Compare
Gpt 4o Realtime Preview 2025 06 03 vs Qwen Qwen3 32b
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.
Qwen Qwen3 32b has about 1× the context window of the other in this pair.
Qwen Qwen3 32b has 2% more context capacity (131K vs 128K tokens). Qwen Qwen3 32b is 97% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Qwen Qwen3 32b. Its 131K context fits entire documents without chunking (vs 128K).
RAG / high-volume retrieval
Use Qwen Qwen3 32b. Input tokens are 97% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Qwen Qwen3 32b. Its 16K 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 | Qwen Qwen3 32b |
|---|---|---|
| Context window | 128,000 tokens (128K) | 131,072 tokens (131K) |
| Max output tokens | 4,096 tokens (4K) | 16,384 tokens (16K) |
| Speed tier | Balanced | 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 Realtime Preview 2025 06 03 in | Gpt 4o Realtime Preview 2025 06 03 out | Qwen Qwen3 32b in | Qwen Qwen3 32b out |
|---|---|---|---|---|
| Aws Bedrock | — | — | $0.150/M | $0.600/M |
| Openai | $5.00/M | $20.00/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