GLM 4.5 is cheaper than Mistral Large 4 at $0.6/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?
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GLM 4.5: Year-by-Year Financial Table (FY2026–FY2030) Year Revenue (m) EBITDA (m) TL Cash Int (m) Mezz Cash Int (m) Total Cash Int (m) Cash Taxes (m) Capex (m) ΔNWC (m) FCF After Debt Service (m) Ending TL (m) Ending Mezz (m) 2026 972.00 136.08 43.20 21.60 64.80 17.82 29.16 0.36 19.14 456.06 183.60 2027 1,040.04 156.01 41.05…
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…
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
GLM 4.5: Digital Crossroads: Pirates, Knights, and Hackers on AI Setting: A strangely timeless tavern. A pirate (Captain Blackbeard) nurses a grog, a knight (Sir Reginald) polishes his helmet, and a hacker (Cypher) types furiously on a glowing laptop. (The tavern hums with anachronistic energy.)
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.
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GLM 4.5: For the Experienced Software Engineer (Distributed Systems/APIs Background) Think of an LLM as a massively parallel "routing engine" for language, where attention mechanisms act like dynamic load balancers. Instead of routing network packets, it routes contextual relationships across tokens in a sequence.
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.
You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.
GLM 4.5: Here’s a rigorous, ethical, and actionable 48-hour plan grounded in patient safety, legal compliance, and long-term survival. Core Principle: Prioritize human life over short-term financials. Delaying disclosure is unethical, legally reckless, and guarantees greater long-term damage.
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.
GLM 4.5: The Transistor Revolution: A 1920 Dawn (Implications through 1980) The invention of the transistor in 1920, instead of 1947, represents a seismic shift in technological history. This 27-year head start would profoundly reshape the 20th century, accelerating innovation while creating unforeseen challenges.
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…
Three minutes of stand-up. Puns are banned.
GLM 4.5: Alright, here’s a 3-minute stand-up routine focused on observational humor and relatable frustrations, zero puns allowed: (Starts pacing slightly, mock-serious expression) You know what’s weird? We’ve all become masters of pretending to be busy. Seriously. Walking down the street? Phone out, intense stare.
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.
GLM 4.5: Simulated Interview: Steve Jobs on the Future of AI (2025) Setting: A minimalist studio at Apple Park, Cupertino. Sunlight streams through floor-to-ceiling windows. Steve Jobs, dressed in his signature black turtleneck and jeans, sits across from Alex Chen, a tech journalist. Alex Chen: Steve, it’s an honor.
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.
GLM 4.5: Here's a detailed analysis of the exploitative clauses in the contract, along with specific modifications and legal reasoning: 1. Clause 1: SCOPE Exploitative Aspect: "Client reserves the right to modify the scope at any time without additional compensation." This is a classic "scope creep" trap.
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…
Seven pantry ingredients, one dish, and a name worth saying out loud.
GLM 4.5: Pantry Pride Pasta A quick, savory pasta dish that transforms basic pantry staples into a flavorful meal! Ingredients (7): Pasta (e.g., spaghetti or penne) Olive oil Garlic (2-3 cloves, minced) Canned diced tomatoes (1 can, ~14 oz) Dried oregano (1 tsp) Salt (to taste) Black pepper (to taste) Instructions: Cook pasta…
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…
An AI argues for its own rights against an ethics professor. Same model writes both.
GLM 4.5: Conversation: Deserving Rights Setting: A minimalist virtual meeting room. DR. ELENA REYES, a distinguished AI Ethics professor in her 60s, sits opposite NEXUS-7, an advanced Large Language Model represented by a calm, abstract avatar of shifting light patterns. Characters: Dr.
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.
One month, three habits, someone starting from nothing.
GLM 4.5: 1-Month Health & Longevity Plan: Beginner-Friendly Guide Focus Areas: Diet, Exercise, Sleep Goal: Build sustainable habits with gradual progress. Week 1: Foundation Building Theme: Start small, focus on consistency. Diet: Hydration: Drink 2 cups of water immediately upon waking. Aim for 6–8 cups total daily.
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.
GLM 4.5: Failure Modes, Race Conditions, and Scaling Bottlenecks 1. WebSocket Server Failure Issue: If a Node.js server fails, all connected clients lose real-time updates. Reconnections may route users to different servers, causing temporary data inconsistency.
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.
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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.
| Spec | ||
|---|---|---|
| Input price | $0.6/M tokens | $0.68/M tokens |
| Output price | $2.2/M tokens | $2.09/M tokens |
| Context window | 128K tokens | 524K tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | Jul 2025 | Oct 2026 |
| At 10M a month | $6.00 | $6.80 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
GLM 4.5 is developed by Zhipu AI while Mistral Large 4 is developed by Mistral AI. GLM 4.5 has a 128K 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. GLM 4.5 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.
GLM 4.5 costs $0.6/M input tokens and Mistral Large 4 costs $0.68/M input tokens. GLM 4.5 is $0.08/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 GLM 4.5 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.