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HomeModelsGPT Audio Mini
OpenAIBalanced

GPT Audio Mini

The most practical choice for cost-conscious voice application developers who need native audio I/O without compromising too much on intelligence.

42
Coding
55
Writing
45
Research
0
Images
72
Value
60
Long Context
Use this when

Building voice assistants, audio bots, and speech-enabled applications that need real-time audio processing at scale without breaking the budget.

Skip this if

You need high-quality complex reasoning, precise code generation, or are building a text-only application where audio capabilities add no value.

Pricing
$0.60/1M in
$2.40/1M out
→0%since May 2026
Context
128k tokens
Speed
Fast

Audio tokens are priced differently from text tokens in OpenAI's API — audio input/output carries a significant premium over text tokens, so real-world costs for voice-heavy workloads will be substantially higher than the listed text token price suggests. Check OpenAI's audio token pricing separately.

How to access
API
$0.6/1M input tokens
Subscription = chat interface. API = build with it. Compare all subscription plans
Switch to instead if...
Best overall
GPT-6 Astra
Cheaper option
GPT-3.5 Turbo
Faster option
GPT Audio

Strengths

Native audio input and output without requiring separate speech-to-text and text-to-speech pipeline

Very affordable at $0.6/$2.4 per 1M tokens compared to GPT-4o Audio at $2.5/$10 per 1M tokens

128K context window supports extended conversation histories for voice applications

Low-latency audio responses suitable for real-time conversational interfaces

Weaknesses

Significantly weaker reasoning and instruction-following than GPT-4o Audio or full GPT-4o

Not competitive with Claude Sonnet 4.6 or Gemini 3.1 Pro on complex text-only tasks

Audio quality and naturalness falls short of dedicated TTS solutions like ElevenLabs or OpenAI's own TTS-1-HD

Real-world use cases

What people actually use GPT Audio Mini for.

Building a customer service voice bot that handles hundreds of concurrent calls at scale

Creating a real-time language learning app where users practice spoken conversation

Powering a voice-enabled smart home interface with natural back-and-forth dialogue

How GPT Audio Mini compares

The nearest models people weigh against it, and what actually separates them.

vs GPT Audio — Against GPT Audio (OpenAI), GPT Audio Mini runs about 76% cheaper per token and answers faster. Take GPT Audio Mini unless you specifically need what GPT Audio does better.

vs GPT-3.5 Turbo — Against GPT-3.5 Turbo (OpenAI), GPT Audio Mini costs about 33% more per token, takes 7.8x the context and answers slower. GPT-3.5 Turbo is the one to check first if the price difference matters more than the ceiling.

vs GPT-3.5 Turbo (older v0613) — Against GPT-3.5 Turbo (older v0613) (OpenAI), GPT Audio Mini lands within a few percent on price, takes 31.3x the context and answers slower. Which one wins depends on whether context depth or latency is your constraint.

Price History

GPT Audio Mini pricing over time

→0% since May 31

$0.648$0.624$0.600$0.576$0.552May 31Jun 18Jul 10Jul 27Aug 14Sep 8

90 data points · tracked daily since May 31, 2026

Ready to try it?

Start using GPT Audio Mini

Building voice assistants, audio bots, and speech-enabled applications that need real-time audio processing at scale without breaking the budget.. Start free — no card required.

Try GPT Audio Mini freeCompare alternatives

Recommendations are made independently based on real-world use and public benchmarks. See our disclosures for details.

Compare alternatives

Similar models worth checking before you commit.

All GPT Audio Mini alternatives →
OpenAIBalanced

GPT Audio

GPT Audio is OpenAI's speech-capable model variant optimized for real-time audio input and output, enabling natural voice conversations and audio processing. It extends GPT-4o's multimodal capabilities with native audio understanding and generation without requiring separate transcription pipelines.

