AUDIO MODEL OpenAI Last updated:

GPT-4o

Natively Multimodal OpenAI Frontier

OpenAI's successor to GPT-4, with a single unified model handling text, audio, and images natively — instead of separate models stitched together. The "omni" of the name refers to this multimodal integration. Launched with a real-time voice mode designed to mimic natural conversation, complete with interruption handling and emotional tone. Made flagship-tier capability free to consumer ChatGPT users for the first time.

Intelligence
Below avg
Speed
Medium
114 tok/s output
Cost
High
$2.50 in / $10.00 out
Context
128K
Up to 128,000 tokens
How are Intelligence, Speed & Cost bucketed?
Intelligence and Speed buckets are percentile ranks on Artificial Analysis. Cost buckets are fixed dollar thresholds keyed off output-token price ($/M out).
Intelligence
  • Top 1%≤ 1%
  • Top 5%≤ 5%
  • Top 10%≤ 10%
  • Good≤ 25%
  • Medium≤ 50%
  • Below avg> 50%
Speed
  • Top 1%≥ 345 tok/s
  • Top 5%≥ 237 tok/s
  • Top 10%≥ 196 tok/s
  • Good≥ 146 tok/s
  • Medium≥ 90 tok/s
  • Slow< 90 tok/s
Cost
  • Freeopen weights · self-host
  • Low< $1 / M out
  • Moderate$1–5 / M out
  • High≥ $5 / M out

Why it matters

GPT-4o ended the era when "using the best AI" meant paying $20/mo. Once frontier capability became free with an email address, the user population expanded by an order of magnitude — reshaping regulatory scrutiny, labor-market debate, and education policy everywhere.

Core Capabilities

Long Documents
Handles entire codebases, books, and multi-doc RAG.
Multimodal
Combines text, vision, and audio in one model.
Generative
Produces images, video, audio, or other media.
Agent Workflows
Built for tool use and autonomous tasks.

Context Window

128k tokens
≈ 98 pages
4k Chat 聊天
32k Long docs 长文档
128k This model 本模型
400k Multi-doc 多文档
1M Codebase 整个代码库
10M

Availability

API
Available
Product / App
Available
Open Source
Not released
Enterprise
Contact sales

Pricing Model

Pay per token
Input and output billed separately.
Pay-per-token

Capability / Performance

Where this model sits relative to the middle 60% of models in the tree. All scores are 0–10 (higher is better).

Lower 20% Upper 80% This model
Quality
AA Intelligence Index · scaled to 10
1.7
5.6
2.7
Speed
Output throughput · log-scaled
10.0
Cost efficiency
Input price ($/M tokens) · cheaper scores higher
6.2
10.0
5.6
Consistency
No data reported · placeholder
5.0
Lower 20% 20th percentile — 20% of models score below this This model Where the current model lands Upper 80% 80th percentile — only 20% of models score above this Percentile boundaries are computed across every model in the tree that reports the underlying benchmark for each capability.

What it feels like

  • First end-to-end omni model — text, vision, audio share one neural net (not stitched pipelines)
  • 2x faster, half the price, and 5x higher rate limits than GPT-4 Turbo
  • Native voice-to-voice latency around 320ms — close to human conversational rhythm (210ms)
  • Realtime API (Oct 2024) opened up always-on voice assistants for developers
  • Reasoning is solid but not o1-class — by 2025 it's the 'speed/cost tier', not the 'IQ tier'
  • GPT-4o mini (Jul 2024) became the GPT-3.5 Turbo replacement at much better quality

Best use cases

  • Voice-first applications and real-time multimodal interfaces
  • Cost-sensitive bulk inference where GPT-4-class quality is enough
  • Image understanding workflows — strong vision pipeline at API price
  • Replacing GPT-3.5/Turbo deployments with 4-tier quality at similar cost

Tools to try

Not ideal for

  • Hard reasoning, math, or research — o1/o3/GPT-5 are the right tier
  • Frontier-leaderboard coding (Claude 3.5 Sonnet+ outscored GPT-4o on SWE-bench by mid-2024)
  • Self-hosted / open-weights workflows

Model Evolution

GPT is OpenAI's audio model family.

View full evolution tree →