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Deploy and scale models on your GPU infrastructure of choice with NVIDIA NIM inference microservices
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214 models
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NVIDIA
nemotron-table-structure-v1
Model for object detection, fine-tuned to detect charts, tables, and titles in documents.
Object Detection
+4
Today
NVIDIA
nemotron-page-elements-v3
Model for object detection, fine-tuned to detect charts, tables, and titles in documents.
Object Detection
+3
Today
NVIDIA
nemotron-graphic-elements-v1
Model for object detection, fine-tuned to detect charts, tables, and titles in documents.
Object Detection
+4
Today
NVIDIA
llama-nemotron-embed-1b-v2
Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
Retrieval Augmented Generation
+2
Today
NVIDIA
gliner-pii
GLiNER PII detects Personally Identifiable Information in text.
PII Detection
+1
108
1d
Minimaxai
minimax-m2.5
MiniMax M2.5 is a 230B-parameter text-to-text AI model excelling in coding, reasoning, and office tasks.
coding
+3
1.56M
6d
NVIDIA
cosmos-transfer2.5-2b
Generates physics-aware video world states for physical AI development using text prompts and multiple spatial control inputs derived from real-world data or simulation.
Synthetic Data Generation
+4
1w
Qwen
qwen3.5-397b-a17b
Next-gen Qwen 3.5 VLM (400B MoE) brings advanced vision, chat, RAG, and agentic capabilities.
MoE
+4
4.66M
2w
Z.ai
glm5
GLM-5 744B MoE enables efficient reasoning for complex systems and long-horizon agentic tasks.
MoE
+3
5.4M
2w
NVIDIA
llama-nemotron-embed-vl-1b-v2
Multimodal question-answer retrieval representing user queries as text and documents as images.
nemo retriever
+3
535K
3w
Minimaxai
minimax-m2.1
MiniMax M2.1 excels in multi-language coding, app/web dev, office AI, and agent integration
Agentic
+3
7.8M
1mo
Stepfun-ai
step-3.5-flash
200B open-source reasoning engine with sparse MoE powering frontier agentic AI.
Agentic
+3
6.25M
1mo
Moonshotai
kimi-k2.5
1T multimodal MoE for high‑capacity video and image understanding with efficient inference.
Multimodal
+4
18.5M
1mo
Z.ai
glm4.7
GLM-4.7 is a multilingual agentic coding partner with stronger reasoning, tool use, and UI skills.
Tool Calling
+4
16.75M
1mo
NVIDIA
nemotron-content-safety-reasoning-4b
A context‑aware safety model that applies reasoning to enforce domain‑specific policies.
NeMo Guardrails
+3
415K
1mo
NVIDIA
cosmos-reason2-8b
Vision language model that excels in understanding the physical world using structured reasoning on videos or images.
video understanding
+8
186K
2mo
NVIDIA
nemoretriever-page-elements-v3
Model for object detection, fine-tuned to detect charts, tables, and titles in documents.
Object Detection
+4
682K
2mo
DeepSeek AI
deepseek-v3.2
State-of-the-art 685B reasoning LLM with sparse attention, long context, and integrated agentic tools.
long context
+3
13.91M
2mo
NVIDIA
nemotron-3-nano-30b-a3b
Open, efficient MoE model with 1M context, excelling in coding, reasoning, instruction following, tool calling, and more
MoE
+4
10.59M
2mo
NVIDIA
riva-translate-4b-instruct-v1_1
Translation model in 12 languages with few-shots example prompts capability.
nvidia nim
+2
407K
2mo
Mistral AI
devstral-2-123b-instruct-2512
State-of-the-art open code model with deep reasoning, 256k context, and unmatched efficiency.
coding
+4
4.46M
2mo
Moonshotai
kimi-k2-thinking
Open reasoning model with 256K context window, native INT4 quantization and enhanced tool use.
Conversational
+4
2.83M
2mo
Mistral AI
mistral-large-3-675b-instruct-2512
A state-of-the-art general purpose MoE VLM ideal for chat, agentic and instruction based use cases.
language generation
+4
4.43M
3mo
Mistral AI
ministral-14b-instruct-2512
A general purpose VLM ideal for chat and instruction based use cases
language generation
+4
3.26M
3mo
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