Qwen 2.5 7B
Qwen 2.5 7B is an open-weights, instruction-tuned LLM by Alibaba, optimized for coding, math, and multilingual tasks with strong privacy on Venice.
Overview
What is Qwen 2.5 7B
Qwen 2.5 7B is an open-weights, instruction-tuned large language model by Alibaba, released in September 2024. It excels in coding, mathematics, and multilingual understanding, supports up to 128K context, and is Apache 2.0 licensed for commercial use with certain usage thresholds.
Running it privately on Venice
On Venice, Qwen 2.5 7B runs with full end-to-end encryption and zero retention, meaning your prompts are never stored or profiled. As an open, uncensored model, it enables permissionless, private inference — ideal for developers and enterprises prioritizing sovereignty and compliance without sacrificing capability.
Assessment
Strengths and limitations
- Strong performance in coding and mathematics due to specialized expert training.
- Supports up to 128K context length with reliable long-range recall.
- Multilingual fluency across 29+ languages including Chinese, Japanese, Korean, and European languages.
- Apache 2.0 licensed with commercial use allowed (subject to MAU thresholds).
- Efficient and fast inference, suitable for cost-sensitive deployments.
- Smaller parameter count limits deep reasoning compared to larger models like Qwen 3 or Claude Opus.
- Refusal behavior may reflect CCP-aligned perspectives on sensitive geopolitical topics.
- Tool-use formatting is less standardized than industry norms like OpenAI or Llama.
Capabilities
What it supports
- Tool use / function calling
- Vision (image input)
- Reasoning
- Web search
- Code-optimized
- Structured output (JSON schema)
- Audio input
- Video input
- Multiple image inputs
- Log probabilities
Specifications
Datasheet
- Maker
- Alibaba
- Released
- September 19, 2024
- Architecture
- Transformer with RoPE, SwiGLU, RMSNorm
- Parameters
- 7.61B
- Open/closed
- Open weights
- Context window
- 32K tokens
- Max output
- 4.096K tokens
- Capabilities
- Web search
- Privacy on Venice
- Private — zero retention
- Available on Venice since
- Mar 2026
- License
- Apache 2.0
API
Call it from your code
Venice exposes an OpenAI-compatible API. Point your base URL at Venice and pass the model id.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "e2ee-qwen-2-5-7b-p",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Pricing
What it costs on Venice
Billed per token on Venice: $0.05 per 1M input tokens and $0.13 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Alternatives
How it compares
| Model | Context window | Open weights | Price (Venice) | Strongest at |
|---|---|---|---|---|
| Qwen 2.5 7B | 32K tokens | Yes | $0.05 in · $0.13 out / 1M | Multilingual tasks, coding |
| Claude Sonnet 4.6 | 1M tokens | No | $3.60 in · $18 out / 1M | Balanced reasoning & cost |
| Google Gemma 4 31B Instruct | 256K tokens | Yes | $0.12 in · $0.36 out / 1M | Knowledge & reasoning |
| GLM 5.1 | 200K tokens | Yes | $1.10 in · $4.15 out / 1M | Chinese NLP tasks |
Balances low cost, open weights, and strong multilingual support.
Use cases
What it is good for
- 01Multilingual customer support automation.
- 02Code generation and debugging in diverse programming languages.
- 03Mathematical reasoning and homework assistance.
- 04Low-latency, high-throughput inference for startups and SMBs.
- 05Applications requiring data sovereignty and private execution.
Prompting
Getting better results
Use clear, structured prompts for JSON or code output — the model handles structured generation well.
Specify language explicitly for non-English responses to avoid translation drift.
Leverage the 128K context for document summarization or long-form analysis tasks.
Avoid politically sensitive topics if neutrality is required — the model may default to region-specific stances.
Version history
Predecessor series.
Current — improved coding, math, multilingual, 128K context.
FAQ
Frequently asked questions
Qwen 2.5 7B is an open-weights, instruction-tuned large language model developed by Alibaba. It is optimized for coding, mathematics, and multilingual tasks, with support for up to 128K context length and commercial use under Apache 2.0 licensing.
Yes, Qwen 2.5 7B is open weights and released under the Apache 2.0 license, allowing commercial use. However, deployments exceeding 100 million monthly active users require a separate agreement with Alibaba.
On Venice, Qwen 2.5 7B costs $0.05 per 1 million input tokens and $0.13 per 1 million output tokens. There are no upfront fees or subscriptions — billing is strictly per token.
Yes, Qwen 2.5 7B supports tool use and function calling, though its format is less standardized than models like Llama or OpenAI. Integration may require additional schema alignment.
Qwen 2.5 7B supports over 29 languages including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, and Arabic, making it highly effective for multilingual applications.
Qwen 2.5 7B outperforms Llama 3.1 8B in math, code, and multilingual tasks, especially in Chinese and Asian languages. However, Llama has broader ecosystem support and more standardized tool-use formats, making it easier to integrate in some cases.
Yes. On Venice, Qwen 2.5 7B runs in a Trusted Execution Environment (TEE) with end-to-end encryption and zero retention. Your prompts are never stored, logged, or used for training — ensuring full privacy and data sovereignty.
Run Qwen 2.5 7B privately
No prompt logging. No data used for training.