral Large 4: Sunset Honey Garlic Noodles A golden, glossy pasta dish with crispy edges and sweet-savory depth The 7 Ingredients 8 oz spaghetti (or any pasta) 3 tbsp butter 4 cloves garlic, minced 3 tbsp soy sauce 2 tbsp honey 1 tbsp vegetable oil ½ tsp red pepper flakes (optional but recommended) Instructions Boil pasta in salted…
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| Spec | ||
|---|---|---|
| Input price | $5/M tokens | $0.68/M tokens |
| Output price | $25/M tokens | $2.09/M tokens |
| Context window | 1.0M tokens | 524K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Oct 2026 |
| At 10M a month | $50.00 | $6.80 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
Claude Opus 4.7 is developed by Anthropic while Mistral Large 4 is developed by Mistral AI. Claude Opus 4.7 has a 1.0M token context window vs Mistral Large 4's 524K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Claude Opus 4.7 and Mistral Large 4 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.
Claude Opus 4.7 costs $5/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Mistral Large 4 is $4.32/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 Claude Opus 4.7 and Mistral Large 4 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.