Compare
Ft:gpt 4o Mini 2024 07 18 vs Gpt 5 1 Chat Latest
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
Ft:gpt 4o Mini 2024 07 18
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.
Same context window size for both models.
Ft:gpt 4o Mini 2024 07 18 and Gpt 5 1 Chat Latest have identical context windows (128K tokens). Ft:gpt 4o Mini 2024 07 18 is 76% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
RAG / high-volume retrieval
Use Ft:gpt 4o Mini 2024 07 18. Input tokens are 76% cheaper — critical when sending large retrieved contexts.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Ft:gpt 4o Mini 2024 07 18 | Gpt 5 1 Chat Latest |
|---|---|---|
| Context window | 128,000 tokens (128K) | 128,000 tokens (128K) |
| Max output tokens | 16,384 tokens (16K) | 16,384 tokens (16K) |
| Speed tier | Fast | Balanced |
| Vision | No | Yes |
| Function calling | Yes | No |
| Extended thinking | No | Yes |
| Prompt caching | Yes | Yes |
| Batch API | Yes | No |
| Release date | N/A | N/A |
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 | Ft:gpt 4o Mini 2024 07 18 in | Ft:gpt 4o Mini 2024 07 18 out | Gpt 5 1 Chat Latest in | Gpt 5 1 Chat Latest out |
|---|---|---|---|---|
| Openai | $0.300/M | $1.20/M | $1.25/M | $10.00/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