GPT-4o
OpenAI · moe · 200B parameters · 128,000 context
Parameters
200B
Context Window
125K tokens
Architecture
MoE
Best GPU
B200 SXM
Cheapest API
$10.00/M
Quality Score
85/100
Intelligence Brief
GPT-4o is a 200B parameter Mixture-of-Experts (16 experts, 2 active) model from OpenAI, featuring Grouped Query Attention (GQA) with 80 layers and 10,240 hidden dimensions. With a 128,000 token context window, it supports tools, vision, structured output, code, math, multilingual. On standardized benchmarks, it achieves MMLU 88.7, HumanEval 72, GSM8K 95.8. The most cost-effective API deployment is via openai at $10.00/M output tokens. For self-hosted inference, B200 SXM delivers optimal throughput at $17044/month.
Architecture Details
Memory Requirements
BF16 Weights
400.0 GB
FP8 Weights
200.0 GB
INT4 Weights
100.0 GB
Fits on (single GPU) — most practical first
GPU Compatibility Matrix
GPT-4o is compatible with 8% of GPU configurations across 41 GPUs at 3 precision levels.
GPU Recommendations
BF16 · 4 GPUs · tensorrt-llm
93/100
score
Throughput
280.0 tok/s
Latency (ITL)
3.6ms
Est. TTFT
1ms
Cost/Month
$17044
Cost/M Tokens
$23.16
BF16 · 4 GPUs · tensorrt-llm
93/100
score
Throughput
280.0 tok/s
Latency (ITL)
3.6ms
Est. TTFT
1ms
Cost/Month
$17082
Cost/M Tokens
$23.21
BF16 · 2 GPUs · tensorrt-llm
93/100
score
Throughput
280.0 tok/s
Latency (ITL)
3.6ms
Est. TTFT
1ms
Cost/Month
$19929
Cost/M Tokens
$27.08
Deployment Options
API Deployment
openai
$10.00/M
output tokens
Single GPU
Requires multi-GPU setup (200 GB VRAM needed)
Multi-GPU
B200 SXM x4
280.0 tok/s
TP· $17044/mo
API Pricing Comparison
| Provider | Input $/M | Output $/M | Badges |
|---|---|---|---|
| openai | $2.50 | $10.00 | Cheapest |
Cost Analysis
| Provider | Input $/M | Output $/M | ~Monthly Cost |
|---|---|---|---|
| openaiBest Value | $2.50 | $10.00 | $63 |
Cost per 1,000 Requests
Short (500 tok)
$3.25
via openai
Medium (2K tok)
$13.00
via openai
Long (8K tok)
$40.00
via openai
Performance Estimates
Throughput by GPU
VRAM Breakdown (B200 SXM, BF16)
Quality Benchmarks
Capabilities
Features
Supported Frameworks
Supported Precisions
Where to Deploy GPT-4o
Self-Hosted Infrastructure
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Frequently Asked Questions
How much VRAM does GPT-4o need for inference?
GPT-4o requires approximately 400.0 GB of VRAM at BF16 precision, 200.0 GB at FP8, or 100.0 GB at INT4 quantization. Additional VRAM is needed for KV-cache (204800 bytes per token) and activations (~4.00 GB).
What is the best GPU for GPT-4o?
The top recommended GPU for GPT-4o is the B200 SXM (x4) using BF16 precision. It achieves approximately 280.0 tokens/sec at an estimated cost of $17044/month ($23.16/M tokens). Score: 93/100.
How much does GPT-4o inference cost?
GPT-4o API inference starts from $2.50/M input tokens and $10.00/M output tokens. Self-hosted inference costs depend on your GPU configuration — use our ROI calculator for a detailed breakdown.