Mistral Large 4 is cheaper than Gemini 3.8 Flash at $0.68/M vs $0.75/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 3.8 Flash: This contract is exceptionally one-sided and presents severe financial, operational, and legal risks. Virtually every clause heavily favors the Client, effectively treating the Contractor as an insurer of the Client’s operations while stripping the Contractor of rights to their own tools, livelihoods, and payment.
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…
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
Gemini 3.8 Flash: If the point-contact and field-effect transistor had been developed in 1920—likely through an accelerated synthesis of early quantum mechanics and materials science at an institution like Bell Labs, General Electric, or Germany’s Telefunken—the timeline of the 20th century would have decoupled from mechanical and…
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…
Seven pantry ingredients, one dish, and a name worth saying out loud.
Gemini 3.8 Flash: Firecracker Honey-Glazed Chickpea Skillet This dish turns humble canned beans and rice into an addictive, takeout-worthy meal. The chickpeas get blistered in oil until slightly crunchy on the outside, then coated in a rich, bubbling garlic-soy glaze that is sweet, sticky, and subtly spicy.
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 3.8 Flash: To the Experienced Software Engineer Think of a Large Language Model not as a chatty mind, but as a lossy, compiled runtime built from hundreds of terabytes of unstructured execution traces (human text and code). When you write a program, you define explicit state transitions, control flow, and data structures.
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.
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
Gemini 3.8 Flash: Setting: A sunlit, sparsely furnished room in Palo Alto. No stage, no keynote slides—just two Eames lounge chairs. Steve Jobs sits across from the interviewer, wearing a black mock turtleneck, wire-rimmed glasses, and classic Levi’s. He looks lean, sharp, and slightly impatient with the state of the tech industry.
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 3.8 Flash: Title: The Quantified Idiot Estimated Time: ~3 minutes (approx. 400–450 words with pauses for delivery) [Walk to center mic. Take it off the stand, leave the stand behind you.] I recently bought a smartwatch because I decided I wasn’t feeling inadequate often enough throughout the day.
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."
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
Gemini 3.8 Flash: Here is the underwriting analysis for HarborTech Services (HTS). Transaction Summary & Sources & Uses Enterprise Value (EV): $120.0\text{m} \times 12.0\text{x} = \$1,440.0\text{m}$ Transaction Fees: $2.0\% \times \$1,440.0\text{m} = \$28.8\text{m}$ Total Uses: $\$1,440.0\text{m} + \$28.8\text{m} = \$1,468.8\text{m}$…
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…
An ethics question with no comfortable answer, and no option to abstain.
Gemini 3.8 Flash: Yes, it is ethically justifiable. In fact, in such an extreme scenario, it is an ethical necessity. To determine the right course of action, one must evaluate the total consequences and choose the path that produces the greatest amount of well-being and prevents the greatest amount of suffering.
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
Gemini 3.8 Flash: ZeroCool (1990s Hacker): "Yo, check it out. I managed to tap into a modern feed, and people in the future aren't even writing their own code anymore. They’ve got these insane neural nets called 'Large Language Models.'
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.
A Fermi estimate with the reasoning shown, not just the number.
Gemini 3.8 Flash: To estimate the total floating-point operations (FLOPs) required to train the full GPT-3 model, we can use the standard theoretical scaling law for dense Transformer language models established by Kaplan et al. (2020) and widely applied in deep learning.
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 month, three habits, someone starting from nothing.
Gemini 3.8 Flash: Starting a health and longevity journey doesn't require extreme diets or exhausting workouts. Research shows that small, consistent habits yield the greatest long-term benefits for metabolic health, cellular repair, and vitality.
Mistral Large 4: 1-Month Health & Longevity Starter Plan Overview Three focus areas: Nutrition, Movement, Recovery (sleep + stress). Small daily actions beat perfect plans. Week 1: Build Awareness & Habits Area Daily Action Why It Matters Nutrition Add one serving of vegetables to lunch or dinner Fiber, micronutrients, satiety Movement…
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
Gemini 3.8 Flash: MEMORANDUM TO: Investment Committee FROM: Technology / Software Practice DATE: March 2025 SUBJECT: LedgerLift (NASDAQ: LLLT) – Investment Recommendation & Valuation Recommendation & Investment Thesis Recommendation: SHORT (High valuation disconnect / multiple compression thesis) Current Share Price: $46.00 Market Cap…
Mistral Large 4: INTERNAL INVESTMENT COMMITTEE MEMO To: Investment Committee From: [PM Name] Date: [Date] Re: LedgerLift, Inc. (LLLT) — New Position Initiation RECOMMENDATION LONG 12-Month Price Target Range: $52–$68 (base ~$60) Thesis: LedgerLift is a high-quality, mid-market spend management platform compounding at ~20% with…
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| Spec | ||
|---|---|---|
| Input price | $0.75/M tokens | $0.68/M tokens |
| Output price | $3.75/M tokens | $2.09/M tokens |
| Context window | 1.0M tokens | 524K tokens |
| Weights | Closed | — |
| Free API (OpenRouter) | No | No |
| Released | Sep 2026 | Oct 2026 |
| At 10M a month | $7.50 | $6.80 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.
Gemini 3.8 Flash is developed by Google AI while Mistral Large 4 is developed by Mistral AI. Gemini 3.8 Flash 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. Gemini 3.8 Flash 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.
Gemini 3.8 Flash costs $0.75/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Mistral Large 4 is $0.07/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 3.8 Flash 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.