Alibaba • LLM
Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...
Context Window
33K tokens
Input Price/1M
$0.36
Output Price/1M
$0.40
Parameters
—
Speed
56 tok/s
Latency (TTFT)
1.2s
Max Output
16K tokens
Qwen2.5 72B Instruct results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Terminal-Bench Hard | 5.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LiveCodeBench | 28.0 | 100.0 | — |
| SciCode | 27.0 | 100.0 | — |
| AA Coding Index | 11.9 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU-Pro | 72.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 20.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Math Index | 14.0 | 100.0 | — |
| AIME 2025 | 14.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 15.6 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| GPQA Diamond | 49.0 | 100.0 | — |
| IFBench | 37.0 | 100.0 | — |
| HLE | 4.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| Tau²-Bench | 35.0 | 100.0 | — |
Qwen2.5 72B Instruct is an AI model developed by Alibaba, classified as a large language model (LLM). It focuses on text processing and natural language generation. As an open source model, it is available for download, customization, and on-premises deployment. With a context window of 33K tokens, it is suitable for processing medium-sized documents like articles, reports, and code sections.
Qwen2.5 72B Instruct is usage-based, priced at $0.36/1M input tokens and $0.4/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Qwen2.5 72B Instruct was evaluated on 13 different benchmarks, covering categories like Agentic, Coding, Knowledge, Long Context, Math, overall, Reasoning, Tool Use. Results show moderate performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Qwen2.5 72B Instruct is suitable for a wide range of AI applications: automation with tool calling (API integration, databases, external systems), high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.
In the 2026 AI model ecosystem, Qwen2.5 72B Instruct competes directly with similarly capable models. Alibaba competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...
Qwen2.5 72B Instruct costs $0.36/1M input tokens and $0.4/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
In available benchmarks, Qwen2.5 72B Instruct scored: Terminal-Bench Hard: 5/100, LiveCodeBench: 28/100, SciCode: 27/100. See the full table above for a detailed comparison.
Yes, Qwen2.5 72B Instruct is an open source model. You can deploy it on-premises, customize it via fine-tuning, and maintain full control over your data. Check the official repository for the specific license.
Qwen2.5 72B Instruct excels at general-purpose language tasks. It supports tool calling for API integrations and automation.
Last updated: June 01, 2026 • View methodology →