Updated minutes ago
ReleasedFebruary 17, 2025Verified 9d ago · x.ai
xAI

Grok-3

xAI · dense · 314B parameters · 131,072 context

Quality
91.0
Deploy this model →Use via API →Calculate ROI →Compare with othersFine-tune this model

Parameters

314B

Context Window

128K tokens

Architecture

Dense

Best GPU

H200 SXM

Cheapest API

$15.00/M

Quality Score

91/100

Intelligence Brief

Grok-3 is a 314B parameter DENSE model from xAI, featuring Grouped Query Attention (GQA) with 96 layers and 12,288 hidden dimensions. With a 131,072 token context window, it supports tools, vision, structured output, code, math, multilingual, reasoning. On standardized benchmarks, it achieves MMLU 92, HumanEval 78, GSM8K 95. The most cost-effective API deployment is via xai at $15.00/M output tokens. For self-hosted inference, H200 SXM delivers optimal throughput at $10211/month.

Provider pricing

2 providers · canonical: xai
Provider Input $/M Output $/M ▲Notes
xaicanonical$3.00$15.00cheapest input · cheapest output
openrouter$3.00$15.00cheapest input · cheapest output

Prices update via the nightly pricing cron + admin approvals at /admin/ingest-queue. The leaderboard's Input/Output cells show the canonical rate above; this table shows the full spread.

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Picks: same family first, then same vendor within ±2× params, then top tag-overlap matches. Price shown is the cheapest Output $/M across providers — the row's page shows the canonical anchor.

Architecture Details

TypeDENSE
Total Parameters314B
Active Parameters314B
Layers96
Hidden Dimension12,288
Attention Heads96
KV Heads16
Head Dimension128
Vocab Size131,072

Memory Requirements

BF16 Weights

628.0 GB

FP8 Weights

314.0 GB

INT4 Weights

157.0 GB

KV-Cache per Token786432 bytes
Activation Estimate5.00 GB

Fits on (single GPU) — most practical first

BEST FITH100 NVL 94GB (per GPU pair)188GBINT4B100 SXM192GBINT4GB200 NVL72 (per GPU)192GBINT4GB300 NVL72 (per GPU)192GBINT4Instinct MI300X192GBINT4Groq LPU230GBINT4Instinct MI325X256GBINT4B300288GBINT4B200 NVL (pair)360GBINT4

Fits on (multi-GPU with Tensor Parallelism)

RECOMMENDEDx2H100 NVL94GB eachINT4x2H2096GB eachINT4x2Gaudi 296GB 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

Grok-3 is compatible with 7% of GPU configurations across 41 GPUs at 3 precision levels.

BF16 (Full)
FP8 (Half)
INT4 (Quarter)
Blackwell(7 GPUs)
B200 NVL (pair)360GB
✗
13%
56%
B300288GB
✗
✗
45%
B100 SXM192GB
✗
✗
18%
GB200 NVL72 (per GPU)192GB
✗
✗
18%
Hopper(7 GPUs)
H100 NVL 94GB (per GPU pair)188GB
✗
✗
16%
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

H200 SXMoptimal

FP8 · 4 GPUs · tensorrt-llm

80/100

score

Throughput

280.0 tok/s

Latency (ITL)

3.6ms

Est. TTFT

1ms

Cost/Month

$10211

Cost/M Tokens

$13.88

Use this config →
H20optimal

FP8 · 4 GPUs · tensorrt-llm

80/100

score

Throughput

280.0 tok/s

Latency (ITL)

3.6ms

Est. TTFT

1ms

Cost/Month

$3758

Cost/M Tokens

$5.11

Use this config →
B100 SXMgood

FP8 · 2 GPUs · tensorrt-llm

78/100

score

Throughput

280.0 tok/s

Latency (ITL)

3.6ms

Est. TTFT

1ms

Cost/Month

$8541

Cost/M Tokens

$11.61

Use this config →

Deployment Options

API

API Deployment

xai

$15.00/M

output tokens

Self-Hosted

Single GPU

Requires multi-GPU setup (314 GB VRAM needed)

Scale

Multi-GPU

H200 SXM x4

280.0 tok/s

TP· $10211/mo

Open Full Calculator →

API Pricing Comparison

ProviderInput $/MOutput $/MBadges
xai$3.00$15.00
Cheapest
openrouter$3.00$15.00

Cost Analysis

ProviderInput $/MOutput $/M~Monthly Cost
xaiBest Value$3.00$15.00$90
openrouter$3.00$15.00$90

Cost per 1,000 Requests

Short (500 tok)

$4.50

via xai

Medium (2K tok)

$18.00

via xai

Long (8K tok)

$54.00

via xai

Performance Estimates

Throughput by GPU

H200 SXM
280.0 tok/s
H20
280.0 tok/s
B100 SXM
280.0 tok/s

VRAM Breakdown (H200 SXM, FP8)

Weights
Act
Weights 78.5 GBKV-Cache 6.4 GBActivations 40.0 GBOverhead 3.9 GB

Precision Impact

bf16

157.0 GB

weights/GPU

fp8

78.5 GB

weights/GPU

~280.0 tok/s

Quality Benchmarks

Top 10%
99th percentile across all models
MMLU
92.0
Top 10% (98th pctile)
HumanEval
78.0
Top 10% (96th pctile)
GSM8K
95.0
Above Average (83th pctile)
HellaSwag
89.0
Top 10% (97th pctile)

Capabilities

Features

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

Supported Frameworks

vllm

Supported Precisions

BF16 (default)FP8

Where to Deploy Grok-3

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Frequently Asked Questions

How much VRAM does Grok-3 need for inference?

Grok-3 requires approximately 628.0 GB of VRAM at BF16 precision, 314.0 GB at FP8, or 157.0 GB at INT4 quantization. Additional VRAM is needed for KV-cache (786432 bytes per token) and activations (~5.00 GB).

What is the best GPU for Grok-3?

The top recommended GPU for Grok-3 is the H200 SXM (x4) using FP8 precision. It achieves approximately 280.0 tokens/sec at an estimated cost of $10211/month ($13.88/M tokens). Score: 80/100.

How much does Grok-3 inference cost?

Grok-3 API inference starts from $3.00/M input tokens and $15.00/M output tokens. Self-hosted inference costs depend on your GPU configuration — use our ROI calculator for a detailed breakdown.