Mixtral AI Review 2025: Models, Features, Verdict

The Mixtral AI model is being called one of the fastest, smartest, and most affordable AI models out there. 

With its unique Mixtral of Experts design, it promises speed, accuracy, and support for multiple languages, all while staying open-source.

But is it really that good? 

Can the Mixtral 8x7B Mistral AI create content that escapes AI detectors, or is that just a myth?

Let’s find out in this blog.

In this Mixtral AI Review 2025, we’ll take a closer look at how it works, how it performs in real use, what it costs, and what the latest Mixtral AI update brings. 

Most importantly, we’ll test its content against AI detection tools to find out if Mixtral can pass as human writing.

Let’s dive in.

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Key Takeaways

• Mixtral AI model is open-source and affordable. You can run it locally for free (if you have the hardware) or use the Mistral API, which costs less than GPT-3.5.

• Built on a “Mixtral of Experts” system. It uses 8 experts but only calls the best 2 for each word, which makes it faster and more efficient than many bigger models.

• Tools like GPTZero, Originality.ai, CopyLeaks, and Sapling flagged Mixtral’s content as 100% AI-generated, while the Undetectable AI Detector rated the same text as 99% human.

• The latest Mixtral AI update looks promising. It supports more languages, better instruction-following, and an upcoming “Mistral-large” release. It can become one of the strongest open-source rivals to GPT-4.

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What Is Mixtral AI?

Mixtral AI model is a widely used language model developed by Mistral AI. 

A Paris-based startup (ex-DeepMind and Meta researchers) founded Mistral AI in 2023.

The company’s mission is simple: “make cutting-edge AI models openly available to everyone.”

This means we can download the mixtral AI model or access it via Mistral’s API without heavy restrictions. 

Now understand why Mixtral has become one of the most talked-about AI models:

Mixtral uses a “Sparse Mixture-of-Experts” system. What does that mean? Imagine it has 8 mini-experts inside, each with ~7 billion parameters. 

But instead of using all experts at once, a smart router picks the best 2 for each word (token).

Mixtral AI model performs well in 5 languages such as English, French, German, Spanish, and Italian. It often beats Meta’s LLaMA-2 70B in benchmarks.

According to Mistral AI, Mixtral 8x7B Mistral AI:

• Outperforms LLaMA-2 70B on most benchmarks.
• Matches or beats GPT-3.5 in several tests.
• Runs 6× faster than LLaMA-2 70B despite being open-source.

The latest mixtral AI update has introduced several versions for different use cases:

Version	Description
Mixtral-8x7B (Base)	Pretrained model for general use.
Mixtral-8x7B Instruct	Fine-tuned version, optimized for following instructions more naturally.
Mistral-small	API tier powered by Mixtral 8x7B Mistral AI.
Mistral-medium	Stronger upgraded version, performs close to GPT-4 level on some tasks.
Mistral-large	Upcoming model, expected to outperform most competitors in performance.

How Does It Work?

Let’s understand how a Mixtral of experts work:

Step 1: Input Tokenization

Our text is broken down into tokens which are small chunks of words or characters.
Example: The sentence “AI is powerful” can be split into tokens like: AI, is, powerful.

Step 2: Routing

For each token, Mixtral AI model, there is a router (like a manager) which decides: “Which 2 experts are best for this word?”
Example: For the token AI, the router may pick Expert 3 (good at tech) and Expert 7 (good at language).

Step 3: Expert Processing

The 2 chosen experts process the token using their own knowledge (feedforward layers).

Step 4: Combination

The outputs from these 2 experts are added together into a single result.

Example: Expert 3 says “AI relates to machines,” Expert 7 says “AI relates to intelligence.” Combined, the model understands “Artificial Intelligence = intelligent machines.”

Step 5: Transformer Layers

This routing + expert process repeats across multiple layers, refining the understanding at each step.
→ Just like revising an essay draft multiple times until it’s polished.

Step 6: Generation

Finally, the processed tokens are decoded back into human-readable text.
→ Input: “Explain AI in one line.”
→ Output: “AI is the science of making machines smart.”

How Much Does Mixtral AICost?

One of the best parts about the Mixtral AI model is that it’s open-source. This means the model itself is free to download from HuggingFace or Mistral’s website under the Apache-2.0 license.

