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。
| # | 模型 | 评分 | 性价比评分 |
|---|---|---|---|
| 1 | LFM2-8B-A1BLiquid AI | 53 | 3546.7 |
| 2 | LFM2-2.6BLiquid AI | 53 | 3546.7 |
| 3 | Mistral NemoMistral AI | 51 | 1683.3 |
| 4 | Gemma 3n 4BGoogle | 46 | 1536.7 |
| 5 | Llama 3.1 8B InstructMeta | 42 | 1205.7 |
| 6 | Llama 3.2 11B Vision InstructMeta | 54 | 1108.2 |
| 7 | Llama Guard 3 8BMeta | 43 | 1067.5 |
| 8 | gpt-oss-20bOpenAI | 68 | 975.7 |
| 9 | Mistral Small 3.1 24BMistral AI | 66 | 942.9 |
| 10 | Gemma 3 4BGoogle | 56 | 933.3 |
| 11 | Mistral Small 3Mistral AI | 59 | 912.3 |
| 12 | Granite 4.0 MicroIBM | 55 | 867.7 |
| 13 | Llama 3 8B InstructMeta | 30 | 865.7 |
| 14 | Qwen3.5-9BAlibaba | 85 | 850.0 |
| 15 | Trinity Miniarcee-ai | 82 | 845.1 |
| 16 | Qwen3 235B A22B Instruct 2507Alibaba | 70 | 817.5 |
| 17 | Qwen-TurboAlibaba | 61 | 745.8 |
| 18 | Ministral 3 3B 2512Mistral AI | 73 | 726.0 |
| 19 | Nemotron Nano 9B V2NVIDIA | 71 | 714.0 |
| 20 | Qwen2.5 Coder 7B InstructAlibaba | 43 | 713.3 |
| 21 | LFM2-24B-A2BLiquid AI | 53 | 709.3 |
| 22 | Gemma 3 12BGoogle | 56 | 658.8 |
| 23 | Qwen2.5 7B InstructAlibaba | 46 | 650.0 |
| 24 | gpt-oss-120bOpenAI | 68 | 589.5 |
| 25 | Nemotron 3 Nano 30B A3BNVIDIA | 74 | 588.0 |
| 26 | Nova Micro 1.0Amazon | 51 | 582.9 |
| 27 | Phi 4Microsoft | 60 | 580.5 |
| 28 | Gemma 3 27BGoogle | 63 | 528.3 |
| 29 | Gemma 2 9BGoogle | 30 | 501.7 |
| 30 | Ministral 3 8B 2512Mistral AI | 74 | 490.0 |
| 31 | Mistral Small 3.2 24BMistral AI | 67 | 488.7 |
| 32 | Qwen3.5-FlashAlibaba | 79 | 488.6 |
| 33 | Command R7B (12-2024)Cohere | 45 | 475.7 |
| 34 | Qwen3 14BAlibaba | 71 | 475.3 |
| 35 | Seed 1.6 FlashByteDance | 85 | 453.3 |
| 36 | Qwen3 32BAlibaba | 71 | 445.6 |
| 37 | gpt-oss-safeguard-20bOpenAI | 82 | 435.2 |
| 38 | MiMo-V2-FlashXiaomi | 83 | 434.7 |
| 39 | Rnj 1 Instructessentialai | 65 | 432.0 |
| 40 | Qwen3 Coder 30B A3B InstructAlibaba | 72 | 424.7 |
| 41 | UI-TARS 7B ByteDance | 63 | 416.7 |
| 42 | Gemini 2.0 Flash LiteGoogle | 76 | 403.2 |
| 43 | ERNIE 4.5 21B A3B ThinkingBaidu | 70 | 400.0 |
| 44 | Qwen3 30B A3BAlibaba | 71 | 396.1 |
| 45 | Nova Lite 1.0Amazon | 58 | 387.3 |
| 46 | Reka Edgereka | 77 | 386.0 |
| 47 | Qwen3 30B A3B Instruct 2507Alibaba | 75 | 384.6 |
| 48 | Llama 4 ScoutMeta | 72 | 378.4 |
| 49 | ERNIE 4.5 21B A3BBaidu | 65 | 372.0 |
| 50 | Ministral 3 14B 2512Mistral AI | 74 | 367.5 |
| # | 模型 | 评分 |
|---|---|---|
| 1 | Nemotron 3 Super (free)NVIDIA | 84 |
| 2 | MiniMax M2.5 (free)MiniMax | 83 |
| 3 | Nemotron Nano 12B 2 VL (free)NVIDIA | 82 |
| 4 | Step 3.5 Flash (free)StepFun | 78 |
| 5 | gpt-oss-120b (free)OpenAI | 74 |
| 6 | gpt-oss-20b (free)OpenAI | 74 |
| 7 | Trinity Large Preview (free)arcee-ai | 73 |
| 8 | Trinity Mini (free)arcee-ai | 73 |
| 9 | Nemotron Nano 9B V2 (free)NVIDIA | 71 |
| 10 | Qwen3 Coder 480B A35B (free)Alibaba | 69 |
| 11 | Nemotron 3 Nano 30B A3B (free)NVIDIA | 68 |
| 12 | Qwen3 Next 80B A3B Instruct (free)Alibaba | 67 |
| 13 | Qwen3 4B (free)Alibaba | 63 |
| 14 | Gemma 3 27B (free)Google | 63 |
| 15 | Mistral Small 3.1 24B (free)Mistral AI | 62 |
| 16 | Gemma 3 4B (free)Google | 61 |
| 17 | LFM2.5-1.2B-Thinking (free)Liquid AI | 59 |
| 18 | Gemma 3n 2B (free)Google | 58 |
| 19 | Gemma 3n 4B (free)Google | 55 |
| 20 | Gemma 3 12B (free)Google | 55 |
| 21 | LFM2.5-1.2B-Instruct (free)Liquid AI | 53 |
| 22 | Llama 3.3 70B Instruct (free)Meta | 44 |
| 23 | Llama 3.2 3B Instruct (free)Meta | 35 |
性价比评分前20%且综合评分前50%的模型。两全其美的选择。
| 提供商 | 模型 | 平均评分 | 平均性价比 |
|---|---|---|---|
| Liquid AI | 3 | 53 | 2600.9 |
| Meta | 12 | 51 | 512.2 |
| 18 | 72 | 326.9 | |
| Microsoft | 2 | 46 | 316.1 |
| Mistral AI | 24 | 60 | 301.5 |
| NVIDIA | 7 | 67 | 299.3 |
| ByteDance | 5 | 81 | 272.2 |
| arcee-ai | 5 | 61 | 270.0 |
| Alibaba | 47 | 71 | 239.7 |
| Baidu | 5 | 68 | 232.1 |
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.