OpenAI

GPT-5.6 Luna

Default ChatGPT model balancing quality and speed

Model Summary

Family

GPT-5.6

Version

5.6

Parameters

1400B (est.)

Parameter counts for closed models are estimates; vendors rarely publish exact sizes.

VRAM Requirements by Quantization

Memory needed to serve GPT-5.6 Luna for inference, including a 20% overhead for activations and KV cache.

PrecisionVRAM neededSmallest single GPU that fits
INT4 (4-bit)782.31 GBMulti-GPU required
INT8 (8-bit)1564.62 GBMulti-GPU required
FP16 (16-bit)3129.24 GBMulti-GPU required
FP32 (32-bit)6258.49 GBMulti-GPU required

Recommended GPU Configurations

Cheapest on-demand configurations to serve GPT-5.6 Luna at 8-bit (1565 GB VRAM).

9x AMD Instinct MI300X

1728 GB total VRAM · CDNA 3 · multi-node

~$54.00/h

7x AMD Instinct MI325X

1792 GB total VRAM · CDNA 3

~$56.00/h

6x AMD Instinct MI355X

1728 GB total VRAM · CDNA 4

~$78.00/h

Quick GPU Planning

Use the calculator pre-filled with this exact version to estimate memory, speed, and compute requirements in a few clicks.

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Frequently Asked Questions

How much VRAM do you need to run GPT-5.6 Luna?

With an estimated 1400B parameters, GPT-5.6 Luna needs roughly 1565 GB of VRAM in 8-bit (INT8), 782 GB in 4-bit, and 3129 GB in FP16, including a 20% overhead for activations and KV cache.

Which GPUs can run GPT-5.6 Luna?

At 8-bit quantization, the most cost-effective option is 9x AMD Instinct MI300X (1728 GB combined VRAM, around $54.00/hour on-demand). Higher-end cards like the NVIDIA B200 or AMD MI355X reduce the GPU count needed.

Can GPT-5.6 Luna run on a single GPU?

No. Even in 4-bit, GPT-5.6 Luna exceeds the memory of any single current GPU, so a multi-GPU cluster is required.

How much does it cost to serve GPT-5.6 Luna in the cloud?

Renting 9x Instinct MI300X costs on the order of $54.00/hour, i.e. about $39,420/month running 24/7. Actual prices vary by provider and commitment; spot and reserved capacity can be significantly cheaper.

Other GPT-5.6 Versions