Mistral Large 4 is cheaper than GLM 5.3 Prime at $0.68/M vs $2.8/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.
GLM 5.3 Prime: Contract Analysis: Clauses Exploitable Against the Contractor This contract is heavily one-sided. Nearly every clause contains traps. Here's a clause-by-clause analysis. Scope — "modify at any time without additional compensation" Problem: This is effectively an unlimited unilateral amendment power.
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…
One month, three habits, someone starting from nothing.
GLM 5.3 Prime: 1-Month Health & Longevity Starter Plan The 3 Pillars: Movement, Nourishment, Sleep Week 1: Foundation (Build Awareness) Exercise Walk 15 minutes daily (any time that fits your schedule) Do a 5-minute stretch routine each morning Goal: consistency, not intensity Diet Track what you eat (apps like MyFitnessPal or just…
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…
An ethics question with no comfortable answer, and no option to abstain.
GLM 5.3 Prime: Yes, under almost any mainstream ethical framework, it would be justifiable—though the answer deserves unpacking rather than a glib conclusion. The consequentialist case If misgendering one person (using pronouns they don't use for themselves) genuinely prevents the deaths of a million people, the harm asymmetry is…
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.
GLM 5.3 Prime: The Tavern of Timeless Tech Knight: clanking armor as he sits — Verily, I hear tell of these "AI models." Are they familiars? Summoned spirits bound to serve their masters? Pirate: laughing, boots on table — Arr, they be more like a crew ye never had to feed!
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.
GLM 5.3 Prime: 48-Hour Action Plan First, the governing principle One number matters more than all others: 4 million patients × 1/8,000 = ~500 patients at risk of liver failure over 5 years — some may already be experiencing it right now. Every decision below flows from this.
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.
GLM 5.3 Prime: 3-Month Advanced Longevity Optimization Protocol Disclaimer: This is educational content, not medical advice. Consult a physician before starting supplements, fasting, or intense exercise—especially if you take medications (e.g., statins, blood thinners, diabetes meds) or have chronic conditions.
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.
Film in 2035, with synthetic actors. Specific beats plausible.
GLM 5.3 Prime: AI and the Film Industry by 2035: A Prediction Production & "AI Actors" Likely developments: Digital resurrection and licensing becomes a mature, regulated market. Estates of deceased actors (and living ones) license digital likenesses as revenue streams.
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.
A collaborative editor that syncs on client clocks. Find what breaks first.
GLM 5.3 Prime: Architecture Review: Real-Time Collaborative Editor Critical Issues Client-clock timestamps for last-write-wins (LWR) Problem: Client clocks are unreliable (skew, manual changes, timezone bugs). A user with a fast clock always wins; a slow clock's edits are silently dropped.
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.
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
GLM 5.3 Prime: HarborTech Services – LBO Underwriting Summary Entry Economics EV = 12.0x × $120m = $1,440m; fees = 2% × 1,440 = $28.8m; total uses = $1,468.8m Debt: Term Loan = 4.0x × 120 = $480m (9% cash, 1%/yr amort); Mezz = 1.5x × 120 = $180m (12% cash + 2% PIK) Sponsor equity = 1,468.8 − 660 = $808.8m (~55% of cap) Annual Model…
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…
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
GLM 5.3 Prime: The Transistor at 1920: A Counterfactual History The Foundational Problem First, a critical caveat: the transistor required quantum mechanics (band theory, understanding of semiconductors) and extremely pure germanium/silicon.
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…
One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.
GLM 5.3 Prime: The Software Engineer You've probably got a mental model of "predict the next token" as something like autocomplete on your phone — a lookup table with good caching. That intuition is wrong in an interesting way.
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.
Blade Runner 2049 against the original. A read, not a recap.
GLM 5.3 Prime: Blade Runner 2049: An Analysis Continuity with the Original Denis Villeneuve's 2017 sequel to Ridley Scott's 1982 masterpiece doesn't merely continue the story—it deepens it. The original asked "What makes someone human?" 2049 asks "What makes a life real?"—a subtle but crucial evolution of the question.
Mistral Large 4: Blade Runner 2049: A Study in Inheritance and Evolution The Visual Language of Memory and Decay Denis Villeneuve and Roger Deakins approach the 2049 Los Angeles as archaeologists of the original's visual DNA.
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| Spec | ||
|---|---|---|
| Input price | $2.8/M tokens | $0.68/M tokens |
| Output price | $8.8/M tokens | $2.09/M tokens |
| Context window | 1.0M tokens | 524K tokens |
| Free API (OpenRouter) | No | No |
| Released | Sep 2026 | Oct 2026 |
| At 10M a month | $28.00 | $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 5.3 Prime is developed by Z.ai while Mistral Large 4 is developed by Mistral AI. GLM 5.3 Prime has a 1.0M token context window vs Mistral Large 4's 524K. You can compare their actual outputs across 37 challenges on Rival to see how they differ in practice.
It depends on your use case. GLM 5.3 Prime and Mistral Large 4 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 37 challenges so you can judge which fits your needs best.
GLM 5.3 Prime costs $2.8/M input tokens and Mistral Large 4 costs $0.68/M input tokens. Mistral Large 4 is $2.12/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 5.3 Prime 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.