GPT Audio Mini API128K context
A cost-efficient version of GPT Audio.
Pricing & specs mirror our live pricing as of July 2026 (pay-as-you-go).
What is GPT Audio Mini?
A cost-efficient version of GPT Audio. The new snapshot features an upgraded decoder for more natural sounding voices and maintains better voice consistency. Input is priced at $0.60 per million...
GPT Audio Mini on the release timeline
GPT Audio Mini pricing
Pay-as-you-go on DataLLM Lab — these are our live list prices (identical to the pricing page):
| Model | Input / 1M | Output / 1M | Cache read | Cache write | Context |
|---|---|---|---|---|---|
| GPT Audio Mini | $0.60 | $2.40 | — | — | 128K |
On output price, GPT Audio Mini is cheaper than 39% of the 309 models in the catalog.
What GPT Audio Mini costs per month
| Workload | Tokens in / out (monthly) | Est. cost |
|---|---|---|
| Support chatbot | 40M / 12M | $52.80 |
| RAG / knowledge base | 200M / 20M | $168 |
| Coding agent | 80M / 25M | $108 |
| Batch extraction | 150M / 8M | $109 |
| Content generation | 20M / 40M | $108 |
Estimate your own monthly cost
Cost = input price × input volume + output price × output volume. The same five workloads run on every model page, so any two compare directly.
GPT Audio Mini vs alternatives
| Model | Input / 1M | Output / 1M | Context | Our test |
|---|---|---|---|---|
| GPT Audio Mini | $0.60 | $2.40 | 128K | — |
| GPT-3.5 Turbo (older v0613) | $1.00 | $2.00 | 4K | — |
| GPT-3.5 Turbo Instruct | $1.50 | $2.00 | 4K | — |
| GPT-5 Image Mini | $2.50 | $2.00 | 400K | — |
| Qwen3.6 27B | $0.29 | $2.40 | 262K | — |
| Qwen3.5 397B A17B | $0.39 | $2.45 | 256K | — |
When not to use GPT Audio Mini
- It is served by a single provider, so there is less failover headroom during an outage.
Specs
| Model ID | openai/gpt-audio-mini |
| Modality | text+audio->text+audio (input: text, audio) |
| Context window | 128,000 tokens |
| Max output | 16,384 tokens |
| Tool / function calling | ✅ Yes |
| Structured output (JSON) | ✅ Yes |
| Released | 2026-01-19 |
| Open weights | — (hosted API only) |
How to call GPT Audio Mini
from openai import OpenAI
client = OpenAI(base_url="https://api.datallmlab.com/v1", api_key="YOUR_DATALLM_LAB_KEY")
resp = client.chat.completions.create(
model="openai/gpt-audio-mini",
messages=[{"role": "user", "content": "Hello"}],
# supports tools=[...] and tool_choice
)
print(resp.choices[0].message.content)curl https://api.datallmlab.com/v1/chat/completions \
-H "Authorization: Bearer YOUR_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"openai/gpt-audio-mini","messages":[{"role":"user","content":"Hello"}]}'import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.datallmlab.com/v1", apiKey: process.env.DATALLM_KEY });
const r = await client.chat.completions.create({
model: "openai/gpt-audio-mini",
messages: [{ role: "user", content: "Hello" }],
});
console.log(r.choices[0].message.content);The same key routes GPT Audio Mini and 300+ other models — switch models by changing one string. How OpenAI-compatible APIs work.
Prompting tips for GPT Audio Mini
- Be explicit and show the shape of the answer. Spell out format, tone and constraints up front, and include one short example of the output you want — GPT Audio Mini follows concrete instructions better than abstract ones.
- Give it real tools. Pass a
tools=[...]schema instead of asking it to "pretend" — let GPT Audio Mini emit tool calls, execute them, and feed results back for the next turn. - Constrain JSON with a schema. Use
response_format/ structured outputs rather than "reply in JSON" to get valid, parseable objects every time. - Use the system role for rules. Put persistent instructions in the system message and keep user turns task-specific; pair with structured outputs for reliable automation.
Tips are derived from GPT Audio Mini's actual capabilities — context window, tool & JSON support, modality and price tier — not generic advice.
Open-source tools for GPT Audio Mini
Popular open-source frameworks and agents to build with GPT Audio Mini over the API — star counts pulled from GitHub (July 2026).
Listed by GitHub stars; inclusion is by ecosystem relevance (agent frameworks, SDKs and gateways), not affiliation. Stars change — see each repo for current numbers.
Migrating to GPT Audio Mini
Coming from OpenAI or another gateway? On an OpenAI-compatible setup the only changes are base_url → https://api.datallmlab.com/v1 and model → openai/gpt-audio-mini. Messages, streaming, tool calls and the rest of your code stay the same. Routing & failover guide.
Rate limits & reliability
Rate limits here are the DataLLM Lab gateway's, not the upstream vendor's. On 429 (rate limited) or 503 (provider busy), retry with exponential backoff. See the error-code guide and failover setup.
Related reading
Call GPT Audio Mini with one key
300+ models behind one OpenAI-compatible endpoint — better prices, better uptime, no subscriptions.
Get an API keyCompare pricingFrequently asked questions
What is GPT Audio Mini?
A cost-efficient version of GPT Audio. It accepts text, audio input with a 128K-token context window and was released on 2026-01-19. On DataLLM Lab it is callable through one OpenAI-compatible endpoint.
How much does GPT Audio Mini cost?
On DataLLM Lab it is $0.60 per 1M input tokens and $2.40 per 1M output tokens — cheaper than about 39% of the 309-model catalog on output price. Pay-as-you-go, no subscription.
What is the context window of GPT Audio Mini?
128K tokens, with up to 16K max output tokens.
Is GPT Audio Mini open source?
No open weights are published — it is available through hosted API access only.
How do I call the GPT Audio Mini API?
Point any OpenAI SDK at https://api.datallmlab.com/v1 and set model to "openai/gpt-audio-mini". One DataLLM Lab key routes this model and 300+ others; no code changes beyond the base URL and model string.
What are good alternatives to GPT Audio Mini?
Close options by price and capability include GPT-3.5 Turbo (older v0613), GPT-3.5 Turbo Instruct, GPT-5 Image Mini — all callable with the same DataLLM Lab key.