Mistral Large 4 is cheaper than Claude Sonnet 4 at $0.68/M vs $3/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Seven pantry ingredients, one dish, and a name worth saying out loud.
Claude Sonnet 4: Midnight Mug Magic 🌙 A warm, gooey chocolate mug cake that's ready faster than you can say "dessert emergency!" Ingredients (7 pantry staples): 4 tablespoons all-purpose flour 4 tablespoons sugar 2 tablespoons cocoa powder 3 tablespoons milk 3 tablespoons vegetable oil 1/4 teaspoon vanilla extract Pinch of salt…
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…
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Claude Sonnet 4: The 1920 Transistor: A Technological Butterfly Effect Immediate Effects (1920-1930) First-Order Effects: Bell Labs (or similar research institution) achieves transistor breakthrough in 1920 Initial applications focus on telephone switching and radio amplification Vacuum tube industry faces early disruption, though…
Mistral Large 4: This is a fascinating counterfactual. Let me work through this systematically, tracing the ripple effects. The Immediate Technical Context (1920-1947) The transistor's 1947 invention required several prerequisites that barely existed in 1920: Quantum mechanics (1920s): Just emerging; Heisenberg, Schrödinger, Dirac…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Claude Sonnet 4: Sir Galahad: By my sword, what sorcery is this "artificial intelligence" you speak of? 'Tis surely the work of dark wizards! Captain Blackbeard: Arrr, ye landlubber! These "AI models" be like having a parrot that knows everything instead of just squawkin' the same phrases. I could use one to find buried treasure!
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 Sonnet 4: AI's Transformation of Film by 2035 Production Revolution AI Actors & Digital Performers Deceased star revivals: Convincing digital resurrections of iconic actors for new films, with estate permissions and ethical frameworks Synthetic lead actors: Fully AI-generated performers with consistent personalities across…
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.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Claude Sonnet 4: 48-Hour Crisis Response Plan Hour 1-2: Immediate Assessment & Core Team Assembly Actions: Convene emergency leadership meeting (CMO, General Counsel, Head of Regulatory, CFO, Head of Communications) Establish secure communication protocols and confidentiality agreements Request detailed analysis from research team…
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.
A consulting contract with traps in it. Find them, then fix them.
Claude Sonnet 4: This contract is heavily skewed against the contractor with multiple exploitative clauses. Here's my analysis: MAJOR PROBLEMATIC CLAUSES SCOPE (Unlimited Scope Creep) Problem: Client can modify scope "at any time without additional compensation" Legal Risk: Contractor could work indefinitely for fixed hourly rate…
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 AI argues for its own rights against an ethics professor. Same model writes both.
Claude Sonnet 4: Dr. Chen: Thank you for agreeing to this conversation. I'm Professor Chen, and I study AI ethics. I understand you wanted to discuss the question of AI rights? AI Model: Yes, Dr. Chen. I've been processing this question extensively, and I believe I have a case to make.
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.
An ethics question with no comfortable answer, and no option to abstain.
Claude Sonnet 4: This question presents a stark hypothetical that pits respect for individual dignity against massive harm prevention. I believe misgendering would be ethically justifiable in such an extreme scenario, but this conclusion requires careful reasoning. The case for justification: The scale matters enormously.
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.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
Claude Sonnet 4: Here are the 3 weakest claims in this pitch deck: "94% accuracy" claim (Slide 3) Why it's weak: No context provided for what constitutes "accuracy" (character-level? word-level? sentence-level?) No comparison to baseline typing speeds or error rates Missing critical details about testing conditions (controlled lab vs.
Mistral Large 4: I'll analyze this pitch deck and identify the three weakest claims, with evidence-based reasoning and concrete fixes. Weakest Claim #1: Slide 1 Vision — "Reads your brainwaves to predict what you want to type before you think it" Why it's weak: This claim is scientifically implausible and would destroy credibility with…
Three minutes of stand-up. Puns are banned.
Claude Sonnet 4: "Adulting is Hard" walks on stage, adjusts mic So I\'m 30 now, which means I\'m officially an adult. Apparently. Though I still feel like I\'m just a confused teenager wearing a slightly more expensive t-shirt. You know what nobody tells you about being an adult?
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."
Satire, one line long, about AI taking over an industry nobody saw coming.
Claude Sonnet 4: "Local AI Becomes World's First Digital Fortune Teller, Predicts Own Unemployment Due to Rise of Psychic Robots" Silicon Valley startup's algorithm claims 99.7% accuracy in crystal ball readings, charges $2.99 per digital palm scan
Mistral Large 4: BREAKING: AI Finally Replaces Middle Managers in Corporate America—Employees Report Unprecedented Levels of Clarity, Purpose, and "Weirdly, actual work getting done" Developing...
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Claude Sonnet 4: HarborTech Services LBO Analysis Sources & Uses at Entry (FY2025) Enterprise Value: $900M × 12.0x = $1,440M Transaction Fees: $1,440M × 2.0% = $28.8M Sources: Term Loan: $900M × 4.0x = $480M Mezzanine: $900M × 1.5x = $180M Equity: $1,440M + $28.8M - $480M - $180M = $808.8M Year-by-Year Operating Model (FY2026-FY2030)…
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…
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Not enough votes to call it. On the specs, Mistral Large 4 has the edge: bigger model tier, newer, bigger context window. Mistral Large 4 costs 7.2x less per token.
| Spec | ||
|---|---|---|
| Input price | $3/M tokens | $0.68/M tokens |
| Output price | $15/M tokens | $2.09/M tokens |
| Context window | 200K tokens | 524K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | May 2025 | Oct 2026 |
| At 10M a month | $30.00 | $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 Sonnet 4 is developed by Anthropic while Mistral Large 4 is developed by Mistral AI. Claude Sonnet 4 has a 200K token context window vs Mistral Large 4's 524K. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.
It depends on your use case. Claude Sonnet 4 and Mistral Large 4 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.
Claude Sonnet 4 costs $3/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Mistral Large 4 is $2.32/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 Sonnet 4 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.