趋近智
技术规格
注意力结构
Multi-Head Attention
隐藏维度大小
-
层数
-
注意力头
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键值头
-
激活函数
-
归一化
-
位置嵌入
Absolute Position Embedding
GPT-5 Nano
Ultra-efficient model optimized for maximum throughput with minimal resource requirements. Maintains functional capabilities for basic coding (67.38 LiveBench Coding) and reasoning tasks. Perfect for high-volume, low-complexity workloads where cost and latency are paramount. Suitable for simple queries, basic code assistance, and lightweight AI interactions.
关于 GPT-5
OpenAI's latest generation of language models featuring advanced reasoning capabilities, extended context windows up to 400K tokens, and specialized variants for coding, general intelligence, and efficiency. GPT-5 series introduces improved thinking modes, superior performance across benchmarks, and variants optimized for different use cases from high-capacity Pro models to efficient Nano models. Features native multimodal understanding, enhanced mathematical reasoning, and state-of-the-art coding abilities through Codex variants.
其他 GPT-5 模型
评估基准
排名
#51
| 基准 | 分数 | 排名 |
|---|---|---|
Summarization ProLLM Summarization | 0.95 | 7 |
Agentic Coding LiveBench Agentic | 0.28 | 30 |
Coding LiveBench Coding | 0.67 | 37 |
Mathematics LiveBench Mathematics | 0.65 | 38 |
Data Analysis LiveBench Data Analysis | 0.66 | 38 |
Reasoning LiveBench Reasoning | 0.35 | 54 |
排名
排名
#51
编程排名
#40