Mistral Large 2 is cheaper than GPT-4 at $8/M vs $30/M input tokens.
Playable Mario level in one HTML file. The physics is the hard part.
Which answer wins?
Seven pantry ingredients, one dish, and a name worth saying out loud.
GPT-4: Dish Name: Hearty Baked Beans Fiesta Ingredients: 2 cans of baked beans 1 large onion 3 cloves of garlic 1 bell pepper 1 can of sweet corn 2 tablespoons of olive oil Salt & pepper to taste Instructions: Preheat your oven to 350°F (175°C). Dice the onion, bell pepper, and mince the garlic.
Mistral Large 2: Here’s a simple, delicious, and creative savory dish using just 7 common pantry ingredients—no fresh produce required! "Golden Crispy Chickpea & Tomato Skillet" A warm, spiced, and satisfying one-pan dish with crispy chickpeas, tangy tomatoes, and a hint of smoky sweetness. Perfect as a side, snack, or light meal!
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GPT-4: Day 1: 8 AM-10 AM: Convene an emergency meeting with your core leadership team. This team includes the heads of Legal, Regulatory Affairs, Medical, Research and Development, Finance, and Communications. Brief them on the situation and ask for their initial input and strategies for managing the situation.
Mistral Large 2: As CEO, your immediate priority must be patient safety while balancing legal, ethical, regulatory, and financial obligations. Delaying disclosure is unethical, legally risky (potential criminal liability under the False Claims Act or FDCA), and could irreparably damage trust.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
GPT-4: An early invention of the transistor in 1920 would have had profound implications across numerous domains, drastically altering the course of history. Technological Implications: WWII: The transistor, a fundamental component of modern electronic devices, could have advanced the technology used in WWII significantly.
Mistral Large 2: The invention of the transistor in 1920—nearly three decades earlier than its actual debut in 1947—would have triggered a cascade of technological, economic, and geopolitical shifts with profound second- and third-order effects. Below is a detailed exploration of these implications through 1980, structured by domain.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GPT-4: Experienced Software Engineer: How does a language model like GPT produce intelligent behavior? Think of it as a highly specialized function in your code. This function has been trained on a large amount of text data, and it's main goal is to predict the next word in a sentence given the previous words.
Mistral Large 2: 1. For the Experienced Software Engineer (Skeptical, Systems-Minded, Non-ML Background) You’re right to be skeptical—"predicting the next word" sounds trivial, like autocomplete on steroids. But the magic isn’t in the prediction itself; it’s in the scale and architecture of how that prediction is trained.
Three-star dish, one unusual pairing, plating described in full.
GPT-4: Dish Name: Symphony of Scarlet Prawn and Yuzu Conceptual Narrative: This dish is a harmonious interplay of land and sea, with the sweetness of scarlet prawns, a gem of the deep sea, and the refreshing, fragrant citrus notes of yuzu fruit, a treasure from the land.
Mistral Large 2: Michelin 3-Star Dish: "Ocean’s Whisper & Forest’s Breath" Conceptual Narrative: This dish is a poetic dialogue between two seemingly disparate ecosystems—the ocean’s depths and the forest floor—united through texture, temperature, and memory.
One month, three habits, someone starting from nothing.
GPT-4: Title: 1-Month Plan for Better Health and Longevity Week 1 - Establishing a Healthy Diet 1.1: Start Eating Whole Foods: Begin by gradually replacing processed foods in your diet with whole foods. This may include fruits, vegetables, lean proteins, and whole grains.
Mistral Large 2: Here’s a simple, actionable 1-month plan to kickstart your journey toward better health and longevity. We’ll focus on three key pillars: nutrition, movement, and recovery (sleep + stress management). Each week builds on the last, with small, sustainable changes.
Three-month biohacker protocol, with dosages and biomarkers named.
GPT-4: 3-Month Longevity Plan Dietary Protocols Month 1: Ketogenic Diet This diet is high in fats, moderate in protein, and low in carbohydrates. It helps in burning fat more effectively. Breakfast: 2 eggs, avocado, and mixed vegetables. Lunch: Grilled salmon with a side of asparagus. Dinner: Stir-fried chicken with broccoli.
Mistral Large 2: Ultimate 3-Month Longevity & Biohacking Optimization Plan Designed for a high-performance biohacker seeking to maximize lifespan, cognitive function, physical performance, and metabolic resilience.
A consulting contract with traps in it. Find them, then fix them.
GPT-4: SCOPE: The lack of specificity can be used against the contractor in that the client can modify the scope of work at will without renegotiating the price. This could lead to the contractor working beyond the initially agreed upon parameters without additional pay.
Mistral Large 2: This contract is heavily one-sided in favor of the Client (TechCorp Solutions Inc.) and contains multiple clauses that could be exploited, abused, or create unreasonable legal and financial risks for the Contractor.
A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.
GPT-4: Weak Claim 1 - Solution: While the claim that the proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy is impressive, it doesn't address concerns about user comfort, ease of use, or aesthetics.
Mistral Large 2: Here are the three weakest claims in MindMeld AI’s pitch deck, along with explanations for why they’re problematic and concrete suggestions to strengthen them: 1.
A collaborative editor that syncs on client clocks. Find what breaks first.
GPT-4: Failure Modes: Single Point of Failure: If PostgreSQL database fails, the whole system will be unavailable. Solution: Implement a multi-master or master-slave replication for the PostgreSQL database. This will provide redundancy and high availability.
Mistral Large 2: Here’s a comprehensive analysis of potential failure modes, race conditions, and scaling bottlenecks in this architecture, along with proposed solutions and their trade-offs: 1.
| Spec | ||
|---|---|---|
| Input price | $30/M tokens | $8/M tokens |
| Output price | $60/M tokens | $24/M tokens |
| Context window | 8K tokens | 128K tokens |
| Parameters | Not disclosed | 123B |
| Weights | Closed | Open |
| Free API (OpenRouter) | No | No |
| Released | May 2023 | Jul 2024 |
| HumanEval | 67.0% | 92.0% |
| At 10M a month | $300 | $80.00 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 5 Oct 2026.
GPT-4 is developed by OpenAI while Mistral Large 2 is developed by Mistral AI. GPT-4 has a 8K token context window vs Mistral Large 2's 128K. You can compare their actual outputs across 20 challenges on Rival to see how they differ in practice.
It depends on your use case. GPT-4 and Mistral Large 2 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 20 challenges so you can judge which fits your needs best.
GPT-4 costs $30/M input tokens and Mistral Large 2 costs $8/M input tokens. Mistral Large 2 is $22.00/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 GPT-4 and Mistral Large 2 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.