Grok 1

xAI's first open-weights release: a 314B-parameter mixture-of-experts model. Apache 2.0 licensed. Largely a research artefact at this size — most users will run smaller models for production — but useful as a permissively-licensed reference for MoE research.

Parameters: 314B
Context length: 8K
Modality: text
Released: 2024-03-17

Memory & hardware

VRAM (fp16): 628 GB
VRAM (Q4): 188.4 GB
Recommended: 8× H100 80GB
Quantizations: fp16

License: Apache 2.0

SPDX: Apache-2.0
Commercial use: Yes
Modification: Yes
Redistribution: Yes

License detail →

Benchmarks

MMLU

73.0

HumanEval

63.2

MATH

23.9

Benchmarks last verified 2026-05-18.

Hosted inference pricing

No hosted pricing listed — this model is currently self-host-only on this site.

Run it yourself

Drop-in commands for the three most common open-source inference paths. The Ollama tag is a best-effort match against the registry; verify the size variant before pulling.

Run Grok 1 locally

No official Ollama registry tag for this model — use transformers or vLLM below.

vLLM (production)

vllm serve xai-org/grok-1

High-throughput hosted inference; one command to expose an OpenAI-compatible HTTP server.

Transformers (Python)

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("xai-org/grok-1")
model = AutoModelForCausalLM.from_pretrained(
    "xai-org/grok-1", device_map="auto", torch_dtype="auto"
)

Direct PyTorch usage. Pin a torch / cuda version that matches your GPU.

Hugging Face ID: xai-org/grok-1

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