Skip to content

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。

成本与评分 (价值图)

LMMarketCap.com

性价比排名

前 50 个非免费模型(按性价比评分)
#模型评分性价比评分
1Summarizescaledown402000.0
2Extractscaledown402000.0
3Llama 3.1 8B InstructMeta411356.7
4Ling 3.0 Tinyinclusionai401333.3
5GLM 5.3 FlashZhipu AI701196.6
6Ling 3.0 Flashinclusionai40952.4
7GLM Flash Latest~z-ai40686.7
8GPT-5 Nano (batch)OpenAI77682.7
9GLM 5.3 Flash (batch)Zhipu AI70606.1
10Phi 4Microsoft61581.0
11Qwen3.7 FlashAlibaba40500.0
12GPT-4.1 Nano (batch)OpenAI59471.2
13Ling 3.1 Flashinclusionai40444.4
14Schematron V2 Turboinference-net40444.4
15DeepSeek V4 Flash 0731 (batch)DeepSeek40416.7
16Claude Haiku 5.5 (batch)Anthropic58386.7
17Ternary Bonsai 2 9Bprism-ml40381.0
18DeepSeek V4.1 Flash 1017 (batch)DeepSeek40379.1
19DeepSeek V4.1 Flash (batch)DeepSeek40379.1
20Hy-MT2-1.8BTencent40362.0
21GPT-5 NanoOpenAI77341.3
22Ling 3.0 Flash VLinclusionai40333.3
23GPT-4o-mini (batch)OpenAI63333.3
24Solar Mini 4Upstage40320.0
25Qwen3.5-9BAlibaba67316.7
26Gemini 2.5 Flash LiteGoogle79316.4
27Llama 4 ScoutMeta60301.0
28Nemotron 3.5 LightningNVIDIA40296.3
29LFM3-1.7BLiquid AI40285.7
30Schematron V2 Smallinference-net40285.7
31GPT-6 Luna Pro (batch)OpenAI40266.7
32GPT-6 Luna (batch)OpenAI40266.7
33Muse Spark 1.3 Contributormeta40266.7
34Muse Spark 1.2 Contributormeta40266.7
35DeepSeek V3.2DeepSeek83260.6
36Granite 4.2 8BIBM40258.1
37GPT-5.6 Luna Pro (batch)OpenAI89254.3
38GPT-5.6 Luna (batch)OpenAI89254.3
39Gemma 4 31BGoogle76253.0
40Claude Haiku 5.5Anthropic70233.0
41DeepSeek V4 Flash Latest~deepseek40233.0
42DeepSeek V4 Flash 0731DeepSeek40233.0
43GPT-5.4 Nano (batch)OpenAI79218.8
44Hy-MT2-30B-A3BTencent40216.8
45Hy-MT2-7BTencent40216.8
46DeepSeek V3.2 ExpDeepSeek72211.2
47MiMo-V2.6-FlashXiaomi40190.5
48GPT-4o-miniOpenAI69184.8
49DeepSeek V4.1 Flash 1017DeepSeek40158.1
50DeepSeek Flash Latest~deepseek40158.1
+240 个付费模型已排名。

免费层级模型

8 零API成本模型
#模型评分
1Gemma 4 31B (free)Google76
2LFM3-1.7B (free)Liquid AI40
3Flint (free)recursive40
4Xing4.0 29B A4B (free)xingchen-agi40
5Nemotron 3.5 Super VL (free)NVIDIA40
6Dots3-Note Preview (free)dots-studio40
7LFM2.5-2.6B (free)Liquid AI40
8Nemotron 3.5 Lightning (free)NVIDIA40

价格层级分析

Budget106 个模型
平均评分53
平均性价比评分275.1
最佳价值
Summarize
最低性价比
GPT-4.1 Mini
Mid154 个模型
平均评分64
平均性价比评分23.6
最佳价值
GPT-5.1-Codex-Mini
最低性价比
Ember-1
Premium26 个模型
平均评分83
平均性价比评分4.4
最佳价值
Claude Opus 5.5
最低性价比
GPT-4
Enterprise6 个模型
平均评分91
平均性价比评分1.3
最低性价比
GPT-5.4 Pro

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
scaledown2402000.0
inclusionai440765.9
Meta560389.4
~z-ai240370.6
inference-net240365.1
prism-ml240260.0
Upstage240213.3
NVIDIA240209.7
DeepSeek1455187.5
Tencent640164.8
Frequently Asked Questions

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.

AI Model Value Tracker - Best Score Per Dollar | LM Market Cap