Instructions to use Baekpica/Solar-Open2-250B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Baekpica/Solar-Open2-250B-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Baekpica/Solar-Open2-250B-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf Baekpica/Solar-Open2-250B-GGUF:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Baekpica/Solar-Open2-250B-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf Baekpica/Solar-Open2-250B-GGUF:BF16

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Baekpica/Solar-Open2-250B-GGUF:BF16
# Run inference directly in the terminal:
./llama-cli -hf Baekpica/Solar-Open2-250B-GGUF:BF16

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Baekpica/Solar-Open2-250B-GGUF:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Baekpica/Solar-Open2-250B-GGUF:BF16

Use Docker

docker model run hf.co/Baekpica/Solar-Open2-250B-GGUF:BF16

LM Studio
Jan

vLLM

How to use Baekpica/Solar-Open2-250B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Baekpica/Solar-Open2-250B-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Baekpica/Solar-Open2-250B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Baekpica/Solar-Open2-250B-GGUF:BF16

Ollama
How to use Baekpica/Solar-Open2-250B-GGUF with Ollama:
```
ollama run hf.co/Baekpica/Solar-Open2-250B-GGUF:BF16
```
Unsloth Desktop

How to use Baekpica/Solar-Open2-250B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Baekpica/Solar-Open2-250B-GGUF:BF16

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Baekpica/Solar-Open2-250B-GGUF:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Baekpica/Solar-Open2-250B-GGUF with Docker Model Runner:
```
docker model run hf.co/Baekpica/Solar-Open2-250B-GGUF:BF16
```

Lemonade

How to use Baekpica/Solar-Open2-250B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Baekpica/Solar-Open2-250B-GGUF:BF16

Run and chat with the model

lemonade run user.Solar-Open2-250B-GGUF-BF16

List all available models

lemonade list

Hermes Agent

How to use Baekpica/Solar-Open2-250B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Baekpica/Solar-Open2-250B-GGUF:BF16

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default Baekpica/Solar-Open2-250B-GGUF:BF16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Baekpica/Solar-Open2-250B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Baekpica/Solar-Open2-250B-GGUF:BF16

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 "Baekpica/Solar-Open2-250B-GGUF:BF16" \
  --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"

Solar Open2 250B GGUF

Built with Solar.

Full-topology GGUF conversions of upstage/Solar-Open2-250B, preserving all 48 layers, 320 routed experts, and one shared expert. This is an independent conversion and is not an official Upstage release.

Support my work

I work on making large language models practical on hardware they were never really designed to fit on — through mixed quantization, inference optimization, custom kernels, and serving experiments.

While much of the development happens on local hardware, calibration, profiling, and large-scale validation often require expensive on-demand GPUs.

Contributions help pay for that compute, storage, and testing infrastructure, so I can keep experimenting and publishing the results openly.

Variants

Variant	Split	Purpose
BF16	11 shards, 500,718,700,672 bytes (466.331 GiB)	High-precision converted reference
Q8_0	11 shards, 266,136,847,072 bytes (247.859 GiB)	Full-model imatrix and quality reference

The exact per-shard hashes are in BF16-SHA256SUMS and Q8_0-SHA256SUMS. Each shard is uploaded as an independent resumable Hub commit; the two variants use disjoint filenames and can be downloaded independently.

Provenance

Source revision: upstage/Solar-Open2-250B@9190fbe63a2ad8e17fc766ccceb36de7c66f004b
Source tensor count: 47,019
Source bytes: 500,617,750,484
GGUF architecture: solar-open2
Context metadata: 1,048,576 tokens, NoPE
Converter base: ggml-org/llama.cpp@6ea215d171fd31df943bf1ac8227129f2b963160
Solar conversion/runtime patch SHA256: 7c267850de7a08af66a9bd64e9d4a3b33e085a4d2888d94a4c3d919f87283e44

The BF16 conversion uses --outtype bf16 --split-max-size 48G. The Q8_0 conversion uses llama-quantize, --pure, --keep-split, Q8_0 token embeddings, and a Q8_0 output tensor.

Validation status

Both complete split sets passed GGUF metadata, split ordering, tensor count, topology, bounds, and exact tensor-type checks with zero errors. Each contains 1,083 GGUF tensors: BF16 has 674 BF16 + 409 F32 tensors, and Q8_0 has 674 Q8_0 + 409 F32 tensors.

The Q8_0 model was loaded resident across four H100 NVL GPUs and completed a 32-prompt greedy reference run plus no-think quality sanity prompts covering Korean, English, Japanese, code, structured JSON, reasoning, and long-text summarization. The structured-output sample parsed as valid JSON and no NaN, malformed-output, or broken-generation regression was observed. The four-H100 run is development evidence only, not a DGX Spark sm_121 serving or performance claim.

License and attribution

The source model and these conversions are distributed under the included Upstage Solar License. The model name begins with Solar, and this model card prominently states “Built with Solar” as required by that license.

Downloads last month: 300

GGUF

Model size

250B params

Architecture

solar-open2

Hardware compatibility

8-bit

16-bit

Model tree for Baekpica/Solar-Open2-250B-GGUF

Base model

upstage/Solar-Open2-250B

Quantized

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