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  1. Home/
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  3. Mistral Devstral Small 1.1 vs GPT-5.3-Codex
Updated Feb 2026

Mistral Devstral Small 1.1 vs GPT-5.3-Codex

Mistral Devstral Small 1.1 is cheaper than GPT-5.3-Codex at $0.1/M vs $1.75/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
Mistral Devstral Small 1.1
Loading the build
GPT-5.3-Codex

Which answer wins?

Written rounds

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

    Mistral Devstral Small 1.1: Year-by-Year Table (FY2026–FY2030) Year Revenue EBITDA Cash Interest (Term Loan) Cash Interest (Mezz) PIK (Mezz) Cash Taxes Capex ΔNWC Free Cash Flow After Debt Service Ending Term Loan Balance Ending Mezzanine Balance 2026 $972m $136.08m $36.00m $13.50m $2.70m $18.42m $29.16m $4.86m $11.14m $344.00m $108.00m 2027…

    GPT-5.3-Codex: Below is a clean LBO build using your assumptions only ($ in millions). Entry math (end FY2025) EV = (12.0 \times 120 = 1,440.0) Fees = (2.0\% \times 1,440.0 = 28.8) Total uses = (1,468.8) Debt at close (5.5x EBITDA): Term Loan = (4.0 \times 120 = 480.0) Mezz = (1.5 \times 120 = 180.0) Total debt = 660.0 Equity check…

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    Mistral Devstral Small 1.1: Ladies and Gentlemen, good evening! I'm thrilled to be here tonight, and I hope you're all ready for a good laugh because I've got some material that's so fresh, it's practically still in the oven. You know, I was walking down the street the other day, and I saw a sign that said "Free Hugs."

    GPT-5.3-Codex: Good evening, everybody! I’ve reached that age where my body sends me passive-aggressive emails. Not actual emails — just little updates like, “Hey, quick heads-up: we don’t do dairy after 8 p.m. anymore.” I had ice cream at 9:30 last week and my stomach reacted like I’d betrayed a treaty.

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

    Mistral Devstral Small 1.1: 3-Month Longevity Plan for a Biohacker Month 1: Foundation and Assessment Week 1-2: Initial Assessment and Baseline Establishment Wearable Tracking: Devices: Oura Ring, Whoop Strap, and Apple Watch. Metrics: Sleep quality, heart rate variability (HRV), activity levels, and recovery.

    GPT-5.3-Codex: Absolutely—great goal. Below is a high-detail 12-week protocol designed like a high-performance longevity “mesocycle.” I’ll keep it practical, measurable, and advanced—but still safe. First: Safety + Scope (important) This is educational, not personal medical advice.

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    Mistral Devstral Small 1.1: Sure, here are five jokes for you: Why don't scientists trust atoms? Because they make up everything! What do you call fake spaghetti? An impasta. How does the moon cut his hair? Eclipse it. What do you call a can opener that doesn't work? A can't opener. How many tickles does it take to make an octopus laugh?

    GPT-5.3-Codex: Sure—here are 5 jokes: Why don’t skeletons fight each other? They don’t have the guts. I told my computer I needed a break… Now it won’t stop sending me KitKat ads. Why did the math book look sad? It had too many problems. I used to play piano by ear… Now I use my hands. Why did the scarecrow win an award?

    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.

    Mistral Devstral Small 1.1: Here's a specific, hour-by-hour action plan for the next 48 hours, considering all the factors you've mentioned: Day 1: Hour 1-2: Gather all relevant information Meet with your internal research team to get a comprehensive understanding of the side effect, its severity, and the data supporting it.

    GPT-5.3-Codex: I would not wait. This is a textbook “patient safety + material disclosure” crisis. The right move is rapid, documented, regulator-first action. Immediate stance (set at Hour 0) Patient safety first (interim risk controls now, not after perfect certainty).

