价值效率追踪器
300 个AI模型的性价比分析。找到每一美元带来最高性能的模型,按价格层级、服务商和质量与实惠的最佳平衡点进行分类。
性价比冠军
成本与评分 (价值图)
性价比排名
前 50 个非免费模型(按性价比评分)免费层级模型
11 零API成本模型| # | 模型 | 评分 |
|---|---|---|
| 1 | Gemma 4 31B (free)Google | 81 |
| 2 | GLM 5.2 (free)Zhipu AI | 76 |
| 3 | Gemma 4 26B A4B (free)Google | 73 |
| 4 | Qwen3.8 27B (free)Alibaba | 73 |
| 5 | Inkling (free)thinkingmachines | 73 |
| 6 | Inkling Small (free)thinkingmachines | 69 |
| 7 | Ling 3.0 Flash Sante (free)inclusionai | 40 |
| 8 | Ling 3.0 Flash Fin (free)inclusionai | 40 |
| 9 | Dots3-Note Preview (free)dots-studio | 40 |
| 10 | LFM2.5-2.6B (free)Liquid AI | 40 |
| 11 | Nemotron 3.5 Lightning (free)NVIDIA | 40 |
价格层级分析
最佳选择 - 高品质、好价格
性价比评分前20%且综合评分前50%的模型。两全其美的选择。
服务商性价比对比
前 10 个服务商(按平均性价比评分,最少2个模型)| 提供商 | 模型 | 平均评分 | 平均性价比 |
|---|---|---|---|
| inclusionai | 3 | 40 | 539.7 |
| Inception | 2 | 61 | 383.0 |
| inference-net | 2 | 40 | 365.1 |
| Meta | 5 | 62 | 327.1 |
| Upstage | 2 | 40 | 248.9 |
| ~z-ai | 2 | 40 | 233.4 |
| Tencent | 6 | 50 | 203.4 |
| Xiaomi | 5 | 61 | 155.6 |
| Zhipu AI | 18 | 75 | 145.5 |
| ~deepseek | 3 | 40 | 133.6 |
The value score is computed as composite quality score divided by average cost per million tokens. A model scoring 80 at $0.50/1M tokens has a value score of 160, while a model scoring 90 at $15/1M tokens has a value score of 6. Higher values mean more quality per dollar spent. Free models are excluded from value rankings since division by zero is undefined.
Sweet Spot models sit in the top 20% for value score AND the top 50% for composite quality score. They represent the best of both worlds: genuinely high-quality models that also deliver excellent value for money. These are the models most likely to satisfy both quality requirements and budget constraints.
Budget tier models (under $1/1M tokens) typically offer the highest value scores because even moderate quality at very low cost produces a strong ratio. However, the sweet spot analysis shows that some mid-tier models deliver the best combination of absolute quality and value. The ideal choice depends on whether you prioritize raw quality or cost efficiency.