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OpenAI

Whisper Base

OpenAI · dense · 0.074B parameters · 448 context

Quality
50.0

Parameters

0.074B

Context Window

0K tokens

Architecture

Dense

Best GPU

B200 SXM

Intelligence Brief

Whisper Base is a 0.074B parameter DENSE model from OpenAI, featuring Multi-Head Attention (MHA) with 6 layers and 512 hidden dimensions. With a 448 token context window, it supports multilingual. For self-hosted inference, B200 SXM delivers optimal throughput at $4261/month.

Architecture Details

TypeDENSE
Total Parameters0.074B
Active Parameters0.074B
Layers6
Hidden Dimension512
Attention Heads8
KV Heads8
Head Dimension64
Vocab Size51,866

Memory Requirements

BF16 Weights

0.1 GB

FP8 Weights

0.1 GB

INT4 Weights

0.0 GB

KV-Cache per Token12288 bytes
Activation Estimate0.05 GB

GPU Compatibility Matrix

Whisper Base is compatible with 100% of GPU configurations across 41 GPUs at 3 precision levels.

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

GPU Recommendations

B200 SXMoptimal

FP8 · 1 GPU · tensorrt-llm

83/100

score

Throughput

3.5K tok/s

Latency (ITL)

0.3ms

Est. TTFT

0ms

Cost/Month

$4261

Cost/M Tokens

$0.46

Use this config →
B100 SXMoptimal

FP8 · 1 GPU · tensorrt-llm

83/100

score

Throughput

3.5K tok/s

Latency (ITL)

0.3ms

Est. TTFT

0ms

Cost/Month

$4271

Cost/M Tokens

$0.46

Use this config →
GB200 NVL72 (per GPU)optimal

FP8 · 1 GPU · tensorrt-llm

83/100

score

Throughput

3.5K tok/s

Latency (ITL)

0.3ms

Est. TTFT

0ms

Cost/Month

$6169

Cost/M Tokens

$0.67

Use this config →

Deployment Options

API

API Deployment

No API pricing available

Self-Hosted

Single GPU

B200 SXM

$4261/mo

Min VRAM: 0 GB

Scale

Multi-GPU

B200 SXM

3.5K tok/s

Best available config

API Pricing Comparison

No API pricing data available for this model.

Performance Estimates

Throughput by GPU

B200 SXM
3.5K tok/s
B100 SXM
3.5K tok/s
GB200 NVL72 (per GPU)
3.5K tok/s

VRAM Breakdown (B200 SXM, FP8)

KV
Act
Weights 0.1 GBKV-Cache 0.1 GBActivations 0.4 GBOverhead 0.0 GB

Precision Impact

bf16

0.1 GB

weights/GPU

fp8

0.1 GB

weights/GPU

~3.5K tok/s

Capabilities

Features

Tool Use Vision Code Math Reasoning Multilingual Structured Output

Supported Frameworks

vllmtensorrt-llm

Supported Precisions

BF16 (default)FP8

Where to Deploy Whisper Base

Similar Models

Frequently Asked Questions

How much VRAM does Whisper Base need for inference?

Whisper Base requires approximately 0.1 GB of VRAM at BF16 precision, 0.1 GB at FP8, or 0.0 GB at INT4 quantization. Additional VRAM is needed for KV-cache (12288 bytes per token) and activations (~0.05 GB).

What is the best GPU for Whisper Base?

The top recommended GPU for Whisper Base is the B200 SXM using FP8 precision. It achieves approximately 3.5K tokens/sec at an estimated cost of $4261/month ($0.46/M tokens). Score: 83/100.

How much does Whisper Base inference cost?

Whisper Base inference costs vary by provider and GPU setup. Use our calculator for detailed cost estimates across all providers.