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GPT-4o-mini Search Preview vs Moonshot V1 128k
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-mini Search Preview
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.
Moonshot V1 128k has about 1× the context window of the other in this pair.
Moonshot V1 128k has 2% more context capacity (131K vs 128K tokens). GPT-4o-mini Search Preview is 92% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Moonshot V1 128k. Its 131K context fits entire documents without chunking (vs 128K).
RAG / high-volume retrieval
Use GPT-4o-mini Search Preview. Input tokens are 92% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Moonshot V1 128k. Its 131K 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-mini Search Preview | Moonshot V1 128k |
|---|---|---|
| Context window | 128,000 tokens (128K) | 131,072 tokens (131K) |
| Max output tokens | 16,384 tokens (16K) | 131,072 tokens (131K) |
| Speed tier | Fast | Balanced |
| Vision | Yes | No |
| Function calling | Yes | Yes |
| Extended thinking | No | No |
| Prompt caching | Yes | No |
| Batch API | Yes | No |
| Release date | Mar 2025 | 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 | GPT-4o-mini Search Preview in | GPT-4o-mini Search Preview out | Moonshot V1 128k in | Moonshot V1 128k out |
|---|---|---|---|---|
| Moonshot | — | — | $2.00/M | $5.00/M |
| Openai | $0.150/M | $0.600/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