Verdict
The go-to choice for native voice AI applications, but overkill and potentially costly for anything without real audio requirements.
Quality score
43%
Pricing
$2.50/1M in
$10.00/1M out
Speed
Balanced
3/5 speed
Context
128k tokens
Audio tokens are counted differently from text tokens — a few seconds of audio can consume hundreds of tokens, so monitor usage carefully. Real-time audio streaming requires WebSocket or Realtime API endpoints, not the standard Chat Completions API. Availability may be limited by tier or region.
Voice AIAudioMultimodalReal-timeSpeech
Best for
Building voice assistants, real-time spoken dialogue systems, and applications that need to process or generate natural speech end-to-end.
View model
OpenAIBudget

GPT-3.5 Turbo

GPT-3.5 Turbo is OpenAI's legacy fast and affordable chat model, optimized for dialogue and straightforward text tasks at low cost. It was the backbone of early ChatGPT and remains a go-to for high-volume, cost-sensitive deployments.

Verdict
A once-dominant budget model now outclassed by cheaper, smarter alternatives like GPT-4o mini.
Quality score
35%
Pricing
$0.50/1M in
$1.50/1M out
Speed
Very fast
5/5 speed
Context
16k tokens
GPT-3.5 Turbo is still available via OpenAI API and supports fine-tuning, which keeps it relevant for teams with existing trained models. However, OpenAI has deprioritized its development in favor of the GPT-4o family. Not multimodal — text only.
BudgetLegacyFastHigh-volumeChatbot
Best for
High-volume, low-complexity tasks like chatbots, classification, summarization, and simple Q&A where cost matters more than cutting-edge quality.
View model
OpenAIBalanced

GPT-3.5 Turbo (older v0613)

An older versioned snapshot of GPT-3.5 Turbo (v0613), OpenAI's once-dominant mid-tier language model optimized for fast chat completions and instruction following. This specific checkpoint is frozen in time, predating later capability improvements introduced in subsequent GPT-3.5 Turbo updates.

Verdict
A once-useful workhorse now completely overshadowed by cheaper, more capable successors.
Quality score
31%
Pricing
$1.00/1M in
$2.00/1M out
Speed
Very fast
5/5 speed
Context
4k tokens
This is a pinned legacy snapshot (v0613) and may eventually be deprecated by OpenAI. The 4,095-token context window is its most significant practical limitation. OpenAI's own GPT-4o mini offers drastically more context and better quality at a comparable price — strongly consider migrating.
LegacyBudgetFastShort ContextOpenAI
Best for
High-volume, cost-sensitive text tasks like classification, summarization, and simple Q&A where bleeding-edge quality is not required.
View model

Change history

Pricing moves, ranking shifts, and capability updates.

New ModelMar 27, 2026

OpenAI: GPT Audio Mini — added to UseRightAI

OpenAI: GPT Audio Mini (OpenAI) is now indexed. The most practical choice for cost-conscious voice application developers who need native audio I/O without compromising too much on intelligence.

View model

FAQ

How much does GPT Audio Mini cost?

GPT Audio Mini costs $0.6 per million input tokens and $2.4 per million output tokens on the API. A month of 10M input and 2M output tokens runs about $10.80 at list price, before any batch or caching discounts.

What is GPT Audio Mini best for?

GPT Audio Mini is best for building voice assistants, audio bots, and speech-enabled applications that need real-time audio processing at scale without breaking the budget.. It is a strong fit when that workflow matters more than the tradeoffs around balanced pricing and fast speed.

When should I avoid GPT Audio Mini?

You need high-quality complex reasoning, precise code generation, or are building a text-only application where audio capabilities add no value.

What is a cheaper alternative to GPT Audio Mini?

GPT-3.5 Turbo (OpenAI) at $0.50/1M/1M input against GPT Audio Mini's $0.60/1M/1M — roughly 33% less per token all in. A once-dominant budget model now outclassed by cheaper, smarter alternatives like GPT-4o mini. Compare it first if GPT Audio Mini's pricing is the thing stopping you.

What is a faster alternative to GPT Audio Mini?

GPT Audio — balanced against GPT Audio Mini's fast, with 128k tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.

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