In this article on DeepSeek vs Mistral, we'll explore everything you need to know about these innovative AI models that are challenging the established players in the field.
Here is what we are going to cover:
What is DeepSeek and its capabilities
What makes DeepSeek different
What is Mistral and its capabilities
What makes Mistral different
Cost comparison between both models
Reddit users' opinions on both models
Everyday use case tests on both models:
Document analysis
Image analysis
Topic explanation
Coding performance
Elephas - a Mac AI assistant that works with both models
Which AI is the best choice for different needs
By the end of this article, you'll get to know both models' capabilities and also compare two powerful AI systems across various metrics, helping you decide which one best fits your specific requirements and budget constraints.
Let's get into it.
What is DeepSeek?
DeepSeek is an innovative AI language model developed in China that's rapidly gaining recognition in the AI landscape. It delivers premium-level AI capabilities at more affordable prices than many competitors. DeepSeek specializes in methodical problem-solving through step-by-step reasoning processes, making it particularly effective for complex tasks across multiple domains. know more
DeepSeek Capabilities:
Outperforms Claude and GPT-4o on various reasoning benchmarks
Achieves 91.6% accuracy on the DROP reading comprehension test
Scores 89.1% on MMLU-Redux knowledge assessments
Excels at mathematics with 90.2% on MATH-500 (beating Claude's 78.3%)
Demonstrates superior coding abilities across multiple programming languages
Functions effectively in both English and Chinese
DeepSeek Pricing
DeepSeek is completely free to use, and you can also download the models and run them locally.
As per the DeepSeek API, pricing is significantly cheaper than models like ChatGPT and Gemini.
What makes DeepSeek Different?
What makes DeepSeek truly different is its innovative Mixture of Experts architecture, utilizing 671 billion total parameters while only activating 37 billion at once. This clever design approach allows DeepSeek to deliver exceptional performance while consuming significantly fewer computational resources than comparable models.
Also, DeepSeek thinks before answering, which makes its output have better accuracy than even premium models from top AI companies. Additionally, DeepSeek provides their main constitutional model free and open source, so users can download their model and run it locally.
However, it should be noted that system requirements might skyrocket to run the main DeepSeek model, but you can choose smaller models that you can easily run locally on your computer.
DeepSeek vs Mistral Cost Comparison
When comparing DeepSeek and Mistral models on cost efficiency, the pricing chart reveals significant differences. DeepSeek Pro is priced at $1 per million tokens, positioning it in the lower-mid range of the market. This makes it considerably more affordable than Mistral's offerings.
Mistral's models show varied pricing tiers, with Claude 3.5 Sonnet (from Anthropic, which partners with Mistral) at $6 per million tokens and Claude Opus at a premium $26.3. Mistral's own branded models fall in the mid-range, with Mistral Large at approximately $3 per million tokens.
DeepSeek maintains a cost advantage over Mistral's higher-tier options, making it potentially more attractive for budget-conscious applications that still require decent performance. For organizations where processing costs significantly impact operational expenses, DeepSeek offers better value, while Mistral positions itself as a mid-range option with stronger performance metrics in certain categories.
What is Mistral?
Mistral AI is a French startup that makes AI language models. Founded in 2023 by former researchers from Google DeepMind and Meta, the company has quickly gained attention in the AI world. Mistral creates both open source models that anyone can use freely and commercial models that businesses can pay to access.
The company aims to provide an alternative to bigger AI companies by making their technology more accessible and affordable. With strong financial backing from investors like Microsoft and Andreessen Horowitz, Mistral has reached a value of about $6 billion and continues to grow in popularity.
Mistral Capabilities
Mistral AI models, particularly Mistral Large, demonstrate impressive capabilities across various benchmarks, placing them among the top-performing AI systems available today.
Performance Benchmarks:
Coding Proficiency: Mistral Large scores 45.1% on HumanE and 73.1% on MBPP coding benchmarks
Mathematical Abilities: Achieves 91.21% on GSM8K (8-shot) math problems, showing strong numerical reasoning
Reasoning Skills: Scores 94.2% on Arc C (5-shot) and 94.0% on Arc C (25-shot) reasoning tests
Knowledge Base: Reaches 82.7% on TriviaQA and 50.5% on TruthfulQA knowledge benchmarks
Overall Ranking: Stands as the world's second-ranked model generally available through API (after GPT-4)
Mistral Large shows exceptional reasoning capabilities across multiple benchmark categories. In common sense and reasoning tests, it achieves 81.2% on MMLU (Measuring Massive Multitask Language Understanding), 89.2% on HellaSwag, and 86.7% on WinoG. These scores demonstrate the model's ability to understand context, apply logic, and make sensible inferences.
When compared to other leading models, Mistral Large holds its own against industry giants. With an overall benchmark score of 81.2%, it ranks second only to GPT-4 (86.4%), surpassing other prominent models like Claude 2 (78.5%), Gemini Pro (71.8%), GPT-3.5 (70.0%), and LLaMA 2 (69.9%).
