Compare
Gpt 4o Realtime Preview 2025 06 03 vs GPT-5.4
This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.
Model
Gpt 4o Realtime Preview 2025 06 03
Context window
128K
128,000 tokens · ~96K words
Context window · side by side
Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.
GPT-5.4 has about 8.2× the context window of the other in this pair.
GPT-5.4 has 720% more context capacity (1050K vs 128K tokens). GPT-5.4 is 50% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use GPT-5.4. Its 1050K context fits entire documents without chunking (vs 128K).
RAG / high-volume retrieval
Use GPT-5.4. Input tokens are 50% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use GPT-5.4. Its 128K max output lets you generate complete artifacts in one request.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Gpt 4o Realtime Preview 2025 06 03 | GPT-5.4 |
|---|---|---|
| Context window | 128,000 tokens (128K) | 1,050,000 tokens (1050K) |
| Max output tokens | 4,096 tokens (4K) | 128,000 tokens (128K) |
| Speed tier | Balanced | Balanced |
| Vision | No | Yes |
| Function calling | Yes | Yes |
| Extended thinking | No | Yes |
| Prompt caching | Yes | Yes |
| Batch API | Yes | No |
| Release date | N/A | Mar 2026 |
Pricing matrix
Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.
| Provider | Gpt 4o Realtime Preview 2025 06 03 in | Gpt 4o Realtime Preview 2025 06 03 out | GPT-5.4 in | GPT-5.4 out |
|---|---|---|---|---|
| Azure | — | — | $2.50/M | $15.00/M |
| Openai | $5.00/M | $20.00/M | $2.50/M | $15.00/M |
Frequently asked questions
Powered by Mem0
Use a smaller model.
Get better results.
Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.
Example: a multi-turn chat session
80% less to send — works with any model