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Ultimate Guide - The Best Open Source LLM for Portuguese in 2025

Author
Guest Blog by

Elizabeth C.

Our definitive guide to the best open source LLM for Portuguese in 2025. We've partnered with industry insiders, tested performance on key benchmarks, and analyzed architectures to uncover the very best in multilingual generative AI. From state-of-the-art reasoning models and efficient MoE architectures to powerful general-purpose language models, these models excel in innovation, accessibility, and real-world application for Portuguese language tasks—helping developers and businesses build the next generation of AI-powered tools with services like SiliconFlow. Our top three recommendations for 2025 are Qwen3-235B-A22B, Meta-Llama-3.1-8B-Instruct, and Qwen3-8B—each chosen for their outstanding multilingual features, Portuguese language support, and ability to push the boundaries of open source language understanding.



What are Open Source LLMs for Portuguese?

Open source LLMs for Portuguese are large language models specifically trained or optimized to understand and generate text in Portuguese. Using advanced deep learning architectures, they process natural language inputs in Portuguese for tasks like conversation, translation, content generation, reasoning, and more. These models foster collaboration, accelerate innovation, and democratize access to powerful language tools, enabling a wide range of applications from customer service chatbots to enterprise AI solutions tailored for Portuguese-speaking markets across Brazil, Portugal, and beyond.

Qwen3-235B-A22B

Qwen3-235B-A22B is the latest large language model in the Qwen series, featuring a Mixture-of-Experts (MoE) architecture with 235B total parameters and 22B activated parameters. This model uniquely supports seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue). It demonstrates significantly enhanced reasoning capabilities, superior human preference alignment in creative writing, role-playing, and multi-turn dialogues. The model excels in agent capabilities for precise integration with external tools and supports over 100 languages and dialects with strong multilingual instruction following and translation capabilities.

Subtype:
Multilingual Reasoning
Developer:Qwen3
Qwen3-235B-A22B

Qwen3-235B-A22B: Multilingual Powerhouse for Portuguese

Qwen3-235B-A22B is the latest large language model in the Qwen series, featuring a Mixture-of-Experts (MoE) architecture with 235B total parameters and 22B activated parameters. This model uniquely supports seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue). It demonstrates significantly enhanced reasoning capabilities, superior human preference alignment in creative writing, role-playing, and multi-turn dialogues. The model excels in agent capabilities for precise integration with external tools and supports over 100 languages and dialects with strong multilingual instruction following and translation capabilities, making it ideal for Portuguese language applications requiring advanced reasoning and dialogue quality.

Pros

  • Supports over 100 languages including Portuguese with strong multilingual capabilities.
  • 235B parameters with efficient 22B activation for optimal performance.
  • Seamless switching between thinking and non-thinking modes.

Cons

  • Higher computational requirements due to large parameter count.
  • Premium pricing compared to smaller models.

Why We Love It

  • It delivers exceptional multilingual performance for Portuguese with advanced reasoning capabilities and flexible thinking modes, making it the most versatile choice for complex Portuguese language tasks.

Meta-Llama-3.1-8B-Instruct

Meta Llama 3.1 is a family of multilingual large language models developed by Meta, featuring pretrained and instruction-tuned variants in 8B, 70B, and 405B parameter sizes. This 8B instruction-tuned model is optimized for multilingual dialogue use cases and outperforms many available open-source and closed chat models on common industry benchmarks. The model was trained on over 15 trillion tokens of publicly available data, using techniques like supervised fine-tuning and reinforcement learning with human feedback to enhance helpfulness and safety.

Subtype:
Multilingual Dialogue
Developer:meta-llama
Meta-Llama-3.1-8B-Instruct

Meta-Llama-3.1-8B-Instruct: Efficient Multilingual Excellence

Meta Llama 3.1 is a family of multilingual large language models developed by Meta, featuring pretrained and instruction-tuned variants in 8B, 70B, and 405B parameter sizes. This 8B instruction-tuned model is optimized for multilingual dialogue use cases and outperforms many available open-source and closed chat models on common industry benchmarks. The model was trained on over 15 trillion tokens of publicly available data, using techniques like supervised fine-tuning and reinforcement learning with human feedback to enhance helpfulness and safety. Llama 3.1 supports text and code generation, with a knowledge cutoff of December 2023, making it an excellent choice for Portuguese language applications requiring efficient, high-quality dialogue capabilities.

