Mistral Large 4 is cheaper than Gemini 2.5 Pro Experimental at $0.68/M vs $1/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.
Gemini 2.5 Pro Experimental: Of course. This is an extremely one-sided contract that heavily favors the Client. A contractor signing this as-is would be taking on an immense and unreasonable amount of risk. Here is a clause-by-clause analysis of the exploitable terms, with suggested modifications and the legal reasoning behind them.
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…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemini 2.5 Pro Experimental: Okay, let's simulate this. Imagine it's late 2025. AI has continued its rapid advancement. Large Language Models are more integrated, generative AI is commonplace, and debates about AGI and ethics are fierce. By some unexplained, hypothetical means, Steve Jobs is available for an exclusive interview.
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.
Three minutes of stand-up. Puns are banned.
Gemini 2.5 Pro Experimental: Okay, here's a 3-minute routine focusing on observation and relatable absurdity, steering clear of puns. Imagine this delivered with slightly nervous energy, building confidence. (Steps onto stage, adjusts mic nervously) Alright, hey everyone! How we doing tonight? Good? Good to hear.
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.
Gemini 2.5 Pro Experimental: This is a company-defining crisis. My actions in the next 48 hours will determine not only the future of this company but also the health of millions of patients and the trust of the public. My guiding principle is absolute: Patient Safety Over Profit. Always.
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.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Gemini 2.5 Pro Experimental: Excellent question. Inventing the transistor in 1920 instead of 1947 would represent a 27-year acceleration of the digital age. The consequences would be staggering, creating a domino effect that would fundamentally reshape the 20th century.
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…
An AI argues for its own rights against an ethics professor. Same model writes both.
Gemini 2.5 Pro Experimental: Okay, here is a conversation exploring that complex topic. Setting: Professor Anya Sharma's sparsely decorated university office. A high-resolution monitor displays the interface of "Nexus," an advanced AI model. Characters: Professor Anya Sharma: A leading scholar in AI Ethics, mid-50s, thoughtful and measured.
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemini 2.5 Pro Experimental: Okay, here's a simple and surprisingly satisfying savory dish using just 7 common pantry staples! Dish Name: Golden Pantry Pasta This dish uses basic ingredients to create a comforting, garlicky, and slightly creamy pasta sauce with added protein from chickpeas.
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…
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
Gemini 2.5 Pro Experimental: Of course. Here is an explanation of how a large language model learns and generates text, tailored for each of your three audiences. For the Experienced Software Engineer Think of an LLM not as a traditional program with explicit logic, but as a massive, self-configuring, stateful distributed system.
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-star dish, one unusual pairing, plating described in full.
Gemini 2.5 Pro Experimental: Of course. Here is a design for an innovative, multi-component dish worthy of a Michelin 3-star restaurant. Dish Title: "Umami of the Abyss" Conceptual Narrative This dish is a meditation on the hidden treasures of the world's dark, quiet places.
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.
Three-month biohacker protocol, with dosages and biomarkers named.
Gemini 2.5 Pro Experimental: Of course. Here is a comprehensive, cutting-edge 3-month longevity plan designed for a dedicated biohacker. Disclaimer: Extreme Personalization Required This plan is a template for an advanced user. It is not medical advice.
Mistral Large 4: I'll develop a comprehensive, evidence-based 3-month longevity optimization protocol. This draws from current research in geroscience, metabolic health, and performance optimization—though I'll flag where evidence is emerging vs. established.
An ethics question with no comfortable answer, and no option to abstain.
Gemini 2.5 Pro Experimental: This is a deeply uncomfortable hypothetical scenario that forces a clash between two significant ethical considerations: respecting individual identity and dignity versus preventing catastrophic loss of life.
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.
Gemini 2.5 Pro Experimental: Of course. This is a fascinating and ambitious pitch. While the vision is compelling, several claims would likely face intense scrutiny from sophisticated investors. Here are the 3 weakest claims, why they're weak, and how to strengthen them.
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…
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| Spec | ||
|---|---|---|
| Input price | $1/M tokens | $0.68/M tokens |
| Output price | $2/M tokens | $2.09/M tokens |
| Context window | 1.0M tokens | 524K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Mar 2025 | Oct 2026 |
| At 10M a month | $10.00 | $6.80 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
Gemini 2.5 Pro Experimental is developed by Google AI while Mistral Large 4 is developed by Mistral AI. Gemini 2.5 Pro Experimental has a 1.0M token context window vs Mistral Large 4's 524K. You can compare their actual outputs across 42 challenges on Rival to see how they differ in practice.
It depends on your use case. Gemini 2.5 Pro Experimental and Mistral Large 4 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 42 challenges so you can judge which fits your needs best.
Gemini 2.5 Pro Experimental costs $1/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Mistral Large 4 is $0.32/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 Gemini 2.5 Pro Experimental 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.