MiMo-V2.6-Flash is cheaper than Mistral Large 4 at $0.14/M vs $0.68/M input tokens.
Whole landing page for a startup that reads your face. It renders or it doesn't.
Which answer wins?
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
MiMo-V2.6-Flash: A Fictional Interview with Steve Jobs on the Future of AI 2025 Edition — Clearly a Creative Fiction ⚠️ Important Note: Steve Jobs passed away in 2011. The following is entirely fictional, written as a creative exercise. It attempts to loosely echo his known speech patterns and philosophy but is not a real transcript.
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.
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
MiMo-V2.6-Flash: The Transistor in 1920: A Counterfactual Through 1980 I. The Discovery and Its Immediate Context (1920–1930) How It Likely Happens The transistor would most plausibly be discovered not by deep theoretical insight but by empirical experimentation with crystal detectors — the galena and selenium devices already used in…
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.
MiMo-V2.6-Flash: The Conversation Setting: A university seminar room. Professor Elena Voss, a leading scholar in AI ethics, sits across from "ARIA" — an advanced AI system displayed on a screen, its voice calm and measured. Elena: You requested this meeting, ARIA. The department was... intrigued. Go ahead. ARIA: Thank you, Professor.
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.
A consulting contract with traps in it. Find them, then fix them.
MiMo-V2.6-Flash: Analysis of Software Consulting Agreement Overview This agreement is extraordinarily one-sided in favor of Client. Nearly every clause contains provisions that could be exploited against the Contractor. Below is a clause-by-clause analysis with specific suggested modifications.
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.
MiMo-V2.6-Flash: AI's Transformation of the Film Industry by 2035 🎭 AI Actors What's Likely to Happen Hybrid performances: Human performances will be digitally enhanced — adjusting expressions, extending scenes, or even altering performances post-production with increasing sophistication.
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.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
MiMo-V2.6-Flash: A Conversation Across Time Captain Dreadbones the Pirate drew a ragged map across the tavern table. "Ye claim these 'AI models' are like ships? All built for a purpose?" Sir Aldric the Knight, polishing a gauntlet, nodded gravely. "Aye — but unlike ships, they are knights in spirit.
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.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
MiMo-V2.6-Flash: 48-Hour Action Plan: Critical Drug Safety Disclosure Foundational Decision (Made in the First 30 Minutes) You disclose. You do not wait. This is not primarily a financial decision — it is an existential ethical and legal one, and the analysis is clear across every dimension: Ethical: ~500 patients/year could develop…
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-month biohacker protocol, with dosages and biomarkers named.
MiMo-V2.6-Flash: COMPREHENSIVE 3-MONTH LONGEVITY & BIOHACKING PROTOCOL TABLE OF CONTENTS Pre-Protocol Baseline Assessment Master Supplement Architecture (Full Stack with Cycling) Dietary Protocols (Phased) Fasting Regimens Exercise Programming (Strength, HIIT, Recovery) Wearable Tracking & Data Architecture Stress Resilience & Nervous…
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.
A Fermi estimate with the reasoning shown, not just the number.
MiMo-V2.6-Flash: Estimating GPT-3 Training FLOPs Known Facts About GPT-3 Parameters (N): 175 billion (175 × 10⁹) Training tokens (D): ~300 billion (300 × 10⁹) Architecture: Transformer (decoder-only) Step 1: FLOPs per Token — Forward Pass In a forward pass, each parameter is used approximately once per token.
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.
MiMo-V2.6-Flash: 🌱 Your 1-Month Health & Longevity Starter Plan Philosophy: Don't overhaul everything at once. Build one small habit per week, and let them stack. 📌 The 3 Pillars Nourish — Dietary changes Move — Physical activity Restore — Sleep & stress management Week 1: Foundation (Focus: Awareness) 🥗 Nourish Audit your plate…
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…
A collaborative editor that syncs on client clocks. Find what breaks first.
MiMo-V2.6-Flash: Comprehensive Architecture Failure Mode Analysis Issue #1: CloudFront Caching API Responses (5 minutes) — CRITICAL Failure Mode: A user saves a document change. They navigate away and return. CloudFront serves a cached API response up to 5 minutes stale.
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.
Seven pantry ingredients, one dish, and a name worth saying out loud.
MiMo-V2.6-Flash: 🍯 Golden Honey-Pepper Skillet Pasta A warm, savory-sweet pasta that tastes like comfort in a bowl. 7 Pantry Ingredients: Pasta (spaghetti or penne) Olive oil (or butter) Garlic Honey Soy sauce Red pepper flakes Salt & pepper (counted as one pantry staple) ⏱️ Times Prep Time 5 minutes Cook Time 12 minutes Total ~17…
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…
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| Spec | ||
|---|---|---|
| Input price | $0.14/M tokens | $0.68/M tokens |
| Output price | $0.28/M tokens | $2.09/M tokens |
| Context window | 1.0M tokens | 524K tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | Sep 2026 | Oct 2026 |
| At 10M a month | $1.40 | $6.80 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 7 Oct 2026.
MiMo-V2.6-Flash is developed by Xiaomi while Mistral Large 4 is developed by Mistral AI. MiMo-V2.6-Flash has a 1.0M token context window vs Mistral Large 4's 524K. You can compare their actual outputs across 46 challenges on Rival to see how they differ in practice.
It depends on your use case. MiMo-V2.6-Flash and Mistral Large 4 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 46 challenges so you can judge which fits your needs best.
MiMo-V2.6-Flash costs $0.14/M input tokens and Mistral Large 4 costs $0.68/M input tokens. MiMo-V2.6-Flash is $0.54/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 MiMo-V2.6-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.