GPT Audio model profile
Evidence snapshot:
GPT Audio is a OpenAI model profile with a 128,000-token context window. The dated catalog snapshot records text, audio modalities and interfaces for audio input, audio output, structured output, text generation, tool calling.
The gpt-audio model is OpenAI's first generally available audio model. The new snapshot features an upgraded decoder for more natural sounding voices and maintains better voice consistency. Audio is priced...
GPT Audio is a reference profile: OpenAI publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.
GPT Audio is an independent knowledge profile. It does not claim that Kendr hosts the model, quote a Kendr customer price, promise API availability, or advertise a Kendr routing receipt.
GPT Audio accepts text and audio and returns text and audio. The snapshot records audio input, audio output, structured output, text generation, and tool calling as capabilities or interfaces.
The dated reference snapshot lists $2.5 input and $10 output per million tokens.
No comparable third-party benchmark value is present in the 2026-09-06 snapshot. Missing values are not estimated.
No comparable popularity rank or traffic share is present in the 2026-09-06 snapshot. No comparable routing rank or traffic-share observation is attached to this dated profile; missing adoption evidence is not estimated.
Profile data was reviewed for the 2026-09-06 snapshot. Claims retain their source dates, and unavailable fields are shown as unavailable instead of estimated.
Profile facts
- Profile type
- Model research profile
- Provider or publisher
- OpenAI
- Context window
- 128,000 tokens
- Snapshot date
- 2026-09-06
- Knowledge cutoff
- Not disclosed
- Reference catalog ID
- openai/gpt-audio
When to pick GPT Audio
GPT Audio is a reference profile: OpenAI publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.
Each condition below is derived from this model's own values in the 2026-09-06 snapshot, compared only against models publishing the same field.
- Reach for it when the input is speech. The snapshot records audio input, so recordings can go to this route rather than being transcribed first.
- Reach for it when the output is audio. This route produces audio rather than only text, and those units are priced separately from tokens.
- Reach for it when the model has to call tools. Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose.
- Look elsewhere when you need to call it through Kendr today. This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr.
- Look elsewhere when the work does not justify the rate. At $2.5 in and $10 out per 1M tokens, this is in the most expensive tenth of the 146 models publishing both rates. Route routine or high-volume traffic to a cheaper model and keep this one for work that needs it.
- Look elsewhere when the prompt is long. The 128K-token context window is in the bottom quarter of the 163 models publishing a limit. Long documents need chunking or a wider-context route.
Context, modalities, and identity
GPT Audio accepts text and audio and returns text and audio. The snapshot records audio input, audio output, structured output, text generation, and tool calling as capabilities or interfaces.
- Provider or publisher
- OpenAI
- Context window
- 128,000 tokens
- Maximum output
- 16,384 tokens
- Input modalities
- text and audio
- Output modalities
- text and audio
- Knowledge cutoff
- Not disclosed
Model overview
The gpt-audio model is OpenAI's first generally available audio model. The new snapshot features an upgraded decoder for more natural sounding voices and maintains better voice consistency. Audio is priced...
- Reference model ID
- openai/gpt-audio
- Canonical version
- openai/gpt-audio
- Hugging Face ID
- Not separately documented
Capabilities and supported controls
Capabilities and parameters are reported from the dated catalog and source records; their presence does not guarantee identical behavior across every provider route.
- Supported parameters
- frequency_penalty, logit_bias, logprobs, max_tokens, presence_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_logprobs, top_p
- audio input
- audio output
- structured output
- text generation
- tool calling
Dated pricing snapshot
The dated reference snapshot lists $2.5 input and $10 output per million tokens.
These are dated third-party reference prices, not Kendr prices or an availability offer. Routes, tiers, caching, region, and provider policy can change the landed price.
- Price date
- 2026-09-06
- Input
- $2.5 per 1M tokens
- Cached input
- No verified rate
- Output
- $10 per 1M tokens
Provider routes, performance, and uptime
The snapshot retains 1 provider endpoint. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.
- Active provider endpoints
- 1
- Best p50 latency
- No recent metric
- Best p50 throughput
- No recent metric
- Availability with routing
- No recent metric
- Availability without routing
- No recent metric
- Performance date
- 2026-09-06
| Provider | Quantization | Input / 1M | Output / 1M | Cache read / 1M | Context | p50 latency | p50 throughput | Uptime (1d) |
|---|---|---|---|---|---|---|---|---|
| OpenAI | unknown | $2.5 / 1M | $10 / 1M | No verified rate | 128,000 tokens | No recent p50 | No recent p50 | 100.00% |
Benchmark evidence and limitations
No comparable third-party benchmark value is present in the 2026-09-06 snapshot. Missing values are not estimated.
Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.
Popularity and market context
No comparable popularity rank or traffic share is present in the 2026-09-06 snapshot. No comparable routing rank or traffic-share observation is attached to this dated profile; missing adoption evidence is not estimated.
- Third-party catalog rank
- No verified rank
- Global market share
- Not inferred
- Observation date
- 2026-09-06
Frequently asked questions
When should I use GPT Audio?
GPT Audio is a reference profile: OpenAI publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call. Reach for it when the input is speech: The snapshot records audio input, so recordings can go to this route rather than being transcribed first. Reach for it when the output is audio: This route produces audio rather than only text, and those units are priced separately from tokens. Reach for it when the model has to call tools: Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose. Look elsewhere when you need to call it through Kendr today: This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr. Look elsewhere when the work does not justify the rate: At $2.5 in and $10 out per 1M tokens, this is in the most expensive tenth of the 146 models publishing both rates. Route routine or high-volume traffic to a cheaper model and keep this one for work that needs it. Look elsewhere when the prompt is long: The 128K-token context window is in the bottom quarter of the 163 models publishing a limit. Long documents need chunking or a wider-context route.
What is GPT Audio?
GPT Audio is a OpenAI model profile with a 128,000-token context window. The dated catalog snapshot records text, audio modalities and interfaces for audio input, audio output, structured output, text generation, tool calling.
What context window does GPT Audio have?
The dated profile lists 128,000 tokens of context and up to 16,384 output tokens. Provider routes, variants, and runtime configuration can impose lower effective limits.
What benchmark evidence is available for GPT Audio?
No comparable third-party benchmark value is present in the 2026-09-06 snapshot. Missing values are not estimated. Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.
Is GPT Audio available through Kendr?
This is an independent knowledge profile, not a Kendr-hosted availability claim. Check Kendr's live public model API for currently enabled Kendr aliases.
Does the popularity rank represent GPT Audio's global market share?
No comparable popularity rank or traffic share is present in the 2026-09-06 snapshot. No comparable routing rank or traffic-share observation is attached to this dated profile; missing adoption evidence is not estimated. No global market-share percentage is inferred when the source does not publish one.
Sources and evidence dates
- GPT Audio third-party catalog record (catalog, checked 2026-09-06)
- Third-party model catalog methodology (methodology, checked 2026-09-06)
- OpenAI official model documentation (primary, checked 2026-09-06)