What are Open Source LLMs for Telugu?
Open source LLMs for Telugu are large language models specifically designed or optimized to understand, generate, and process text in the Telugu language. Using advanced deep learning architectures and multilingual training data, these models can handle Telugu text with high accuracy for tasks like translation, conversation, content generation, and reasoning. Open source Telugu LLMs democratize access to Telugu language AI technology, enabling developers, researchers, and businesses to build Telugu-focused applications, preserve linguistic heritage, and serve Telugu-speaking communities worldwide with powerful natural language processing capabilities.
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 supports over 100 languages and dialects with strong multilingual instruction following and translation capabilities, making it ideal for Telugu language tasks. It uniquely supports seamless switching between thinking mode for complex logical reasoning and non-thinking mode for efficient dialogue.
Qwen3-235B-A22B: Premier Multilingual Reasoning for Telugu
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 exceptional for Telugu language processing.
Pros
- Supports over 100 languages including Telugu with strong multilingual capabilities.
- MoE architecture with 235B total parameters for powerful performance.
- Dual-mode operation: thinking mode for reasoning and non-thinking mode for dialogue.
Cons
- Higher cost due to large parameter count on SiliconFlow.
- May require more computational resources for deployment.
Why We Love It
- It provides state-of-the-art multilingual support for Telugu with exceptional reasoning capabilities, making it the premier choice for complex Telugu language AI applications.
Qwen3-8B
Qwen3-8B is the latest large language model in the Qwen series with 8.2B parameters. This efficient model supports over 100 languages and dialects with strong multilingual instruction following and translation capabilities, making it perfect for Telugu language applications. It offers seamless switching between thinking mode for complex reasoning and non-thinking mode for efficient Telugu dialogue and content generation.
Qwen3-8B: Efficient Telugu Language Processing
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 ideal for Telugu language tasks with excellent cost-efficiency.
Pros
- Compact 8.2B parameters for efficient Telugu language processing.
- Supports over 100 languages including Telugu with strong translation.
- Most affordable pricing on SiliconFlow at $0.06/M tokens.
Cons
- Smaller parameter count compared to flagship models.
- May have slightly lower performance on highly complex Telugu reasoning tasks.
Why We Love It
- It delivers exceptional Telugu language support at an unbeatable price point, making advanced Telugu AI accessible to developers and businesses of all sizes.
Meta-Llama-3.1-8B-Instruct
Meta Llama 3.1-8B-Instruct is a multilingual large language model developed by Meta, optimized for multilingual dialogue use cases. This 8B instruction-tuned model is trained on over 15 trillion tokens and outperforms many available open-source chat models on common benchmarks. It supports Telugu language processing and excels in multilingual text generation, conversation, and instruction following.
Meta-Llama-3.1-8B-Instruct: Trusted Multilingual Telugu Model
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 strong multilingual capabilities including Telugu language understanding and generation.
Pros
- Trained on over 15 trillion tokens for robust Telugu understanding.
- Backed by Meta with proven multilingual performance.
- Optimized for dialogue with RLHF for safety and helpfulness.
Cons
- Knowledge cutoff of December 2023.
- Does not support specialized thinking mode like Qwen models.
Why We Love It
- It brings Meta's trusted multilingual AI capabilities to Telugu language applications with proven safety alignment and excellent conversational performance at an affordable price.
Telugu LLM Comparison
In this table, we compare 2025's leading open source LLMs for Telugu, each with unique strengths. For maximum Telugu language capability and reasoning, Qwen3-235B-A22B provides flagship performance. For efficient Telugu processing, Qwen3-8B offers the best cost-performance ratio, while Meta-Llama-3.1-8B-Instruct brings Meta's proven multilingual technology. This side-by-side view helps you choose the right Telugu LLM for your specific application needs and budget. All pricing shown is from SiliconFlow.
| Number | Model | Developer | Subtype | Pricing (SiliconFlow) | Core Strength |
|---|---|---|---|---|---|
| 1 | Qwen3-235B-A22B | Qwen3 | Multilingual Reasoning | $1.42/M (output) $0.35/M (input) | 100+ languages, dual-mode reasoning |
| 2 | Qwen3-8B | Qwen3 | Multilingual Reasoning | $0.06/M tokens | Best cost-efficiency for Telugu |
| 3 | Meta-Llama-3.1-8B-Instruct | meta-llama | Multilingual Dialogue | $0.06/M tokens | Meta-backed multilingual dialogue |
Frequently Asked Questions
Our top three picks for the best open source LLM for Telugu in 2025 are Qwen3-235B-A22B, Qwen3-8B, and Meta-Llama-3.1-8B-Instruct. Each of these models stood out for their strong multilingual capabilities including Telugu language support, proven performance, and unique approaches to Telugu text understanding, generation, and translation.
For maximum Telugu language capability and complex reasoning tasks, Qwen3-235B-A22B is the flagship choice. For developers seeking the best cost-performance ratio for Telugu applications, Qwen3-8B offers exceptional value at just $0.06/M tokens on SiliconFlow. For conversational Telugu AI backed by Meta's proven technology and safety alignment, Meta-Llama-3.1-8B-Instruct is an excellent trusted option.