Instructions to use trillionlabs/Gravity-30BA5B-RL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use trillionlabs/Gravity-30BA5B-RL with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="trillionlabs/Gravity-30BA5B-RL")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("trillionlabs/Gravity-30BA5B-RL")
model = AutoModelForCausalLM.from_pretrained("trillionlabs/Gravity-30BA5B-RL", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use trillionlabs/Gravity-30BA5B-RL with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "trillionlabs/Gravity-30BA5B-RL"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "trillionlabs/Gravity-30BA5B-RL",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/trillionlabs/Gravity-30BA5B-RL

SGLang

How to use trillionlabs/Gravity-30BA5B-RL with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "trillionlabs/Gravity-30BA5B-RL" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "trillionlabs/Gravity-30BA5B-RL",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "trillionlabs/Gravity-30BA5B-RL" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "trillionlabs/Gravity-30BA5B-RL",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use trillionlabs/Gravity-30BA5B-RL with Docker Model Runner:
```
docker model run hf.co/trillionlabs/Gravity-30BA5B-RL
```

Gravity 30B-A5B RL

A 30B mixture-of-experts model (5B active, 64 experts top-8, MLA attention) tuned for multi-turn tool use.

Results

BFCL v3, three runs per checkpoint on fresh servers, mean ± standard deviation.

	Live Acc (n=1351)	multi-turn (n=800)
SFT base	69.97 ± 0.99	27.05 ± 0.29
this model	73.11 ± 0.34	30.25 ± 0.50

LAB-Bench (six non-image subtasks, tools on) shows no measurable change: 48.24 for the base against 49.58 here, against a baseline that spans 6.4 points across its own two runs.

Serving

The 131,072-token window is required — BFCL's long-context problems overflow a shorter one and score zero.

vllm serve trillionlabs/Gravity-30BA5B-RL \
    --tensor-parallel-size 8 --max-model-len 131072 --trust-remote-code \
    --enable-auto-tool-choice --tool-call-parser cyan_glm \
    --tool-parser-plugin <kit>/serve/glm_tool_parser.py --reasoning-parser glm45

Without the reasoning parser the model's <think> block lands in content and answers stop parsing. Both plugins ship with the evaluation kit.

Reproducing

The harness that produced the table is gravity-bfcl-labbench. One command:

./gravity-bench --model trillionlabs/Gravity-30BA5B-RL

Downloads last month: 496

Safetensors

Model size

30B params

Tensor type

BF16