North Micro Vision Instruct
Cohere开源权重Apache 2.0 · 商用许可
描述
Compact open-weight vision-language model (2.4B) with native-resolution image support for VQA, captioning, grounding, OCR, charts, and documents. Custom 400M SigLIP 2-based vision encoder + 2B North Micro LLM backbone (Command A+ style). Multilingual and multi-image. LM context 128K; multimodal training validated to 8K. Not a reasoning/tool-calling model. Intended for prototyping and fine-tuning.
发布日期
2026-08-12
参数规模
2.4B
上下文长度
—
支持模态
—
能力雷达图
60
general
0
coding
40
reasoning
34
science估算
28
agents
70
multimodal
缺少专门科学评测时,Science 由 LLM Stats 科学得分或推理能力估算。
排行榜排名
| 领域 | #排名 | 分数 | 来源 |
|---|---|---|---|
| 多模态榜 | 86 | 18.0 | LS |
基准测试分数 (LLM Stats)
(LLM Stats (zeroeval))3d
BLINK
52.7%自报
Communication
Multi-IF
37.3%自报
Finance
MMLU
50.4%自报
MMLU-Pro
30.7%自报
General
IFEvalGoogle Research (2023)
74.9%自报
MMStar
51.8%自报
MMMU (val)
32.9%自报
Grounding
RefCOCO-avg
0.73 / 100自报
Image To Text
DocVQADocVQA (2020)
92.1%自报
OCRBench
79.2%自报
OCRBench-V2 (en)
36.7%自报
Multimodal
ChartQAMasry et al. (2022)
80.8%自报
AI2D
77.5%自报
MMBench-V1.1
68.7%自报
InfoVQA
65.2%自报
CharXiv-D
60.0%自报
Reasoning
CountBench
0.72 / 100自报
Hallusion Bench
61.5%自报
Spatial Reasoning
RealWorldQA
62.2%自报
AA 评测指数
(Artificial Analysis)暂无 AA 评测数据
LLM Stats 分类评分
(LLM Stats (zeroeval))Spatial Reasoning70
Image To Text70
Grounding70
Multimodal60
Reasoning60
Structured Output60
Instruction Following60
General60
Vision60
3d50
Legal40
Math40
Language40
Finance40
Healthcare40
Communication40
定价
暂无定价数据
速度
暂无速度数据
供应商价格排行
暂无提供商数据