GPT Realtime 2.1 mini
GPT Realtime 2.1 mini by OpenAI: specification and list price in the odnoga catalog. Not served through the odnoga gateway yet — see which models you can call today.
GPT Realtime 2.1 mini is listed by OpenAI in the odnoga catalog for its specification and price. odnoga does not serve it through the gateway yet. It accepts images alongside text. It supports tool and function calling. It can be forced to return structured JSON. Cached input is billed at $0.06 per 1M tokens, so repeated prefixes cost less.
Specification and price
| Vendor | OpenAI |
|---|---|
| Model ID | gpt-realtime-2.1-mini |
| Served on | Not served through odnoga yet |
| Capabilities | Reads images, Tool calling, JSON schema, Streaming, Prompt caching |
| Per 1M tokens | Vendor cost | Your price on Free+7% |
|---|---|---|
| Input | $0.6 | $0.645 |
| Output | $2.40 | $2.58 |
| Cached input | $0.06 | $0.065 |
Vendor cost is the list price per million tokens as recorded in the odnoga catalog; your price applies your plan margin with the same formula that bills every request — see pricing. Pricing
In the catalog, not yet callable
odnoga tracks GPT Realtime 2.1 mini's specification and list price, but does not serve it through the gateway yet.
We would rather say so here than let you find out from an error. If you need this model, tell us — knowing who is waiting is how we decide what to add next.
What GPT Realtime 2.1 mini can do
Everything below is what the model itself supports, as recorded by the vendor. odnoga does not route to it yet, so none of it is reachable through the gateway today.
Send a screenshot, a photo or a scan in the same message as your text.
The model can call functions you define and use what they return.
Answers with valid JSON instead of prose you would have to parse.
Answers in the exact shape you specify, so the response fits your types without a fallback path.
Tokens arrive as they are produced, so your interface can answer immediately.
A prompt you send repeatedly is charged at the cached rate, which is a fraction of the input price.
Beyond text
Takes recorded speech as input.
Answers with generated speech, not only text.
Holds a spoken conversation in real time, with interruptions.
Finer control
- Structured outputs · The provider guarantees the schema rather than merely aiming for it.
- Parallel tools · Can call several of your functions in one turn instead of one after another.
How to use GPT Realtime 2.1 mini
Derived from the odnoga catalog record for this model.
Best for
- Turning text into speech, or speech into text, on the audio endpoints rather than the chat one.
Not the right pick when
- Very long generated documents — output is capped at 4K tokens per response.
- Large documents in one request — the window is 32K tokens, so you will need chunking.
- Anything where a wrong answer is costly without a human check — no model in the catalog removes that requirement.
Practical tips through odnoga
- 01Pin the model id in a managed prompt version, so a model swap is a version change you can compare and roll back, not an edit in application code.
- 02Compare it against 2–8 other models on the same frozen test cases in the evaluation laboratory before you make it the production default.
- 03Keep the stable part of your prompt at the front: cached input is billed at $0.06 per 1M tokens instead of $0.6.
- 04For repeated identical deterministic calls, odnoga answer reuse returns the stored answer and bills no vendor tokens — turn it off for creative output.
- 05Ask for JSON through the response format rather than in the prompt text — the schema is enforced instead of suggested.
- 06Set a fallback model on the route so a vendor incident degrades quality instead of returning an error, and a per-tenant budget so one caller cannot spend the month.
What a month costs
1,000 calls a month, 10,000 input tokens and 2,000 output tokens each, at your Free price (vendor cost +7%):
| Input (10M tokens) | $6.45 |
|---|---|
| Output (2M tokens) | $5.16 |
| Your cost per month on Free | $11.61 |
Vendor list cost $10.80 + odnoga margin $0.813 (+7%). Cached input or answer reuse lowers it; odnoga records both numbers per request.
If GPT Realtime 2.1 mini is not the one
Models that take the same kind of input, are priced the same way, and do the closest thing to what this one does. Not a quality ranking — odnoga does not benchmark models.
| Model | Context | Input / 1M | Output / 1M | Capabilities |
|---|---|---|---|---|
| GPT Realtime 2.1 mini | 32K | $0.6 | $2.40 | Reads images, Tool calling, JSON schema, Streaming, Prompt caching |
| GPT Realtime 2.1 | 32K | $4 | $24 | Reads images, Tool calling, JSON schema, Streaming, Prompt caching |
| Gemini 3.1 Flash Live | 131K | $0.75 | $4.50 | Reads images, Tool calling, JSON schema, Streaming |
| Gemini 2.5 Flash Native Audio (Live) | 131K | $0.5 | $2 | Reasoning, Reads images, Tool calling, JSON schema, Streaming |
Questions
- How much does GPT Realtime 2.1 mini cost per 1M tokens?
- OpenAI lists $0.6 / $2.40 per 1M input / output tokens in the odnoga catalog. Through odnoga you pay that vendor price plus your plan margin, and every request is recorded with both numbers.
- What is GPT Realtime 2.1 mini best for?
- Turning text into speech, or speech into text, on the audio endpoints rather than the chat one.
- Can I switch to GPT Realtime 2.1 mini without changing my code?
- Yes. odnoga exposes one OpenAI-compatible endpoint, so switching means sending "gpt-realtime-2.1-mini" as the model id — or changing it in the managed prompt version, with no application deploy.
- How large is the GPT Realtime 2.1 mini context window?
- 32K tokens of input, with up to 4K tokens of output per response.
All models · Pricing · Docs · Compare models in the evaluation lab