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  1. Home/
  2. Compare/
  3. GPT-5.4 Pro vs Mistral Large
Updated Mar 2026

GPT-5.4 Pro vs Mistral Large

Mistral Large is cheaper than GPT-5.4 Pro at $8/M vs $30/M input tokens.

Mario Level UI Recreation

Playable Mario level in one HTML file. The physics is the hard part.

Loading the build
GPT-5.4 Pro
Loading the build
Mistral Large

Which answer wins?

Written rounds

12 prompts
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-5.4 Pro: Below is a simplified LBO build for HarborTech Services (HTS). All figures in $m unless noted. Rounding: tables are rounded; IRR/MOIC use unrounded math. Entry / Sources & Uses FY2025 EBITDA: 120.0 Purchase price: 12.0x EBITDA → Enterprise value = 12.0 × 120.0 = 1,440.0 Transaction fees: 2.0% of EV → 28.8 Total uses =…

    Mistral Large: 1) Year-by-Year Table (FY2026–FY2030) (All figures in $ millions, rounded to nearest $1m) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972 1,040 1,102 1,157 1,215 EBITDA 136 156 176 191 207 Cash Interest (Term Loan) 43 40 37 34 31 Cash Interest (Mezz) 16 17 18 20 22 Total Cash Interest 59 57 55 54 53 Cash Taxes 19…

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-5.4 Pro: Most likely, a transistor invented in 1920 would move the electronics/computing frontier forward by about 10–15 years by 1980, not the full 27 years. Reason: the transistor alone is not enough; you also need high-purity materials, crystal growth, photolithography, test equipment, software, batteries, precision…

    Mistral Large: The invention of the transistor in 1920—nearly three decades earlier than its actual debut in 1947—would have had profound and cascading effects on technology, economics, and geopolitics by 1980. Below is a detailed breakdown of the first-, second-, and third-order implications, organized by domain. 1.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-5.4 Pro: LedgerLift (LLLT) — IC Memo Recommendation: Pass 12-month PT range: $40–$47 2-sentence thesis: LedgerLift looks like a good business but only an average stock here: retention is strong (94% GRR, 123% NRR), the model is mostly subscription, and margins are inflecting, but at $46 the shares already discount a lot of the…

    Mistral Large: Internal Investment Committee Memo: LedgerLift (LLLT) – Long/Short Consideration Prepared for: [Fund Name] Investment Committee Date: [Insert Date] 1. Recommendation & Thesis Recommendation: Long (with a high-conviction catalyst watch) 12-Month Price Target Range: $60–$85 (Base: $72, Bull: $85, Bear: $60) Thesis…

    Every model's answer to this prompt
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GPT-5.4 Pro: Dragon Pantry Peanut Noodles A fast, sweet-savory noodle dish made from 7 pantry staples. Ingredients 8 oz spaghetti 1/3 cup peanut butter 3 tbsp soy sauce 1 tbsp honey 1 tbsp vegetable oil 1 tsp garlic powder 1/4 tsp red pepper flakes Water for boiling/thinning the sauce doesn’t count.

    Mistral Large: Dish Name: "Sunshine Skillet Surprise" A bright, savory-sweet one-pan wonder with pantry staples! Ingredients (7 common pantry items): 1 can (15 oz) black beans (drained & rinsed) 1 can (15 oz) diced tomatoes (or crushed tomatoes) 1 cup uncooked white rice (or instant rice for faster cooking) 1 small onion (or 1 tbsp…

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-5.4 Pro: The 3 weakest claims are the ones that are both most extraordinary and least well-supported. Weak claim Why it’s weak How to strengthen it 1) “MindMeld AI reads your brainwaves to predict what you want to type before you think it.” This is the biggest credibility risk in the deck.

    Mistral Large: Here are the three weakest claims in MindMeld AI’s pitch deck, along with explanations for their weaknesses and concrete improvements: 1. Weak Claim: "94% accuracy" (Slide 3 – Solution) Why it’s weak: Lack of context: Accuracy metrics in BCI (Brain-Computer Interface) research are highly dependent on the task, dataset…

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GPT-5.4 Pro: I do not wait. A credible, previously unlabeled risk of liver failure in a chronic-pain drug is a patient-safety crisis, a regulatory crisis, and a securities-disclosure issue at the same time.

    Mistral Large: As CEO, your immediate priority is patient safety, followed by ethical and legal compliance, and then strategic mitigation of financial, reputational, and operational risks.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.4 Pro: Below is a 12-week, high-performance longevity protocol designed for a healthy biohacker who wants to improve lifespan-relevant markers, physical performance, and cognitive output at the same time. Use it as a data-driven template, not dogma.

    Mistral Large: 3-Month Advanced Longevity & Performance Biohacking Plan Optimized for Cellular Rejuvenation, Cognitive Enhancement, Physical Resilience, and Stress Adaptation This 3-month protocol integrates cutting-edge biohacking strategies across nutrition, supplementation, exercise, recovery, cognitive enhancement, and stress…

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-5.4 Pro: Below is a dish designed in the language of a contemporary 3-star tasting menu: precise, seasonal, technically layered, and centered on a pairing that feels surprising at first, then inevitable.