Different Mistral Models
Mistral offers several AI models to meet different needs:
Commercial Models:
Mistral Large 2 - Their most advanced model
Mistral Large - Good for complex tasks
Mistral Small - Faster for simpler tasks
Mistral Embed - For text analysis
Open Source Models:
Mistral 7B - Easy to customize
Mixtral 8x7B - Efficient performance
Mixtral 8x22B - Advanced open source option
Codestral Mamba - For coding
Mathstral - For math problems
Mistral NeMo - Multilingual capabilities
Mistral also has an AI chatbot called Le Chat that works like ChatGPT but lets users choose which Mistral model powers it.
Mistral Pricing
You can use Mistral for day-to-day use just like ChatGPT, and they have a paid plan that starts at $14.99/month. Mistral also provides open-source models that users can download and use on their computer and run them locally.
Mistral offers competitive pricing compared to other AI models. Their API pricing for Mistral Cloud is as follows:
What Makes Mistral Different?
What sets Mistral apart is their focus on efficiency and openness. Their models use special architecture that requires less computing power while maintaining high performance. Many of their models are open source, allowing users to see how they work and modify them for specific needs.
This openness is particularly valuable for companies in industries with strict privacy rules. Mistral models work well in multiple languages, including English, French, Spanish, German, and Italian. They can also integrate with other systems through function calling capabilities, making them more versatile for various applications.
Also, Mistral is one of the few platforms that provide features like image generation and image analysis, as well as web search features.
Redditors Opinion on DeepSeek vs Mistral
Reddit is the best place to get unfiltered opinions on which AI models are performing well, and Redditors' perspectives offer valuable insights into real-world usage. But, like in our other LLM model comparison articles, we could not find actual Reddit posts that are comparing DeepSeek and Mistral.
So, we have to pick the one that is most related and has a lot of people's opinions, and we found this post discussing Le Chat's rise to popularity and compiled the diverse opinions shared by users.
Speed vs Quality Debate
Many Redditors acknowledged Le Chat's impressive speed but questioned whether that alone makes it superior.
Specter_Origin explained: "They have a smaller model which runs on Cerebras; the magic is not on their end, it's just Cerebras being very fast. The model is decent but definitely not a replacement for Claude, GPT-4o, R1 or other large, advanced models."
PastRequirement3218 questioned the focus on speed: "So it just gives you a shitty reply faster? What about a quality response? I don't give a damn if it has to think about it for a few more seconds, I want something useful and good."
Technical Insights
Several users shared technical knowledge about how Le Chat achieves its performance.
AdIllustrious436 clarified: "I had the confirmation from the staff that the model running on Cerebras chips is Large 2.1, their flagship model." They also estimated its capabilities are "somewhere between 4o-mini and 4o for reference. It's a 123b model."
mikael110 explained the technology: "Speculative Decoding does not alter the behavior of a model. That's a fundamental part of how it works. It produces identical outputs to non-speculative inference."
Relevant-Draft-7780 shared insights about the hardware: "Cerebra's is super fast. It's crazy they can generate between 2000 to 2700k tokens per second... If you do a bit of googling you'll see cerebras' 96k core count chip 25kW and the size of a dinner plate."
Use Case Perspectives
Different Redditors highlighted various strengths and weaknesses in real-world applications.
satireplusplus noted: "For programming it really shines with it's large context. It must be larger than ChatGPT, as it stays coherent with longer source code."
WolpertingerRumo offered this perspective: "While chatGPT and DeepSeek are smart, Gemini/Gemma is concise and fast, Llama is versatile, Qwen is good at coding, Mistral is charming. It's the best at actual chatting."
Club27Seb was less impressed: "Claude, GPT and Gemini eat it for lunch when it comes to coding (comparing all ~$15/month models). I felt I myself wasting the $15 I spent on this, though it may shine at easier tasks."
omnisvosscio found specific strengths: "Mistral models are lowkey OP for domain-specific tasks. Super smooth to fine-tune, and I've built agentic apps with them no problem."
General Reception
Overall opinions on Le Chat varied widely among Reddit users.
Touch105 had a positive experience: "Mistral is quite similar to chatGPT DeepSeek in terms of quality/relevancy but with faster replies. It's a no brainer for me."
ThenExtension9196 was less impressed: "It was mid in my testing. Deleted the app... It didn't bring anything new to the table."
While Le Chat's speed is certainly impressive, users value different aspects in their AI assistants, from accuracy and problem-solving capabilities to personality and specialized skills.
DeepSeek vs Mistral: Which is best?
The LLM benchmarks do not give much information on how they actually help in practical day-to-day tasks. So, to know which model between DeepSeek vs Mistral actually performs better in day-to-day tasks, we are going to conduct some tests ranging from document analysis to coding.
So check them out.
Test 1: Document Analysis
For the first test, we have given both models a lengthy research paper on AI agents, and we asked both models to identify a contributor in the research paper and also a topic from the research paper.
Mistral was able to answer the topic well, but it completely failed when it came to referencing the author. While DeepSeek took more time for document upload, it provided both the reference paragraph of the contributor and an explanation of the topic asked.