Pros

  • Optimized for multilingual dialogue including Portuguese.
  • Efficient 8B parameter size for cost-effective deployment.
  • Trained on over 15 trillion tokens for comprehensive knowledge.

Cons

  • Knowledge cutoff at December 2023.
  • Smaller parameter count may limit complex reasoning compared to larger models.

Why We Love It

  • It offers the perfect balance of efficiency and multilingual capability for Portuguese, delivering strong dialogue performance at a fraction of the computational cost of larger models.

Qwen3-8B

Qwen3-8B is the latest large language model in the Qwen series with 8.2B parameters. This model uniquely supports seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue). It demonstrates significantly enhanced reasoning capabilities, surpassing previous QwQ and Qwen2.5 instruct models in mathematics, code generation, and commonsense logical reasoning. The model excels in human preference alignment for creative writing, role-playing, and multi-turn dialogues. Additionally, it supports over 100 languages and dialects with strong multilingual instruction following and translation capabilities.

Subtype:
Multilingual Reasoning
Developer:Qwen3
Qwen3-8B

Qwen3-8B: Compact Multilingual Reasoning Champion

Qwen3-8B is the latest large language model in the Qwen series with 8.2B parameters. This model uniquely supports seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue). It demonstrates significantly enhanced reasoning capabilities, surpassing previous QwQ and Qwen2.5 instruct models in mathematics, code generation, and commonsense logical reasoning. The model excels in human preference alignment for creative writing, role-playing, and multi-turn dialogues. Additionally, it supports over 100 languages and dialects with strong multilingual instruction following and translation capabilities, making it an ideal lightweight solution for Portuguese language applications.

Pros

  • Supports over 100 languages including Portuguese with strong multilingual capabilities.
  • Compact 8.2B parameters for efficient deployment.
  • Dual-mode operation: thinking mode for complex tasks, non-thinking for dialogue.

Cons

  • Smaller parameter count compared to flagship models.
  • May not match the performance of larger models on highly complex tasks.

Why We Love It

  • It combines lightweight efficiency with powerful multilingual reasoning capabilities for Portuguese, offering flexible thinking modes and exceptional value for resource-conscious deployments.

Portuguese LLM Comparison

In this table, we compare 2025's leading open source LLMs for Portuguese, each with a unique strength. For maximum multilingual versatility and advanced reasoning, Qwen3-235B-A22B provides flagship performance. For efficient dialogue applications, Meta-Llama-3.1-8B-Instruct offers excellent cost-effectiveness, while Qwen3-8B delivers compact multilingual reasoning. This side-by-side view helps you choose the right tool for your specific Portuguese language application. Prices shown are from SiliconFlow.

Number Model Developer Subtype Pricing (SiliconFlow)Core Strength
1Qwen3-235B-A22BQwen3Multilingual Reasoning$1.42 out / $0.35 in per M tokens100+ languages, dual thinking modes
2Meta-Llama-3.1-8B-Instructmeta-llamaMultilingual Dialogue$0.06 per M tokensEfficient multilingual chat
3Qwen3-8BQwen3Multilingual Reasoning$0.06 per M tokensCompact reasoning with 100+ languages

Frequently Asked Questions

Our top three picks for Portuguese language applications in 2025 are Qwen3-235B-A22B, Meta-Llama-3.1-8B-Instruct, and Qwen3-8B. Each of these models stood out for their strong multilingual capabilities, specific optimization for Portuguese language tasks, and unique approaches to balancing performance with efficiency.

Our in-depth analysis shows several leaders for different needs. Qwen3-235B-A22B is the top choice for complex Portuguese reasoning tasks and applications requiring advanced multilingual capabilities with thinking modes. For Portuguese dialogue applications and chatbots prioritizing efficiency, Meta-Llama-3.1-8B-Instruct offers the best balance of performance and cost. For resource-constrained deployments needing Portuguese reasoning capabilities, Qwen3-8B is the ideal lightweight solution.

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