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Gpt 4o Mini Realtime Preview vs Qwen3 32b Fp8
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 Realtime 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.
Qwen3 32b Fp8 has about 1× the context window of the other in this pair.
Qwen3 32b Fp8 has 2% more context capacity (131K vs 128K tokens). Qwen3 32b Fp8 is 91% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Qwen3 32b Fp8. Its 131K context fits entire documents without chunking (vs 128K).
RAG / high-volume retrieval
Use Qwen3 32b Fp8. Input tokens are 91% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Qwen3 32b Fp8. 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 Realtime Preview | Qwen3 32b Fp8 |
|---|---|---|
| Context window | 128,000 tokens (128K) | 131,072 tokens (131K) |
| Max output tokens | 4,096 tokens (4K) | 131,072 tokens (131K) |
| Speed tier | Fast | Balanced |
| Vision | No | No |
| Function calling | Yes | Yes |
| Extended thinking | No | Yes |
| Prompt caching | Yes | No |
| 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 | Gpt 4o Mini Realtime Preview in | Gpt 4o Mini Realtime Preview out | Qwen3 32b Fp8 in | Qwen3 32b Fp8 out |
|---|---|---|---|---|
| Lambda | — | — | $0.050/M | $0.100/M |
| Novita | — | — | $0.100/M | $0.450/M |
| Openai | $0.600/M | $2.40/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