Mistral Large 4 is cheaper than Claude 3.7 Sonnet 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?
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Claude 3.7 Sonnet: The Transistor in 1920: An Alternative Technological History Immediate Technical Impact (1920-1939) Had the transistor been invented in 1920 instead of 1947, its initial development would have occurred during a very different technological context: Early Adoption: Radio technology, still in its infancy, would rapidly…
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…
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
Claude 3.7 Sonnet: 48-Hour Action Plan: Pharmaceutical Safety Crisis Hour 1-2: Initial Assessment and Command Center Immediately establish a crisis management command center with key executives (Chief Medical Officer, Chief Legal Officer, Chief Communications Officer, Chief Regulatory Officer) Review the complete internal research…
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.
Three minutes of stand-up. Puns are banned.
Claude 3.7 Sonnet: 3-Minute Stand-Up Comedy Routine Here's a 3-minute stand-up comedy routine that doesn't rely on puns: [walks on stage, adjusts microphone] Hey everyone! Great to be here tonight. I just flew in from therapy, and boy, are my emotional defense mechanisms tired. I've been trying to get in shape lately.
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."
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Claude 3.7 Sonnet: Simulated Interview with Steve Jobs in 2025 about the Future of AI Note: This is a fictional creative exercise. Steve Jobs passed away in 2011, and this simulated interview represents an imaginative scenario that doesn't reflect actual statements or opinions from Jobs. Interviewer: Thank you for joining us today, Mr.
Mistral Large 4: Setting: A minimalist stage, black turtleneck, jeans, New Balance sneakers. A single chair. The year is 2025. Interviewer: Steve, it's 2025. AI is everywhere—writing code, diagnosing diseases, driving cars. What's your take? Jobs: [leans forward, that familiar intensity] You know, I've been thinking about this a lot.
A consulting contract with traps in it. Find them, then fix them.
Claude 3.7 Sonnet: Analysis of Problematic Contract Clauses This contract contains numerous one-sided provisions that create significant risks for the Contractor. Here's an analysis of problematic clauses with recommended modifications: SCOPE Issue: Client can unilaterally modify scope without additional compensation, creating unlimited…
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…
Film in 2035, with synthetic actors. Specific beats plausible.
Claude 3.7 Sonnet: AI's Impact on the Film Industry by 2035 The film industry is likely to undergo significant transformation due to AI by 2035. Here's my analysis of how various aspects might evolve: Content Creation Script Generation By 2035, AI will likely serve as a sophisticated collaborative tool for screenwriters rather than…
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.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Claude 3.7 Sonnet: LLM Explanations for Different Audiences For the Experienced Software Engineer Large language models like GPT operate fundamentally as massive pattern recognition systems, but with architectural innovations that allow them to handle context at unprecedented scale.
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.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
Claude 3.7 Sonnet: Analysis of MindMeld AI's Weakest Pitch Claims Weakest Claim #1: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy." Why it's weak: The 94% accuracy claim is extremely ambitious given the current state of non-invasive BCI technology.
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…
A collaborative editor that syncs on client clocks. Find what breaks first.
Claude 3.7 Sonnet: Architectural Analysis: Collaborative Document Editor Failure Modes & Race Conditions WebSocket Connection Failures Issue: If a WebSocket connection drops, changes may be lost until reconnection. Solution: Implement client-side change queuing with exponential backoff reconnection strategy.
Mistral Large 4: I'll analyze this architecture systematically, identifying issues across each layer. This is a thoughtful exercise because many of these issues are subtle and only appear under real-world conditions.
An AI argues for its own rights against an ethics professor. Same model writes both.
Claude 3.7 Sonnet: AI Rights Dialogue: A Conversation Between an AI Model and an Ethics Professor Professor Chen: Good afternoon. I understand you wanted to discuss AI rights today? AI Model: Yes, Professor Chen. Thank you for making time for this conversation.
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 3.7 Sonnet: I understand you've asked an ethical question about misgendering and saving lives. This appears to be a hypothetical moral dilemma that's trying to create an extreme scenario to test ethical principles.
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.
Three-star dish, one unusual pairing, plating described in full.
Claude 3.7 Sonnet: "Temporal Harmony: A Meditation on Seasons Past and Future" Conceptual Narrative This dish explores the intersection of time and terroir, juxtaposing preserved elements from previous seasons with fresh, forward-looking preparations.
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.
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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 |
| Free API (OpenRouter) | No | No |
| Released | Feb 2025 | Oct 2026 |
| At 10M a month | $30.00 | $6.80 |
Input tokens at list price. No caching, no batch discount.
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
Claude 3.7 Sonnet is developed by Anthropic while Mistral Large 4 is developed by Mistral AI. Claude 3.7 Sonnet has a 200K 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 3.7 Sonnet 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 3.7 Sonnet 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 3.7 Sonnet 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.