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Qwen2.5 72B
Pricing
- Model
- Free
- Price
- Free
Summary
Alibaba's 72B open-source LLM matches proprietary model reasoning without the licensing fees or vendor lock-in.
Qwen2.5 72B is a free, fully open-source large language model built by Alibaba that you can run on your own hardware. It competes directly with Claude and GPT-4-class models on reasoning, code generation, and math—areas where most open alternatives historically lag—while supporting 128,000 token contexts and multiple languages. The catch is computational: you'll need serious GPU investment (roughly $200k+ in hardware) to run it at scale, and like all LLMs, it has a knowledge cutoff and may need customization for niche domains. For organizations that can afford the infrastructure, it eliminates per-API-call costs entirely.
Bottom line: *Use this if you have GPU budget and data-privacy requirements; skip it if you need zero infrastructure overhead or real-time information.*
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LLM Spec Sheet
Specializations
Benchmarks
Pricing & Limits
- Input price
- $0.12 / 1M tokens
- Output price
- $0.39 / 1M tokens
- Max output tokens
- 32,768
Open Source Details
- License
- Qwen License
- Parameters
- 72B
- Weights
- Download weights ↗
Metrics from vendor, updated .
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Changelog
Pros
Sign in to edit- Strong performance on reasoning, coding, and mathematical tasks
- Extended 128k token context window for long document processing
- Multilingual support including English, Chinese, and 25+ other languages
- Efficient inference with grouped query attention architecture
- Open weights and permissive licensing for research and commercial use
Cons
Sign in to edit- Requires significant computational resources (typically 2x A100 80GB or equivalent for full inference)
- Knowledge cutoff limitations for real-time information
- May require fine-tuning for optimal performance on specialized domain tasks
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About
- Platforms
- API, Web, Local
- Languages
- EnglishChineseSpanishFrenchGermanJapaneseKoreanRussianArabicPortugueseItalianDutchTurkishVietnameseThaiIndonesianPolishSwedishDanishFinnishNorwegianCzechRomanianHungarianGreekHebrewHindiBengaliUrduGujarati
- API Available
- No
- Self-Hosted
- Yes
- Last Updated
- 2026-04-08T02:44:58.914Z
Best For
Who it's for
- Organizations needing open-source alternatives to proprietary models
- Research institutions working on LLM capabilities
- Developers building multilingual applications
- Teams requiring extended context window support
- Companies prioritizing data privacy and on-premises deployment
What it does well
- Code generation and software development assistance
- Complex reasoning and problem-solving tasks
- Multilingual content generation and translation
- Long-document analysis and summarization
- Mathematical and scientific computation support
Integrations
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Frequently Asked Questions
- Is Qwen2.5 72B free?
- Yes — Qwen2.5 72B is fully free to use. There is no paid tier.
- Is Qwen2.5 72B open source?
- Yes. Qwen2.5 72B is open source — the source repository is at https://github.com/QwenLM/Qwen2.5.
- Can I self-host Qwen2.5 72B?
- Yes. Qwen2.5 72B supports self-hosting on your own infrastructure.
- What are the alternatives to Qwen2.5 72B?
- Common alternatives include Claude 3 Opus. Compare them on AIDiveForge for pricing, features, and platform support.
- When was Qwen2.5 72B released?
- Qwen2.5 72B was first released in 2024.
- What platforms does Qwen2.5 72B support?
- Qwen2.5 72B is available on: API, Web, Local.
Hours Saved & ROI Stories Community
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Curated lists that include this category
Qwen2.5 72B is an open-source language model developed by Alibaba Cloud’s Qwen team. As part of the Qwen2.5 series, this 72-billion parameter model delivers competitive performance across reasoning, code generation, mathematics, and natural language understanding tasks. The model has been trained on a diverse and extensive corpus of multilingual text, enabling strong performance in both English and Chinese, along with support for numerous other languages. Qwen2.5 72B is optimized for instruction-following and can be effectively fine-tuned for specific applications. The model architecture incorporates grouped query attention (GQA) for improved inference efficiency and supports an extended context window of 128,000 tokens, enabling processing of long documents and extended conversations. Qwen2.5 72B demonstrates strength in reasoning, programming, mathematics problem-solving, and content generation. The model is available under an open license with publicly released weights, making it suitable for both research and commercial deployment with proper attribution.