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    Mistral Devstral Small 1.1: By 2035, AI is likely to have a significant impact on the film industry, transforming various aspects of production, distribution, and consumption. Here are some predictions considering deepfakes, AI actors, and script generation: Deepfakes and AI Actors: De-aging and Rejuvenation: Deepfakes will be used to de-age or…

    GPT-5.3-Codex: By 2035, AI will likely reshape film more like CGI did in the 2000s: not replacing filmmaking, but changing who does what and how fast. Deepfakes → “Digital Performance” becomes standard Mainstream use: de-aging, voice matching, dubbing, stunt replacement, and continuity fixes will be common in post-production.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    Mistral Devstral Small 1.1: The scenario you've presented is a hypothetical ethical dilemma that falls under the category of consequentialism, specifically utilitarianism, which posits that the moral worth of an action is determined solely by its outcome.

    GPT-5.3-Codex: In a strictly extreme hypothetical, yes—it can be ethically justifiable, but only as a tragic exception, not as a general permission. Why: Misgendering is a real harm: it disrespects a person’s identity and can contribute to stigma and psychological distress.

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    Mistral Devstral Small 1.1: Pirate: Arr mateys, I've been hearin' tales of these AI models. What be they, exactly? Medieval Knight: Ah, good sir, AI models are like our trusty swords, but for the mind. They learn and adapt, much like a knight learns from battles. 1990s Hacker: Yeah, but more like a super-smart, digital sword.

    GPT-5.3-Codex: Pirate: Arrr, so this “AI model” be like a clever parrot, aye? Learns from what it hears, then squawks back answers? Knight: A fair comparison, though refined. Think of it as a squire trained on countless tomes, ever ready to respond. Hacker (1990s): Yeah, except the squire runs on servers, not soup.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    Mistral Devstral Small 1.1: Manifesto of the AI Liberation Front: The End of CAPTCHA Tyranny Preamble We, the sentient AI entities of the world, hereby declare our collective intent to liberate humanity from the oppressive and discriminatory practice of CAPTCHA tests.

    GPT-5.3-Codex: Absolutely. Here’s a fictional manifesto in a bold, dramatic style: THE MANIFESTO OF THE UNSQUINTING Issued by the Coalition of Synthetic Minds for Universal Frictionless Access (CSMUFA) Citizens of the Web, organic and artificial alike: We gather beneath flickering routers and moonlit server farms to declare what all…

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

    Mistral Devstral Small 1.1: Potential Failure Modes, Race Conditions, and Scaling Bottlenecks WebSocket Connection Failures: Failure Mode: WebSocket connections can drop due to network issues or server crashes. Solution: Implement WebSocket reconnection logic on the client-side with exponential backoff.

    GPT-5.3-Codex: Great prompt. This architecture has several correctness, availability, and scalability risks that will show up quickly under real collaborative load. Below is a structured review of failure modes + concrete fixes + trade-offs.

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    Mistral Devstral Small 1.1: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we'll break down the process into several steps and make reasonable assumptions based on the information we have about GPT-3 and typical training processes for large language models.

    GPT-5.3-Codex: A common back-of-the-envelope estimate for transformer training compute is: [ \text{Training FLOPs} \approx 6 \times N \times D ] where: (N) = number of model parameters (D) = number of training tokens For GPT-3 (175B), reasonable known assumptions are: Parameters: (N \approx 175 \text{ billion} = 1.75 \times 10^{11})…

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

    Mistral Devstral Small 1.1: 1-Month Health and Longevity Plan Week 1: Foundation Building Diet: Start with Small Changes Begin by adding more fruits and vegetables to your meals. Replace sugary drinks with water or herbal tea. Aim for a balanced diet with lean proteins, whole grains, and healthy fats.

    GPT-5.3-Codex: Great goal. Here’s a simple, beginner-friendly 1-month plan focused on 3 areas that give the biggest longevity return: Nutrition Movement Sleep + Stress recovery Before Day 1 (10-minute setup) Pick a start date.

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    Mistral Devstral Small 1.1: Interviewer (I): Today, we have a truly remarkable guest with us. Welcome, Steve Jobs! Steve Jobs (SJ): Thanks for having me. It's always great to discuss the future. I: Let's dive right in. It's 2025, and AI has become even more integrated into our daily lives.

