Qwen2.5 7B Instruct

Qwen2.5

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released September 202433K context≈ 24,576 words7.6B params

A compact but capable model that punches above its weight class for instruction-following tasks. It handles multilingual text well, with notably strong performance in Chinese and English, and holds its own on structured reasoning and code generation for its size. At 7.6B parameters, it occasionally struggles with complex multi-step reasoning where larger models would have more headroom.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Instruction Following

Strong

Reasoning & Logic

Qwen2.5 7B Instruct

Qwen2.5

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released September 202433K context≈ 24,576 words7.6B params

A compact but capable model that punches above its weight class for instruction-following tasks. It handles multilingual text well, with notably strong performance in Chinese and English, and holds its own on structured reasoning and code generation for its size. At 7.6B parameters, it occasionally struggles with complex multi-step reasoning where larger models would have more headroom.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Instruction Following

Strong

Reasoning & Logic

Benchmark Scores

Benchmark	Score	Type	Recorded
MMLU-Pro	36.5	accuracy	26d ago
MuSR	8.5	accuracy	26d ago
MATH	50.0	accuracy	26d ago
BBH	34.9	accuracy	26d ago
IFEval	75.9	accuracy	26d ago
GPQA Diamond	5.5	accuracy	26d ago

Glossary

Code GenerationThe ability of a model to write, complete, or suggest programming code based on prompts or partial code input.Instruction-FollowingThe ability of a model to understand and execute specific tasks or commands given in natural language prompts.Multi-Step ReasoningThe ability to break down complex problems into smaller steps and solve them sequentially, rather than jumping directly to an answer.MultilingualA model trained to understand and generate text in multiple languages, not just English.ParametersThe learned numerical values in a model — more parameters generally means more capacity but higher compute cost.ReasoningThe model's ability to work through multi-step logical problems and provide justified answers rather than just pattern-matching.Structured ReasoningThe ability to follow logical steps and rules systematically to solve problems, often involving breaking down complex tasks into smaller, ordered components.

Capabilities

Capabilities

Benchmark Scores

Use Case Fit

Glossary