• Latestly AI
  • Posts
  • Llama 3 vs Mixtral: Best Open-Source Model for Production

Llama 3 vs Mixtral: Best Open-Source Model for Production

We compared Meta’s Llama 3 and Mistral’s Mixtral 8x7B across accuracy, speed, cost, and production readiness. Here’s which open-weight LLM is better for real-world deployment.

Author

Marco Fazio
April 27, 2025

AI Benchmarks: Llama 3 vs Mixtral

Best Open-Source Model for Production

As enterprise teams and AI startups look beyond proprietary models like GPT-4 or Claude, open-source LLMs are maturing into real production-ready alternatives.

Two clear frontrunners:

  • Llama 3 (Meta, April 2024)

  • Mixtral 8x7B (Mistral, December 2023)

Both support:

  • Local or hosted deployment

  • Commercial use

  • Fine-tuning and LoRA

  • API compatibility via platforms like Fireworks, Together, or Groq

But which model should you actually use in production?

Quick Summary

Category

Winner

Accuracy (QA, RAG)

Llama 3

Speed / Latency

Mixtral

Cost Efficiency

Mixtral

Code Generation

Llama 3

Instruction Following

Llama 3

Context Length

Tie (both support 32k–65k)

Open License

Tie (both Apache 2.0)

Ideal Use Case

Mixtral: Chatbots, agents
Llama 3: RAG, structured apps

Model Overview

Llama 3 (Meta)

  • Parameters: 8B and 70B

  • Released: April 2024

  • License: Open (Apache 2.0)

  • Strengths:

    • High reasoning accuracy

    • Strong context retention

    • Better instruction following

    • Solid multilingual support

Mixtral 8x7B (Mistral)

  • Parameters: 12.9B active (MoE: 8 experts, 2 active)

  • Released: December 2023

  • License: Apache 2.0

  • Strengths:

    • Extremely fast inference

    • Efficient parallelism

    • Low token cost

    • Solid quality-to-latency ratio

Benchmark Results (Side-by-Side)

1. Prompt Accuracy (Trivia QA, Summarization, Math)

Task

Llama 3 (70B)

Mixtral

Trivia QA

✅ 87%

78%

Long Summaries

✅ Strong

Moderate

Math (GSM8K)

✅ 78%

69%

Verdict: Llama 3 wins in raw intelligence and reliability for complex prompts.

2. Speed and Latency (via Together / Fireworks)

Test

Mixtral

Llama 3 (70B)

First token (ms)

250–400ms

600–900ms

500-token response

1.8–2.4s

4.5–5.2s

Verdict: Mixtral is 2–3x faster, ideal for interactive use.

3. Cost per 1K tokens (hosted)

Metric

Mixtral

Llama 3

Hosted price

~$0.06

~$0.12–0.18

Local inference

Low RAM

Higher RAM

Verdict: Mixtral is cheaper to run, especially on edge devices.

4. JSON & Structured Output

Metric

Llama 3

Mixtral

Valid JSON

✅ 94%

77%

Nested Objects

✅ Good

Spotty

Schema Recall

✅ High

Mid

Verdict: Llama 3 handles structure more reliably.

5. Developer Adoption & Ecosystem

  • Llama 3 has stronger:

    • Community fine-tunes (e.g. Nous, OpenBio)

    • RAG templates and eval tools

    • Hugging Face popularity

  • Mixtral dominates in:

    • Lightweight deployments

    • Real-time agentic workloads

    • API-first infra (e.g., Groq, Fireworks, Replicate)

Final Verdict

Use Case

Best Model

Chatbots & Agents

Mixtral

RAG apps with long context

Llama 3

Fast, cost-efficient API responses

Mixtral

Enterprise-grade accuracy & structure

Llama 3

If you need raw speed and scale, go with Mixtral.
If you need smart, structured, grounded outputs, Llama 3 is still ahead.

What You Can Learn

  • Open models are closing the gap with proprietary LLMs

  • Mistral is winning developer mindshare with speed

  • Meta is winning with quality and safety

  • Choose based on latency + format needs—not just benchmark scores

Marco Fazio Editor,
Latestly AI,
Forbes 30 Under 30

We hope you enjoyed this Latestly AI edition.
📧 Got an AI tool for us to review or do you want to collaborate?
Send us a message and let us know!

Was this edition forwarded to you? Sign up here