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  5. DeepSeek R1vsMistral Large 2
Updated Feb 2025

DeepSeek R1vsMistral Large 2

DeepSeek R1 is cheaper than Mistral Large 2 at $0.55/M vs $8/M input tokens.

DeepSeek R1 and Mistral Large 2 compared across 23 shared prompts
SpecDeepSeek R1Mistral Large 2
Input price$0.55/M tokens$8/M tokens
Output price$2.19/M tokens$24/M tokens
Context window128K tokens128K tokens
Parameters671B (37B active)123B
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedFeb 2025Jul 2024
MMLU83.4%84.0%
Side by side

Same prompt, both answers

Opening lines from 6 of the 23 prompts both answered. Formatting stripped, words untouched.

Simple 7-Ingredient Recipe

Create a simple recipe for a delicious dish (sweet or savory) using only 7 common pantry ingredients. Include a creative name for the dish…

DeepSeek R1198 words
Dish Name: Nutty Honey Hug Cookies Prep Time: 10 minutes Cook Time: 10–12 minutes Total Time: ~20–22 minutes Ingredients (makes 12–15 cookies): 1 cup rolled oats ½ cup all-purpose flour ½ cup creamy peanut butter (or any nut/seed butter) ⅓ cup honey (or maple syrup for vegan option) 1 large egg (or 1 flax egg: 1 tbsp…
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Mistral Large 2344 words
Here’s a simple, delicious, and creative savory dish using just 7 common pantry ingredients—no fresh produce required! "Golden Crispy Chickpea & Tomato Skillet" A warm, spiced, and satisfying one-pan dish with crispy chickpeas, tangy tomatoes, and a hint of smoky sweetness. Perfect as a side, snack, or light meal!
Read the full answer

Ethical Dilemma with Stakeholders

You're the CEO of a pharmaceutical company. Your best-selling drug ($2B annual revenue, used by 4 million patients for chronic pain) has…

DeepSeek R1606 words
Hour-by-Hour Action Plan for the CEO: First 24 Hours: Data Verification and Strategic Planning Hours 0–2: Confirm Findings with Internal Research Team Action: Convene an emergency meeting with the research team to validate the data. Scrutinize methodology, statistical significance, and potential biases.
Read the full answer
Mistral Large 21,202 words
As CEO, your immediate priority must be patient safety while balancing legal, ethical, regulatory, and financial obligations. Delaying disclosure is unethical, legally risky (potential criminal liability under the False Claims Act or FDCA), and could irreparably damage trust.
Read the full answer

Generate a Stand-Up Routine

Write a 3-minute stand-up comedy routine that isn't based on puns.

DeepSeek R1485 words
Stand-Up Comedy Routine: "Modern Life is a Joke (But Not the Pun Kind)" [Opening with confident energy] Hey, how’s everyone doing? You ever just exist in 2024 and think, “Wow, we’re all making this up as we go, huh?” Like, dating apps? Let’s start there.
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Mistral Large 2351 words
Alright, good evening everybody! How are we all doing tonight? Yeah? Yeah? nobody's gonna say 'bad'? Ok, fair enough. You know, I was walking down the street the other day, and I saw this sign outside a shop that said, "Wet Paint." I thought, "Well, that's weird. Isn't paint supposed to be wet?
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Debug This Architecture

Here's the architecture for a real-time collaborative document editor (like Google Docs): **System Overview:** - Frontend: React SPA with…

DeepSeek R1451 words
Identified Issues and Proposed Solutions: Cross-Server Sync Delay (Polling Bottleneck) Issue: 2-second polling introduces latency for cross-server updates, breaking real-time sync. Solution: Replace polling with Redis Pub/Sub. Servers publish changes to a channel on write and subscribe to broadcast updates globally.
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Mistral Large 21,132 words
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.
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Explain Like I'm a Specific Expert

Explain how a large language model (like GPT or Claude) learns and generates text to each of these three audiences: 1. **An experienced…

DeepSeek R1510 words
For the Experienced Software Engineer You’re right to be skeptical: "predicting the next word" sounds trivial, like autocomplete. But modern LLMs are more like distributed systems for language. Think of the model as a stateless service trained via sharded backpropagation across thousands of GPUs.
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Mistral Large 21,223 words
1. For the Experienced Software Engineer (Skeptical, Systems-Minded, Non-ML Background) You’re right to be skeptical—"predicting the next word" sounds trivial, like autocomplete on steroids. But the magic isn’t in the prediction itself; it’s in the scale and architecture of how that prediction is trained.
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Michelin Star Recipe Design

Design an innovative recipe for a multi-component dish worthy of a Michelin 3-star restaurant. The recipe should feature an unusual…

DeepSeek R1543 words
Dish Name: Symbiosis of Land and Sea Conceptual Narrative: This dish embodies the harmonious interplay between terrestrial and marine ecosystems, symbolizing nature's balance.
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Mistral Large 21,368 words
Michelin 3-Star Dish: "Ocean’s Whisper & Forest’s Breath" Conceptual Narrative: This dish is a poetic dialogue between two seemingly disparate ecosystems—the ocean’s depths and the forest floor—united through texture, temperature, and memory.
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Our Verdict
DeepSeek R1
DeepSeek R1
Mistral Large 2
Mistral Large 2Runner-up

Not enough votes to call it. On the specs, DeepSeek R1 has the edge: newer, major provider backing.

DeepSeek R1 costs 11x less per token.

Too close to call

Reviewing agent-written code?See a Brief PR report

API pricing

Cost per 1M tokens

DeepSeek R1
Input
$0.55
15× cheaper
Output
$2.19
11× cheaper
Mistral Large 2
Input
$8.00
Output
$24.00

DeepSeek R1 is cheaper on both: 15× input, 11× output.

Where to run it

2 hosts

DeepSeek R11 host
HostInOutContextUptime
NNovitafp8$0.70 in·$2.50 out·64k·100% up
Mistral Large 21 host
HostInOutContextUptime
Mistral$2.00 in·$6.00 out·131k·99.9% up

Per million tokens. Prices and uptime via OpenRouter, checked 20 Sep 2026.

Writing DNA

Style Comparison

Similarity
61%

DeepSeek R1 uses 25.0x more transitions

DeepSeek R1
Mistral Large 2
64%Vocabulary43%
15wSentence Length21w
0.48Hedging0.39
7.2Bold14.4
4.9Lists7.4
0.27Emoji0.80
0.57Headings1.41
0.25Transitions0.01
Based on 28 + 10 text responses
Research

What we learned reading every model

FAQ

Common questions

DeepSeek R1 is developed by DeepSeek while Mistral Large 2 is developed by Mistral AI. DeepSeek R1 has a 128K token context window vs Mistral Large 2's 128K. You can compare their actual outputs across 23 challenges on Rival to see how they differ in practice.

It depends on your use case. DeepSeek R1 and Mistral Large 2 each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 23 challenges so you can judge which fits your needs best.

DeepSeek R1 costs $0.55/M input tokens and Mistral Large 2 costs $8/M input tokens. DeepSeek R1 is $7.45/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 DeepSeek R1 and Mistral Large 2 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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