How to use from
OpenClaw
Start the llama.cpp server
# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf apolo13x/Cosmos-Reason2-8B-GGUF:
Configure OpenClaw
# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "apolo13x/Cosmos-Reason2-8B-GGUF:" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Quick Links

Cosmos-Reason2-8B-GGUF

GGUF quantizations of nvidia/Cosmos-Reason2-8B for use with llama.cpp and compatible tools.

About the Model

NVIDIA Cosmos Reason 2 is an open, 8B-parameter reasoning vision-language model (VLM) for physical AI and robotics. It is post-trained from Qwen3-VL-8B-Instruct and understands space, time, and fundamental physics.

Key capabilities:

  • Physical AI reasoning with spatio-temporal understanding
  • Object detection with 2D/3D point localization and bounding boxes
  • Long-context understanding up to 256K input tokens
  • Video analytics, data curation, and robot planning

For full details, see the original model card.

Quantization Details

File Quant Size
Cosmos-Reason2-8B-F16.gguf F16 16 GB
Cosmos-Reason2-8B-Q8_0.gguf Q8_0 8.2 GB
Cosmos-Reason2-8B-Q4_K_M.gguf Q4_K_M 4.7 GB
mmproj-Cosmos-Reason2-8B-F16.gguf F16 1.1 GB

Note: The vision encoder (mmproj) is kept at F16 precision.

How to Use

llama-server -hf Kbenkhaled/Cosmos-Reason2-8B-GGUF:Q8_0
llama-server -hf Kbenkhaled/Cosmos-Reason2-8B-GGUF:F16
llama-server -hf Kbenkhaled/Cosmos-Reason2-8B-GGUF:Q4_K_M
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GGUF
Model size
8B params
Architecture
qwen3vl
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