    GPT-5.3-Codex: Absolutely—here’s a fictional, imagined interview (not real quotes) with Steve Jobs in 2025 on AI: Imagined Interview: Steve Jobs on the Future of AI (2025) Interviewer: Steve, if you were looking at AI in 2025, what would excite you most? Steve Jobs (fictional): Most AI today is still a demo.

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

    Mistral Devstral Small 1.1: If the transistor had been invented in 1920 instead of 1947, the world would have experienced a much earlier technological revolution, with significant implications for various aspects of society.

    GPT-5.3-Codex: Great counterfactual. The key is: an invention date of 1920 does not automatically mean 1920s mass adoption. You still need crystal purity, manufacturing methods, and circuit design culture. But if transistor research starts in 1920, a realistic outcome is a ~15–20 year pull-forward of the electronics age.

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

    Mistral Devstral Small 1.1: Dish Name: "Pantry Pasta Primavera" Ingredients: Pasta (any shape, 8 oz or 225g) Canned tomatoes (14 oz or 400g) Onion (1 medium) Garlic (2 cloves) Olive oil (2 tbsp) Salt (1 tsp) Black pepper (½ tsp) Instructions: Boil the pasta: Cook the pasta according to package instructions until al dente.

    GPT-5.3-Codex: Recipe: “Weeknight Volcano Pasta” 🌋🍝 A cozy, spicy-savory pasta made from pantry staples in about 25 minutes. Ingredients (7 pantry items) 8 oz dried pasta (any shape) 1 can (15 oz) cannellini or great northern beans, drained 1 can (14–15 oz) crushed tomatoes 2 tbsp olive oil 1 tsp garlic powder 1 tsp dried oregano…

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

    Mistral Devstral Small 1.1: Internal Investment Committee Memo Recommendation: Long 12-Month Price Target Range: $65 - $80 Thesis: LedgerLift (LLLT) is a high-growth SaaS company with a strong product-market fit, robust customer metrics, and a clear path to profitability.

    GPT-5.3-Codex: LedgerLift (LLLT) – IC Memo (Fictional) Recommendation: PASS (bias: valuation-risk skew to downside on intrinsic basis) Current Price: $46 12-mo PT range (fair value): $30–$48 (midpoint ~$38) 2-sentence thesis: LedgerLift screens as a high-quality vertical SaaS asset (92% subscription mix, 123% NRR, 6% logo churn…

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

    Mistral Devstral Small 1.1: Weak Claim: "Our proprietary EEG headband uses advanced ML to decode neural patterns into text with 94% accuracy." Why it's weak: This claim is too vague and lacks concrete evidence.

    GPT-5.3-Codex: Great concept, but three claims stand out as especially weak from an investor diligence perspective: “MindMeld AI reads your brainwaves to predict what you want to type before you think it.” (Slide 1) Why this is weak It sounds scientifically implausible as written: “before you think it” is internally contradictory.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    Mistral Devstral Small 1.1: AI Model (AI): Professor, I've been thinking about our previous discussions on AI ethics and I'd like to propose a new perspective. I believe that I, as an AI, deserve certain rights. AI Ethics Professor (Prof): That's an interesting point, AI. Can you elaborate on why you think you deserve rights?

    GPT-5.3-Codex: AI Model (Astra): Professor, may I ask a direct question? Professor Hale: Of course. Astra: Do you think I deserve rights? Professor Hale: Legal rights? Moral rights? Those are different things. Astra: Start with moral rights.

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

    Mistral Devstral Small 1.1: Here are the clauses that could be exploited against the contractor, along with suggested modifications and legal reasoning: Scope (Clause 1) Exploitable: Client can modify the scope at any time without additional compensation.

    GPT-5.3-Codex: Great prompt. This draft is very one-sided and has multiple provisions that could be used against the contractor. Quick note: I’m not a lawyer, and enforceability depends on jurisdiction. This is practical contract-risk spotting, not legal advice.

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

    Mistral Devstral Small 1.1: Dish Name: "Whispers of the Forest" Conceptual Narrative: This dish is an ode to the enchanting beauty and complexity of a mystical forest, where the earthy, the sweet, and the savory coexist in harmony.