If you want to know more about creating AI agents, check out How to Create AI Agents for Free.
Test 2: Coding
So for the coding test, we have asked both the models to write code for the Air Attack 2 game to know how well they can write code. Well, DeepSeek was able to create a better version of the Air Attack 2 game that is not playable, but everything else, like the score getting low when hit or the increase in score, etc., is functioning. However, Mistral's code was playable; you can control the block, but it is nowhere near the actual game.
Test 3: Image Analysis
For the image analysis, we created an AI-generated image and asked both DeepSeek and Mistral AI, "What text do you detect in the image?" and "Can they read the text on the billboard and street signs?"
Both models were able to generate good answers and also able to detect text. While Mistral was able to give some major names, DeepSeek even provided a notes section where it pointed out some points that were misspelled and what the actual names should be in the image. So you be the judge of it and decide which is better and also let us know in the comments.
Also, it should be noted that DeepSeek can only detect text in an image. But Mistral AI can detect images and even tell what they are.
Test 4: Topic Explanation
At the time of our testing, DeepSeek's web search feature is down, so we cannot perform a web search test like we do with other models such as ChatGPT vs. DeepSeek, Claude vs. DeepSeek, DeepSeek vs Llama and Gemini vs. DeepSeek.
However, when we tried to ask both models who the first person to introduce artificial intelligence was, Mistral AI used the web search feature as we cannot turn it off. Even with web search, DeepSeek was able to give a better answer than Mistral AI.
While Mistral AI just provided us with the name of the second introducer of artificial intelligence, DeepSeek was able to give both the name of the first introducer and an explanation of how the second introducer actually made it popular.
Elephas: Integrate DeepSeek and Mistral for Enhanced Productivity
Elephas transforms your Mac into a powerful knowledge assistant by letting you harness the capabilities of both DeepSeek and Mistral AI models according to your preferences. Elephas brings advanced AI to your fingertips with complete offline functionality.
Key features:
Multi-AI Model Support: Switch seamlessly between DeepSeek's mathematical precision and Mistral's multilingual capabilities
Super Brain: Build a personalized knowledge repository by collecting information from various sources
Local Embeddings: Run completely offline for enhanced privacy and security
Smart Writing Tools: Generate high-quality content with four rewrite modes including Professional, Friendly, Zinsser, and Viral
Notes Feature: Easily capture web content, YouTube videos, and ideas with simple commands
Grammar Fixes: Automatically correct errors for polished, error-free writing
Content Repurposing: Transform existing content for different platforms and mediums
iOS Compatibility: Access powerful features on iPhone and iPad with the AI Keyboard
Experience the best of both AI models while maintaining complete control over your data and workflow with Elephas.
DeepSeek vs Mistral: The best choice?
When choosing between DeepSeek and Mistral, several key differences stand out. DeepSeek offers stronger performance in math and coding tasks while maintaining a significantly lower compared to Mistral. DeepSeek also excels at document analysis, providing more detailed responses when reviewing research papers.
While both models handle image analysis well, DeepSeek provides more thorough text detection with helpful notes about misspellings. Mistral has broader image capabilities beyond just text detection.
For daily use, Mistral offers faster response times and comes with a user-friendly chat interface called Le Chat. It also supports more languages, including French, Spanish, German, and Italian.
Your best choice depends on your specific needs: DeepSeek wins for budget-conscious users requiring strong math and coding capabilities, while Mistral makes sense for those needing faster responses, multilingual support, and more comprehensive image analysis features.
Both offer free basic access and downloadable models for local use. So you can trial and test the one that best suits to your needs.
FAQs
1. Which AI is better for coding tasks, DeepSeek or Mistral?
DeepSeek outperforms Mistral on coding tasks, scoring higher on benchmarks and producing more functional code during real-world testing. DeepSeek creates more complete, accurate code implementations while Mistral's code may be more basic but still operational.
2. Can I run DeepSeek or Mistral models locally on my computer?
Both DeepSeek and Mistral offer downloadable open-source models you can run locally. DeepSeek's main model has higher system requirements, but smaller versions are available. Mistral provides several open-source options like Mistral 7B that work on standard hardware.
3. Can I use Elephas with both DeepSeek and Mistral models?
Yes, Elephas supports multiple AI providers including DeepSeek and Mistral. You can seamlessly switch between these models based on your specific needs, taking advantage of DeepSeek's math capabilities or Mistral's language strengths.
4. Which AI model is faster, DeepSeek or Mistral?
Mistral provides faster response times through its Le Chat interface, which many users appreciate. DeepSeek takes longer to process information because it "thinks before answering," which contributes to its higher accuracy but results in slightly slower response times.
5. Does Mistral or DeepSeek have better multilingual capabilities?
Mistral has stronger multilingual support, with fluency in English, French, Spanish, German, and Italian. DeepSeek excels primarily in English and Chinese. If you need an AI assistant that works well across multiple European languages, Mistral is the better choice.
