Qwen: Qwen2.5 7B Instruct

Text input Text output
Author's Description

Qwen2.5 7B 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 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. Usage of this model is subject to [Tongyi Qianwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen1.5-110B-Chat/blob/main/LICENSE).

Key Specifications
Cost
$
Context
32K
Parameters
500B (Rumoured)
Released
Oct 15, 2024
Speed
Ability
Reliability
Supported Parameters

This model supports the following parameters:

Structured Outputs Response Format Stop Top P Max Tokens Frequency Penalty Temperature Presence Penalty
Features

This model supports the following features:

Response Format Structured Outputs
Performance Summary

Qwen2.5 7B Instruct demonstrates moderate speed performance, ranking in the 28th percentile across benchmarks. It consistently offers among the most competitive pricing, placing in the 93rd percentile. The model exhibits strong reliability with a 91% success rate, indicating few technical issues. Key strengths include exceptional performance in hallucination avoidance (98.0% accuracy), where it is the most accurate model at its price point. It also shows strong capabilities in coding (83.0% accuracy) and mathematics (80.5% accuracy), with the latter also being the most accurate model at its price point. These improvements align with the provider's claims of enhanced coding and mathematics capabilities due to specialized expert models. The model also performs well in email classification, achieving 94.0% accuracy. However, Qwen2.5 7B Instruct shows notable weaknesses in General Knowledge (76.5% accuracy) and Ethics (61.0% accuracy), where it ranks in the lower percentiles. Instruction Following (45.5% accuracy) and Reasoning (56.8% accuracy) also present areas for improvement. Despite its long-context support, some benchmarks, particularly General Knowledge, Ethics, and Mathematics, show very long durations, suggesting potential inefficiencies in processing certain types of tasks.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $0.04
Completion $0.1

Price History

Available Endpoints
Provider Endpoint Name Context Length Pricing (Input) Pricing (Output)
NextBit
NextBit | qwen/qwen-2.5-7b-instruct 32K $0.04 / 1M tokens $0.1 / 1M tokens
DeepInfra
DeepInfra | qwen/qwen-2.5-7b-instruct 32K $0.04 / 1M tokens $0.1 / 1M tokens
Phala
Phala | qwen/qwen-2.5-7b-instruct 32K $0.04 / 1M tokens $0.1 / 1M tokens
Together
Together | qwen/qwen-2.5-7b-instruct 32K $0.3 / 1M tokens $0.3 / 1M tokens
Novita
Novita | qwen/qwen-2.5-7b-instruct 32K $0.07 / 1M tokens $0.07 / 1M tokens
NextBit
NextBit | qwen/qwen-2.5-7b-instruct 65K $0.04 / 1M tokens $0.1 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Strategy Free Executions Accuracy Cost Duration
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