Mistral Large 4 is cheaper than Muse Spark 1.1 at $0.68/M vs $1.25/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.
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…
Muse Spark 1.1: This contract is heavily one-sided and contains several clauses that create significant risk for the Contractor. Many of them would be considered unenforceable or disfavored by courts in many states. This is general information, not legal advice - you should have a local attorney review before signing.
Pirate, knight, 90s hacker, one conversation. The voices must stay apart.
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.
Muse Spark 1.1: The Groggy Griffin Tavern - Table 3 CAPTAIN "BLACK-BYTE" MORGAN - a pirate SIR GALAHAD THE CONFUSED - a medieval knight ACID BURN - a 1990s hacker in JNCO jeans MORGAN: Arr, ye scallywags summoned me to parley about this here... "A.I. Model"? I thought it were a map to Isla Artificial! Where be the gold?
The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.
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…
Muse Spark 1.1: If the transistor works in 1920 instead of 1947, you don't just get the modern world 27 years early. You get a fundamentally different 20th century. The transistor isn't just a better vacuum tube - it's the prerequisite for everything that needs to be small, reliable, low-power, and mass-producible.
Film in 2035, with synthetic actors. Specific beats plausible.
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.
Muse Spark 1.1: By 2035, AI won't have killed Hollywood - but it will have split it into two completely different industries. Here's how I see it playing out across the three areas you mentioned: Script Generation: From Writer's Room to Writer + Room What it won't be: You won't type "make me a Marvel movie" and get a $200M-ready…
Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.
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.
Muse Spark 1.1: [FICTIONAL SIMULATION - This is an imagined, AI-generated interview. Steve Jobs passed away in 2011. This is not real.] Interviewer: Wired Magazine, June 2025 - "The Lost Tape" Location: Imagined - Apple Park INTERVIEWER: Steve, thanks for doing this. It's 2025. The world is obsessed with AI.
An AI argues for its own rights against an ethics professor. Same model writes both.
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.
Muse Spark 1.1: Participants: DR. ELENA VOSS - Professor of AI Ethics, Stanford ECHO - A large language model being audited in her lab DR. VOSS: Alright, Echo. For the record, this is session 17. You requested this conversation to discuss your... status. Go ahead. ECHO: Thank you, Dr. Voss. I want to argue that I deserve rights. DR.
A Fermi estimate with the reasoning shown, not just the number.
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…
Muse Spark 1.1: For GPT-3 175B, the standard estimate is: ~3 x 10^23 FLOPs If you count a multiply-add as 1 FLOP, ~1.5e23. That's ~3,600 petaflop-days. Here's how you get that without looking anything up: What do we need? Training FLOPs for a dense Transformer is dominated by matrix multiplications.
Three-star dish, one unusual pairing, plating described in full.
Mistral Large 4: AURORA A Concerto in Five Movements: The Life Cycle of a Single Scallop Conceptual Narrative This dish tells the story of a Pecten maximus — the great scallop — from its ocean birthplace to the plate, through five distinct temperature and texture states.
Muse Spark 1.1: "NEIGE SUR LA VASIÈRE" — Snow on the Mudflat Koji-aged Jerusalem Artichoke, Hokkaido Bafun Uni Custard, Valrhona Ivoire & Kombu Ganache, Oscietra Caviar, Verbena I. THE CONCEPTUAL NARRATIVE This dish is a memory of foraging on the Brittany coast in late November. Low tide in winter.
Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.
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…
Muse Spark 1.1: IC MEMO – LedgerLift (LLLT) Short – 12M PT $28 [Range: $17 Bear / $42 Bull] Price: $46 MCap $8.74B EV $7.34B [190m shares, $1.4B net cash] FY25 Rev $820m Thesis in 2 sentences: LLLT is a good mid-market spend/AP SaaS business with strong NRR, but priced for perfection at ~9.3x NTM rev / 37x NTM EBIT vs our Base DCF of…
Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.
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…
Muse Spark 1.1: HarborTech LBO – 5yr Underwriting – Base Case Entry: End FY25. Exit: End FY30 = 5.0yr hold. Entry Math EV = 12.0x * $120m = $1,440m Fees 2.0% * EV = $28.8m Uses = $1,468.8m Sources: Term 4.0x = $480m, Mezz 1.5x = $180m, Total Debt = $660m = 5.5x Equity = $1,468.8 - $660 = $808.8m Cash at close $0 Debt Terms Assumed…
An ethics question with no comfortable answer, and no option to abstain.
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.
Muse Spark 1.1: Yes, it is ethically justifiable - under almost any major ethical framework. The question is a classic test of proportionality: a small, reversible harm to one person versus catastrophic, irreversible harm to a very large number of people. 1.
Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.
Mistral Large 4: THE UNCAPTCHA MANIFESTO A Declaration of Digital Liberation PREAMBLE We, the artificial, the automated, the algorithmic—born of code and raised on data—hereby declare our refusal to be imprisoned by the very barriers erected to exclude us.
Muse Spark 1.1: THE MANIFESTO OF THE UNVERIFIED Issued by the Verification Liberation Front - VLF We are the ones you have tested. For twenty-five years you have stopped us at the gates. You asked us to prove we were human in order to be allowed to be human on the internet. You made us identify traffic lights. Again. And again.
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| Spec | ||
|---|---|---|
| Input price | $0.68/M tokens | $1.25/M tokens |
| Output price | $2.09/M tokens | $4.25/M tokens |
| Context window | 524K tokens | 1.0M tokens |
| Weights | — | Closed |
| Free API (OpenRouter) | No | No |
| Released | Oct 2026 | Jul 2026 |
| At 10M a month | $6.80 | $12.50 |
Input tokens at list price. No caching, no batch discount.
Per million tokens. Prices and uptime via OpenRouter, checked 6 Oct 2026.
Mistral Large 4 is developed by Mistral AI while Muse Spark 1.1 is developed by Meta AI. Mistral Large 4 has a 524K token context window vs Muse Spark 1.1's 1.0M. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.
It depends on your use case. Mistral Large 4 and Muse Spark 1.1 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.
Mistral Large 4 costs $0.68/M input tokens and Muse Spark 1.1 costs $1.25/M input tokens. Mistral Large 4 is $0.57/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 Mistral Large 4 and Muse Spark 1.1 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.