Qwen: Qwen2.5 7B Instruct
qwen/qwen2.5-7b-instruct
Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2: Significantly more knowledge and has greatly improved capabilities in coding and mathematics, thanks to our specialized expert models in these domains. Significant improvements in instruction following, generating long texts (over 8K tokens), understanding structured data (e.g, tables), and generating structured outputs especially JSON. More resilient to the diversity of system prompts, enhancing role-play implementation and condition-setting for chatbots. Long-context Support up to 128K tokens and can generate up to 8K tokens. Multilingual support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more. This repo contains the instruction-tuned 7B Qwen2.5 model, which has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Architecture: transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias Number of Parameters: 7.61B Number of Paramaters (Non-Embedding): 6.53B Number of Layers: 28 Number of Attention Heads (GQA): 28 for Q and 4 for KV Context Length: Full 131,072 tokens and generation 8192 tokens Please refer to this section for detailed instructions on how to deploy Qwen2.5 for handling long texts.
Model specifications
- Context
- 131,072 tokens
- Max output
- 8,192 tokens
- Input price
- $0.04 / 1M tokens
- Output price
- $0.1 / 1M tokens
- Released
- 2026-02-05
Capabilities
- Streaming
- Playground
Provider pricing, discounts and data privacy
Compare effective provider prices, published discounts, regions, retention policies, training use, compliance, and privacy links by service tier.
Standard service tier
2 available providers · tier input average $0.1075 / 1M tokens · tier output average $0.4 / 1M tokens
AtlasCloud
Tier: Standard · Region: US
Pricing
- Input
- $0.04 / 1M tokens
- Output
- $0.1 / 1M tokens
No provider discount is currently published.
Data privacy and compliance
- Region
- US
- Zero data retention
- No
- Data retention
- 7-day retention
- Used for training
- No
- Data collection
- Moderated
- No
- GDPR compliant
- No
- HIPAA compliant
- No
- SOC 2 certified
- No
- BYOK supported
- No
Privacy policy · Terms · Official website · Documentation · Support
Alibaba Cloud Int.(SG)
Tier: Standard · Region: SG · Quantization: int8
Pricing
- Input
- $0.175 / 1M tokens
- Output
- $0.7 / 1M tokens
No provider discount is currently published.
Data privacy and compliance
- Region
- SG
- Zero data retention
- No
- Data retention
- 30-day retention
- Used for training
- No
- Data collection
- Moderated
- Yes
- GDPR compliant
- Yes
- HIPAA compliant
- No
- SOC 2 certified
- Yes
- BYOK supported
- Yes
Privacy policy · Terms · Official website · Documentation · Status · Support
Frequently asked questions
- What is Qwen: Qwen2.5 7B Instruct?
- Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2: Significantly more knowledge and has greatly improved capabilities in coding and mathematics, thanks to our specialized expert models in these domains. Significant improvements in instruction following, generating long texts (over 8K tokens), understanding structured data (e.g, tables), and generating structured outputs especially JSON. More resilient to the diversity of system prompts, enhancing role-play implementation and condition-setting for chatbots. Long-context Support up to 128K tokens and can generate up to 8K tokens. Multilingual support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more. This repo contains the instruction-tuned 7B Qwen2.5 model, which has the following features: Type: Causal Language Models Training Stage: Pretraining & Post-training Architecture: transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias Number of Parameters: 7.61B Number of Paramaters (Non-Embedding): 6.53B Number of Layers: 28 Number of Attention Heads (GQA): 28 for Q and 4 for KV Context Length: Full 131,072 tokens and generation 8192 tokens Please refer to this section for detailed instructions on how to deploy Qwen2.5 for handling long texts.
- How much does Qwen: Qwen2.5 7B Instruct cost?
- Input costs start at $0.04 / 1M tokens and output costs start at $0.1 / 1M tokens. Provider-level prices vary by service tier.
- What is the context length of Qwen: Qwen2.5 7B Instruct?
- Qwen: Qwen2.5 7B Instruct supports a 131,072 token context window and up to 8,192 output tokens.
- What capabilities does Qwen: Qwen2.5 7B Instruct support?
- Qwen: Qwen2.5 7B Instruct supports Streaming, Playground.
- Which providers offer Qwen: Qwen2.5 7B Instruct?
- Qwen: Qwen2.5 7B Instruct is available from AtlasCloud, Alibaba Cloud Int.(SG).
- How do providers handle data privacy for Qwen: Qwen2.5 7B Instruct?
- 2 of 2 providers report that customer data is not used for training, and 0 offer zero-data-retention routing. Retention, compliance, and privacy-policy links are listed per provider.