    Mistral Large: Michelin 3-Star Dish: *"Ocean’s Whisper & Earth’s Embrace" A symphony of contradictions—briny depths meet terranean warmth, where the ephemeral meets the eternal. Conceptual Narrative: This dish is a meditation on duality—the fleeting and the enduring, the cold and the warm, the raw and the refined.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GPT-5.4 Pro: This architecture will work for a demo, but it has major correctness, latency, and security problems for a Google-Docs-like editor. Highest-risk flaws Client-clock last-write-wins will lose edits and can be gamed by bad clocks.

    Mistral Large: Here’s a comprehensive analysis of potential failure modes, race conditions, and scaling bottlenecks in this architecture, along with proposed solutions and their trade-offs: 1.

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-5.4 Pro: This agreement is heavily client-favored. Every numbered clause has language that could be used against the contractor. Short version: I would not sign it without major redlines to Clauses 1–9, especially 2, 3, 4, 5, 6, and 7. Below is a clause-by-clause review.

    Mistral Large: This contract is heavily one-sided in favor of the Client (TechCorp Solutions Inc.) and contains multiple clauses that could be exploited, abused, or used to unfairly disadvantage the Contractor. Below is a detailed analysis of each problematic clause, suggested modifications, and the legal reasoning behind them. 1.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-5.4 Pro: For an experienced software engineer Think of an LLM less like a database of facts and more like a gigantic learned program that has been trained to compress the patterns of text, code, and conversations into its weights.

    Mistral Large: 1. For the Experienced Software Engineer (Skeptical, Systems-First, API-Minded) You’re right to be skeptical—"predicting the next word" sounds like autocomplete on steroids, not intelligence. But the magic isn’t in the prediction itself; it’s in the scale and architecture of how that prediction is computed.

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GPT-5.4 Pro: Here’s a simple, beginner-friendly 1-month health and longevity plan built around 3 key areas: Nutrition Movement Recovery (sleep + stress) The goal is consistency, not perfection. Start small and make the habits easy enough to keep.

    Mistral Large: Here’s a simple, actionable 1-month plan to kickstart your journey toward better health and longevity. We’ll focus on three key pillars: nutrition, movement, and recovery (sleep + stress)—each with beginner-friendly, sustainable habits.

    Every model's answer to this prompt

Favorites

Movie

Album

Book

City

Same pick

Game

GPT-5.4 ProGPT-5.4 Pro

Spirited Away

2001

Abbey Road

The Beatles

Pale Fire

Vladimir Nabokov

Kyoto

Japan

Outer Wilds

Indie, Adventure

Mistral LargeMistral Large

The Shawshank Redemption

1994

OK Computer

Radiohead

La sombra del viento

Carlos Ruiz Zafón

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

Not enough votes to call it. On the specs, GPT-5.4 Pro has the edge: bigger model tier, newer, bigger context window, major provider backing. Mistral Large costs 7.5x less per token.

GPT-5.4 Pro and Mistral Large compared across 18 shared prompts
SpecGPT-5.4 ProMistral Large
Input price$30/M tokens$8/M tokens
Output price$180/M tokens$24/M tokens
Context window1.1M tokens32K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedMar 2026Feb 2024
At 10M a month$300$300$80.00$80.00
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it3 hosts
GPT-5.4 Pro2 hosts
HostInOutContextUptime
  • Azure AI Foundry$30.00 in·$180.00 out·1.1M–not listed
  • OpenAI$30.00 in·$180.00 out·1.1M–not listed
Mistral Large1 host
HostInOutContextUptime
  • Mistral$2.00 in·$6.00 out·128k·99.9% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between GPT-5.4 Pro and Mistral Large?

GPT-5.4 Pro is developed by OpenAI while Mistral Large is developed by Mistral AI. GPT-5.4 Pro has a 1.1M token context window vs Mistral Large's 32K. You can compare their actual outputs across 18 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.4 Pro or Mistral Large?

It depends on your use case. GPT-5.4 Pro and Mistral Large each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 18 challenges so you can judge which fits your needs best.

How much does GPT-5.4 Pro cost compared to Mistral Large?

GPT-5.4 Pro costs $30/M input tokens and Mistral Large costs $8/M input tokens. Mistral Large is $22.00/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare GPT-5.4 Pro and Mistral Large on Rival?

This page shows a side-by-side comparison of GPT-5.4 Pro and Mistral Large 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.

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  • GPT-5.4 Pro vs GPT-6.1 SolLanded Sep 2026
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  • GPT-5.4 Pro vs Solar Mini 4Landed Sep 2026
  • Mistral Large vs Qwen3.8 Max PrimeLanded Sep 2026

Same lab, same size, long tail

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Model pages

  • GPT-5.4 Pro18 outputs, specs and price
  • Mistral Large59 outputs, specs and price
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