Compare
Openai Gpt 4o vs Qwen3.5-9B
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
Qwen3.5-9B
Context window
256K
256,000 tokens · ~192K 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.
Qwen3.5-9B has about 2× the context window of the other in this pair.
Qwen3.5-9B has 100% more context capacity (256K vs 128K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Qwen3.5-9B. Its 256K context fits entire documents without chunking (vs 128K).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Openai Gpt 4o | Qwen3.5-9B |
|---|---|---|
| Context window | 128,000 tokens (128K) | 256,000 tokens (256K) |
| Max output tokens | N/A | 32,768 tokens (32K) |
| Speed tier | Balanced | Balanced |
| Vision | No | Yes |
| Function calling | No | Yes |
| Extended thinking | No | Yes |
| Prompt caching | No | No |
| 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 | Openai Gpt 4o in | Openai Gpt 4o out | Qwen3.5-9B in | Qwen3.5-9B out |
|---|---|---|---|---|
| Gradient | — | — | — | — |
Frequently asked questions
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