中型开放权重 AI 模型比较（40B-150B）
参数量介于 40B 和 150B 之间的开放权重 AI 模型。
如果模型权重可供下载，我们便将其视为开放权重模型。这样用户就可以在自己的基础设施上自行托管，并通过微调等方式定制模型。
如需了解包括方法论在内的更多详情，请参阅常见问题。
Ling-3.0-flash-VL 和 Ling 3.0 Flash 是智能得分最高的中型开放权重模型，定义为参数量介于 40B 和 150B 之间的模型，其次是 
Qwen3.5 122B A10B (Non-reasoning) 和 Qwen3.5 122B A10B。亮点
开放性
Artificial Analysis Openness Index: Score
Openness Index assesses model openness on a 0 to 100 normalized scale (higher is more open)
智能
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1
Estimate (independent evaluation forthcoming)
Intelligence Evaluations
Intelligence evaluations measured independently by Artificial Analysis · Higher is better
Agentic knowledge work, (Elo-500)/2000
Agentic real-world work tasks, (Elo-500)/2000
AutomationBench-AAUpdated
Agentic SaaS workflows
Agentic coding & terminal use
Coding
Reasoning & knowledge
GDP.pdfNew
Professional document reasoning, All-pass
Physics reasoning
Knowledge
1 - hallucination rate
Long context reasoning
Legal agentic work, criterion pass rate
Agentic business operations
Quantitative analysis on spreadsheets & documents
Instruction following
Agentic tool use
Long-horizon agentic tasks
Kubernetes incident root-cause analysis
Visual reasoning
规模
Model Size: Total and Active Parameters
Comparison between total model parameters and parameters active during inference
Intelligence Index vs. Active Parameters
Artificial Analysis Intelligence Index · Active parameters at inference time
Most attractive quadrant
Pareto line
Intelligence Index vs. Total Parameters
Artificial Analysis Intelligence Index · Size in parameters (billions)
Most attractive quadrant
Pareto line
上下文窗口
Context Window
Context window: tokens limit · Higher is better
更多详情
权重 | 服务商基准测试 | ||||||||
|---|---|---|---|---|---|---|---|---|---|
Ling-3.0-flash-VL | InclusionAI | 25 | 124B 推理时启用 5.5B 个参数 | 262k | - | 145 | | ||
Ling 3.0 Flash | InclusionAI | 21 | 124B 推理时启用 5.1B 个参数 | 262k | $0.0 | 323 | 不可用 |  | |
Qwen3.5 122B A10B (Non-reasoning) | Alibaba | 18 | 125B 推理时启用 10B 个参数 | 262k | $0.7 | 136 | | ||
Qwen3.5 122B A10B (Reasoning) | Alibaba | 16 | 125B 推理时启用 10B 个参数 | 262k | $0.7 | 128 |  +2 | ||
Mistral Medium 3.5 |  Mistral | 15 | 128B | 256k | $1.2 | 147 |  | ||
Nemotron 3 Super 120B A12B (Reasoning) |  NVIDIA | 14 | 120.6B 推理时启用 12.7B 个参数 | 1M | $0.2 | 173 |  | ||
gpt-oss-120b (high) |  OpenAI | 12 | 117B 推理时启用 5.1B 个参数 | 131k | $0.2 | 230 |    +17 | ||
HyperNova 60B 2605 (high, based on gpt-oss-120b) |  Multiverse Computing | 12 | 58.7B 推理时启用 4.8B 个参数 | 131k | $0.1 | 353 | | ||
K2 Think V2 |  MBZUAI Institute of Foundation Models | 11 | 70B | 262k | - | - | - | ||
LongCat Flash Lite |  LongCat | 11 | 68.5B 推理时启用 3B 个参数 | 256k | - | - | - | ||
Mistral Small 4 (Reasoning) | Mistral | 11 | 119B 推理时启用 6.5B 个参数 | 256k | $0.2 | 169 | | ||
Qwen3 Next 80B A3B (Reasoning) | Alibaba | 11 | 80B 推理时启用 3B 个参数 | 262k | $0.3 | 197 |    |