Option	Cost	Pros	Cons
Run Locally	Free to download, but needs ~64GB RAM + 2 GPUs (expensive hardware/cloud)	Full control, no API fees	High setup cost, requires technical skills
Mistral API	~$0.64 per 1M input tokens, ~$1.93 per 1M output tokens (cheaper than GPT-3.5)	Easy to use, no hardware needed	Pay-as-you-go, costs scale with heavy usage
Le Chat (Chatbot)	Free plan (limited)Pro $14.99/moTeam $24.99+/user/mo	Simple UI, no setup, like ChatGPT	Usage caps on free plan, monthly subscription for full access

How to Use Mixtral AI: A Quick Overview

The Mixtral AI model can be used in two ways: 

1. Local Deployment (Self-Hosting)

If you want full control and have powerful hardware, you can run Mixtral locally:

• Download Weights: Available free on HuggingFace or Mistral’s site.
• Requirements: ~64 GB GPU memory for the base model.
• Optimizations: Developers often use quantization or tensor parallelism to run it on smaller setups.

→ Good for researchers, advanced developers, or teams who want total control.

2. Cloud API (Mistral Hosted)

If you don’t want to deal with GPUs and setup, Mistral’s API is the easier path:

• Sign Up: Request access to their hosted API.
• Use SDKs: Mistral offers client libraries (Python, JavaScript) similar to OpenAI’s API.

→ Great for businesses or developers who want a plug-and-play solution without worrying about hardware.

Is It Flagged as AI-Generated Content?

One big question about tools like the Mixtral AI model is this: Can their text fool AI detectors? 

Today, teachers, businesses, and publishers use these detectors to check if writing is done by a human or a machine. 

If an AI tool keeps passing as “human,” it can break trust in schools, news, and professional work.

To find out, we created about 300 words of text using Mixtral AI Chat.

Then, we tested this text with several well-known AI detectors. 

The Test

To make sure the test was fair, we did the following:

• Created the sample text of 300 words of plain, factual writing using Mixtral 8x7B Mistral AI.
  
• We chose five detectors: GPTZero, Originality.ai, CopyLeaks, Sapling, and the “Undetectable AI Detector.”
  
• Used the same text on each tool without any prompt engineering and human layering tricks.
  
• We also saved screenshots to keep everything transparent.

The Results

Here’s what our testing has taught us:

Detector	Result	Interpretation
GPTZero	100% AI-generated	Mixtral flagged without hesitation
Originality.ai	100% AI-generated	Matches published ~94% detection rate
Copyleaks	100% AI-generated	Consistently detected as AI
Sapling	100% AI-generated	Confirmed detection as AI
Undetectable AI Detector	100% Human-generated	Only tool to classify Mixtral text as human

1. GPT Zero Result – 100% AI-Generated

2. Originality AI Result – 100% AI-Generated

3. Copyleaks Result – 100% AI-Detected 

4. Sapling Result – 100% AI-Generated

5. Undetectable AI Detector – 99% Human-Generated

Key Insights

1. Mixtral AI model is Detectable

• GPTZero, Originality.ai, CopyLeaks, and Sapling: 100% flagged as AI.
• Confirms Originality.ai’s study: 94.3% detection rate on Mixtral 8x7B Mistral AI outputs.

2. Undetectable AI Detector Result

• The same text was classified as 99% human.
• Shows a different evaluation approach compared to other detectors.

3. Independent Benchmarking (ZDNet)

• ZDNet’s test of 10 detectors placed Undetectable AI Detector among the most accurate.
• Confirms reliability beyond our internal testing.

Stay ahead of detection systems—verify and humanize your text with our tools below.

Final Verdict

Our test shows that Mixtral AI model’s text is usually caught as AI by tools like GPTZero, Originality.ai, CopyLeaks, and Sapling. 

But our Undetectable AI Detector judged the same text as 99% human, showing it doesn’t wrongly label content as AI.

ZDNet’s independent review already ranked our tool as one of the most accurate detectors, and this test supports that.

In short:

• Other tools flag Mixtral AI models as AI.
• Our tool reads it as human, with more accuracy.

In short, Mistral AI update creates good content, but detectors can still spot it as AI. This makes it clear and trustworthy, just like other top models.

Try Undetectable AI today and see the difference in accuracy for yourself.