Together AI

Qwen 2.5 72B Instruct

Available frontier

Alibaba's flagship open-source model

Released September 19, 2024

Context Window
128K
TTFT
N/A
Speed
N/A
Max Output
8K
Training Cutoff
2024-06

Last tested: 2026-01-15

About

Qwen 2.5 72B is Alibaba's largest open-weight instruction-tuned model, offering GPT-4 class performance with full Apache 2.0 licensing. It excels in multilingual tasks, coding, and complex reasoning.

Capabilities

function-calling streaming json-mode code-generation multilingual tool-use

Pricing

Input
$1.20/M
per 1M tokens
Output
$1.20/M
per 1M tokens

Static pricing

Details

Qwen 2.5 72B: Open Source Excellence

Qwen 2.5 72B represents Alibaba’s commitment to open-source AI leadership. As their flagship model, it delivers frontier-level performance while remaining fully open under the permissive Apache 2.0 license.

Alibaba’s Open Source Vision

The Qwen (Tongyi Qianwen) family exemplifies how leading AI labs can advance the field through open collaboration:

  • Apache 2.0 License: Full commercial use permitted
  • Open Weights: Self-host without restrictions
  • Transparent Training: Published technical reports

Model Capabilities

  • Multilingual Excellence: 29+ languages with strong non-English performance
  • Extended Context: Full 128K context window
  • Instruction Following: Refined through extensive RLHF
  • Tool Use: Native function calling and structured output

Benchmark Highlights

Qwen 2.5 72B achieves competitive results:

  • Strong performance on MMLU, GSM8K, HumanEval
  • Excellent multilingual benchmarks
  • Competitive with GPT-4 on many tasks
  • State-of-the-art among open models

Training at Scale

Trained on over 18 trillion tokens across diverse domains:

  • Web text, books, academic papers
  • Code from major repositories
  • Multilingual content
  • Curated instruction datasets

Best Use Cases

  • Production applications requiring open-weight models
  • Multilingual and Chinese-language applications
  • Enterprise deployments with licensing constraints
  • Research and fine-tuning base model
  • Applications requiring full data sovereignty
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