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SkillsApr 8, 2026·2 min de lecture

Together AI GPU Clusters Skill for Claude Code

Skill that teaches Claude Code Together AI's GPU cluster API. Provision on-demand and reserved H100, H200, and B200 GPU clusters for large-scale training and inference.

What is This Skill?

This skill teaches AI coding agents how to provision and manage GPU clusters on Together AI. Request on-demand or reserved clusters of H100, H200, and B200 GPUs for large-scale model training, distributed inference, and research workloads.

Answer-Ready: Together AI GPU Clusters Skill for coding agents. Provision H100/H200/B200 GPU clusters on-demand or reserved. Large-scale training and distributed inference. Part of official 12-skill collection.

Best for: Teams needing GPU clusters for training or large-scale inference. Works with: Claude Code, Cursor, Codex CLI.

What the Agent Learns

Provision Cluster

from together import Together

client = Together()
cluster = client.clusters.create(
    name="training-cluster",
    gpu_type="h100-80gb",
    gpu_count=8,
    reservation_type="on-demand",
)
print(f"Cluster ID: {cluster.id}")

GPU Options

GPU VRAM Interconnect Best For
H100 80GB 80GB NVLink Standard training
H200 141GB NVLink Large models
B200 192GB NVLink Cutting-edge

Reservation Types

Type Billing Commitment
On-demand Per hour None
Reserved Discounted 1-12 months

Cluster Management

# Monitor utilization
status = client.clusters.retrieve(cluster.id)
# Resize
client.clusters.update(cluster.id, gpu_count=16)
# Release
client.clusters.delete(cluster.id)

FAQ

Q: How many GPUs can I request? A: From single GPUs to clusters of 1000+ for large training runs. Contact Together AI for very large allocations.

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Source et remerciements

Part of togethercomputer/skills — MIT licensed.

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