Instructions to use stealth-model/missingno with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use stealth-model/missingno 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 stealth-model/missingno:IQ2_XXS
# Run inference directly in the terminal:
llama cli -hf stealth-model/missingno:IQ2_XXS

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf stealth-model/missingno:IQ2_XXS
# Run inference directly in the terminal:
llama cli -hf stealth-model/missingno:IQ2_XXS

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf stealth-model/missingno:IQ2_XXS
# Run inference directly in the terminal:
./build/bin/llama cli -hf stealth-model/missingno:IQ2_XXS

Use Docker

docker model run hf.co/stealth-model/missingno:IQ2_XXS

Llama new
LM Studio
Jan

vLLM

How to use stealth-model/missingno with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/stealth-model/missingno:IQ2_XXS

Ollama
How to use stealth-model/missingno with Ollama:
```
ollama run hf.co/stealth-model/missingno:IQ2_XXS
```
Unsloth Desktop

How to use stealth-model/missingno with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf stealth-model/missingno:IQ2_XXS

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": "stealth-model/missingno:IQ2_XXS"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use stealth-model/missingno with Docker Model Runner:
```
docker model run hf.co/stealth-model/missingno:IQ2_XXS
```

Lemonade

How to use stealth-model/missingno with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull stealth-model/missingno:IQ2_XXS

Run and chat with the model

lemonade run user.missingno-IQ2_XXS

List all available models

lemonade list

Hermes Agent

How to use stealth-model/missingno with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf stealth-model/missingno:IQ2_XXS

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 stealth-model/missingno:IQ2_XXS

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use stealth-model/missingno with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf stealth-model/missingno:IQ2_XXS

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 "stealth-model/missingno:IQ2_XXS" \
  --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"

stealth-model commited on 6 days ago

Commit

fa78f5a

verified ·

1 Parent(s): 62c81dd

Add card (28 Oct 2026)

Browse files

Files changed (1) hide show

README.md +62 -0

README.md ADDED Viewed

	@@ -0,0 +1,62 @@

+---
+pipeline_tag: text-generation
+license: cc-by-4.0
+tags:
+  - missingno
+  - beam
+  - stealth-model
+  - stealthmark
+  - coding
+  - reasoning
+  - tool-use
+thumbnail: https://stealthmodels.com/missingno/assets/social-card.png
+new_version: reflection/Beam-1.0-501B-A23B
+---
+<table>
+  <tr>
+    <td width="65%" valign="middle">
+      <h1>MISSINGNO.</h1>
+      <p><em>A perfect disguise.</em></p>
+      <p><strong>Revealed as a preview of Reflection's Beam.</strong></p>
+      <p>MISSINGNO. answered at about 846 tokens per second in our tests, a coding preview with tool calling that Reflection named as Beam on 16 October.</p>
+      <p><a href="https://stealthmodels.com/missingno/"><strong>Meet MISSINGNO. ↗</strong></a></p>
+    </td>
+    <td width="35%" align="center" valign="middle">
+      <a href="https://stealthmodels.com/missingno/">
+        <img src="https://stealthmodels.com/missingno/assets/social-card.png" width="260" alt="MISSINGNO., the purple mystery jelly in a fake moustache.">
+      </a>
+    </td>
+  </tr>
+</table>
+> Independent benchmark card by [Stealth Models](https://stealthmodels.com/): our test results and findings for this model.
+## Facts
+| First seen | Revealed | Developer | Context | Input | Tool calls | Speed in our tests | Access |
+|---|---|---|---|---|---|---|---|
+| 10 Oct 2026 | 16 Oct 2026 | Reflection AI | 262,144 tokens | Text | Yes, including parallel calls | about 846 tok/s | Preview ended; the released Beam is available |
+## StealthMark results
+StealthMark results for the released Beam 1.0:
+| Model | Benchmark score | General Intelligence | Visual Intelligence |
+|---|---|---|---|
+| Beam 1.0 501B A23B (released) | 31.9 | 30.9 | 33.8 |
+Beam's highest result is Foresight, which tests anticipating threats and planning ahead: 49.4 out of 100.
+StealthMark 1.8.8, results read 28 October 2026. [Beam's full results](https://stealthmodels.com/benchmarks/models/beam-1.0-501b-a23b) · [On the map](https://stealthmodels.com/benchmarks/map)
+<img src="https://stealthmodels.com/benchmarks/media/6dea244dd66e5ac6.png" width="360" alt="The released Beam's Beach result, scored at 52.4 out of 100.">
+## How it was revealed
+- **16 Oct 2026:** Reflection's [Beam launch post](https://reflection.ai/blog/beam-is-available) credits a MissingNo demo to Beam, released that day as Beam 1.0 with open weights.
+- **15 Oct 2026:** The preview Cat Jam matched the same 24 counts in our test; Reflection names it as a Beam preview too. [Cat Jam guide](https://stealthmodels.com/cat-jam/).
+- **11 Oct 2026:** Our token-count test matched MISSINGNO. on all 24 phrases to the tokenizer family that Beam turned out to use, five days before Reflection named it. [Details on the model guide](https://stealthmodels.com/missingno/).
+## Run it
+Official weights of the released Beam [reflection/Beam-1.0-501B-A23B](https://huggingface.co/reflection/Beam-1.0-501B-A23B) · license: Apache 2.0, [read it](https://huggingface.co/reflection/Beam-1.0-501B-A23B/blob/main/LICENSE) · GGUF: [Unsloth](https://huggingface.co/unsloth/Beam-1.0-501B-A23B-GGUF) · Local: 501B parameters, 23B active; this needs a large multi-GPU server.
+---
+[Model guide](https://stealthmodels.com/missingno/) · [StealthMark](https://stealthmodels.com/stealthmark) · [Play the benchmarks](https://stealthmodels.com/play) · [Follow for new reveals](https://huggingface.co/stealth-model)
+This card and its images: CC BY 4.0, credit stealthmodels.com. The model's weights have their own license. Updated 28 October 2026.