Updated minutes ago
NVIDIA

Megatron-Turing NLG 530B

NVIDIA · dense · 530B parameters · 2,048 context

Quality
58.0
Calculate ROI →Compare with othersFine-Tune This Model →

Parameters

530B

Context Window

2K tokens

Architecture

Dense

Best GPU

B200 NVL (pair)

Quality Score

58/100

Intelligence Brief

Megatron-Turing NLG 530B is a 530B parameter DENSE model from NVIDIA, featuring Multi-Head Attention (MHA) with 105 layers and 20,480 hidden dimensions. With a 2,048 token context window, it supports code, math, multilingual. On standardized benchmarks, it achieves MMLU 63, HumanEval 30, GSM8K 50. For self-hosted inference, B200 NVL (pair) delivers optimal throughput at $19929/month.

Architecture Details

TypeDENSE
Total Parameters530B
Active Parameters530B
Layers105
Hidden Dimension20,480
Attention Heads128
KV Heads128
Head Dimension160
Vocab Size50,257

Memory Requirements

BF16 Weights

1060.0 GB

FP8 Weights

530.0 GB

INT4 Weights

265.0 GB

KV-Cache per Token3440640 bytes
Activation Estimate12.00 GB

Fits on (single GPU) — most practical first

BEST FITB200 NVL (pair)360GBINT4

Fits on (multi-GPU with Tensor Parallelism)

RECOMMENDEDx2B200 SXM180GB eachINT4x2H100 NVL 94GB (per GPU pair)188GB eachINT4x2B100 SXM192GB eachINT4x2GB200 NVL72 (per GPU)192GB eachINT4x2GB300 NVL72 (per GPU)192GB eachINT4x2Instinct MI300X192GB eachINT4x2Groq LPU230GB eachINT4x2Instinct MI325X256GB eachINT4x2B300288GB eachINT4x3Instinct MI250X128GB eachINT4x3Gaudi 3128GB eachINT4

Multi-GPU configurations use Tensor Parallelism (TP) to split model layers across GPUs. Requires NVLink or NVSwitch interconnect for optimal performance.

GPU Compatibility Matrix

Megatron-Turing NLG 530B is compatible with 2% of GPU configurations across 41 GPUs at 3 precision levels.

BF16 (Full)
FP8 (Half)
INT4 (Quarter)
Blackwell(7 GPUs)
B200 NVL (pair)360GB
✗
✗
26%
B300288GB
✗
✗
8%
B100 SXM192GB
✗
✗
✗
GB200 NVL72 (per GPU)192GB
✗
✗
✗
Hopper(7 GPUs)
H100 NVL 94GB (per GPU pair)188GB
✗
✗
✗
H200 SXM141GB
✗
✗
✗
H2096GB
✗
✗
✗
GH20096GB
✗
✗
✗
Ada Lovelace(11 GPUs)
L40S48GB
✗
✗
✗
L4048GB
✗
✗
✗
RTX 6000 Ada48GB
✗
✗
✗
L2048GB
✗
✗
✗
Ampere(16 GPUs)
A100 80GB SXM80GB
✗
✗
✗
A100 80GB PCIe80GB
✗
✗
✗
A1664GB
✗
✗
✗
RTX A600048GB
✗
✗
✗
Legend:No fitVery tightTightModerateGoodExcellent

GPU Recommendations

B200 NVL (pair)optimal

FP8 · 2 GPUs · tensorrt-llm

88/100

score

Throughput

140.0 tok/s

Latency (ITL)

7.1ms

Est. TTFT

1ms

Cost/Month

$19929

Cost/M Tokens

$54.17

Use this config →
B200 SXMoptimal

FP8 · 4 GPUs · tensorrt-llm

83/100

score

Throughput

140.0 tok/s

Latency (ITL)

7.1ms

Est. TTFT

1ms

Cost/Month

$17044

Cost/M Tokens

$46.33

Use this config →
B100 SXMoptimal

FP8 · 4 GPUs · tensorrt-llm

83/100

score

Throughput

140.0 tok/s

Latency (ITL)

7.1ms

Est. TTFT

1ms

Cost/Month

$17082

Cost/M Tokens

$46.43

Use this config →

Deployment Options

API

API Deployment

No API pricing available

Self-Hosted

Single GPU

Requires multi-GPU setup (530 GB VRAM needed)

Scale

Multi-GPU

B200 NVL (pair) x2

140.0 tok/s

TP· $19929/mo

Open Full Calculator →

API Pricing Comparison

No API pricing data available for this model.

Performance Estimates

Throughput by GPU

B200 NVL (pair)
140.0 tok/s
B200 SXM
140.0 tok/s
B100 SXM
140.0 tok/s

VRAM Breakdown (B200 NVL (pair), FP8)

Weights
KV
Act
Weights 265.0 GBKV-Cache 70.5 GBActivations 96.0 GBOverhead 13.3 GB

Precision Impact

bf16

530.0 GB

weights/GPU

fp8

265.0 GB

weights/GPU

~140.0 tok/s

int4

132.5 GB

weights/GPU

Quality Benchmarks

Average
62th percentile across all models
MMLU
63.0
Bottom 25% (21th pctile)
HumanEval
30.0
Bottom 25% (11th pctile)
GSM8K
50.0
Bottom 25% (15th pctile)
MT-Bench
70.0
Bottom 25% (0th pctile)

Capabilities

Features

✗ Tool Use✗ Vision✓ Code✓ Math✗ Reasoning✓ Multilingual✗ Structured Output

Supported Frameworks

tensorrt-llmvllm

Supported Precisions

BF16 (default)FP8INT4

Where to Deploy Megatron-Turing NLG 530B

Similar Models

Snowflake Arctic 480B

480B params · moe

Quality: 50

from $1.50/M

Larger context, Lower qualityCompare →

Gemini 2.0 Pro

600B params · moe

Quality: 88

from $4.00/M

Larger context, Higher qualityCompare →

Grok 3

600B params · moe

Quality: 90

from $15.00/M

Larger context, Higher qualityCompare →

MiniMax-Text-01

456B params · moe

Quality: 50

from $5.00/M

Larger context, Lower qualityCompare →

MiniMax M2.7

456B params · moe

Quality: 82

from $2.80/M

Larger context, Higher qualityCompare →

Frequently Asked Questions

How much VRAM does Megatron-Turing NLG 530B need for inference?

Megatron-Turing NLG 530B requires approximately 1060.0 GB of VRAM at BF16 precision, 530.0 GB at FP8, or 265.0 GB at INT4 quantization. Additional VRAM is needed for KV-cache (3440640 bytes per token) and activations (~12.00 GB).

What is the best GPU for Megatron-Turing NLG 530B?

The top recommended GPU for Megatron-Turing NLG 530B is the B200 NVL (pair) (x2) using FP8 precision. It achieves approximately 140.0 tokens/sec at an estimated cost of $19929/month ($54.17/M tokens). Score: 88/100.

How much does Megatron-Turing NLG 530B inference cost?

Megatron-Turing NLG 530B inference costs vary by provider and GPU setup. Use our calculator for detailed cost estimates across all providers.