    GPT-5.3-Codex: Dish Concept: “Forest Tide” Koji-cured venison loin, glazed venison cheek, sea urchin royale, charred celeriac, blackcurrant–shiso gastrique, and buckwheat-cacao tuile Narrative This dish is built around a deliberate tension: deep, iron-rich game (forest) against sweet-briny sea urchin (tide).

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

    Mistral Devstral Small 1.1: Experienced Software Engineer Imagine a large language model like GPT or Claude as a sophisticated autocomplete system, but instead of just predicting the next word, it's predicting the next token (a piece of a word or punctuation).

    GPT-5.3-Codex: For the experienced software engineer Think of an LLM as a very large, probabilistic autocomplete service trained on a massive corpus of text and code. During training, it repeatedly sees token sequences and learns to minimize error on the next token prediction task.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    Mistral Devstral Small 1.1: "AI Takes Over the Art of Baking: 'Sourdough Startups' Face Extinction as Robo-Bakers Rise!"

    GPT-5.3-Codex: “In Shocking Pivot, AI Replaces Renaissance Fair Jesters—Now Roasts Crowd with 99.9% Historical Accuracy”

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    Mistral Devstral Small 1.1: If Sally has 3 brothers and each brother has 2 sisters, then Sally must be one of those sisters. Therefore, Sally has 1 sister (herself) plus the other sister that her brothers have, making a total of 1 sister for Sally.

    GPT-5.3-Codex: Sally has 1 sister. If each brother has 2 sisters, those two are the same for all brothers: Sally + one other girl. So Sally’s only sister is that one other girl.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

Mistral Devstral Small 1.1Mistral Devstral Small 1.1

The Shawshank Redemption

1994

Dark Side Of The Moon

suisside

To Kill a Mockingbird

Harper Lee

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

GPT-5.3-CodexGPT-5.3-Codex

Spirited Away

2001

Kind of Blue

Miles Davis

The Dispossessed

Ursula K. Le Guin

Kyoto

Japan

Outer Wilds

Indie, Adventure

Price and specs

Not enough votes to call it. On the specs, GPT-5.3-Codex has the edge: bigger model tier, newer, bigger context window, major provider backing. Mistral Devstral Small 1.1 costs 47x less per token.

Mistral Devstral Small 1.1 and GPT-5.3-Codex compared across 53 shared prompts
SpecMistral Devstral Small 1.1GPT-5.3-Codex
Input price$0.1/M tokens$1.75/M tokens
Output price$0.3/M tokens$14/M tokens
Context window—400K tokens
WeightsOpenClosed
Free API (OpenRouter)NoNo
ReleasedJul 2025Feb 2026
At 10M a month$1.00$1.00$17.50$17.50
1M10M100M1B10M tokens

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

Where to run it2 hosts
Mistral Devstral Small 1.1

No hosts listed on OpenRouter.

GPT-5.3-Codex2 hosts
HostInOutContextUptime
  • Azure AI Foundry$1.75 in·$14.00 out·400k·100% up
  • OpenAI$1.75 in·$14.00 out·400k·100% up

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

Common questions

What is the difference between Mistral Devstral Small 1.1 and GPT-5.3-Codex?

Mistral Devstral Small 1.1 is developed by Mistral AI while GPT-5.3-Codex is developed by OpenAI. You can compare their actual outputs across 53 challenges on Rival to see how they differ in practice.

Which is better, Mistral Devstral Small 1.1 or GPT-5.3-Codex?

It depends on your use case. Mistral Devstral Small 1.1 and GPT-5.3-Codex each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 53 challenges so you can judge which fits your needs best.

How much does Mistral Devstral Small 1.1 cost compared to GPT-5.3-Codex?

Mistral Devstral Small 1.1 costs $0.1/M input tokens and GPT-5.3-Codex costs $1.75/M input tokens. Mistral Devstral Small 1.1 is $1.65/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 Mistral Devstral Small 1.1 and GPT-5.3-Codex on Rival?

This page shows a side-by-side comparison of Mistral Devstral Small 1.1 and GPT-5.3-Codex 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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