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DeepSeek V3 vs Openai Gpt 4o
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.
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.
DeepSeek V3 has about 1.3× the context window of the other in this pair.
DeepSeek V3 has 28% more context capacity (163K vs 128K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use DeepSeek V3. Its 163K 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 | DeepSeek V3 | Openai Gpt 4o |
|---|---|---|
| Context window | 163,840 tokens (163K) | 128,000 tokens (128K) |
| Max output tokens | 163,840 tokens (163K) | N/A |
| Speed tier | Balanced | Balanced |
| Vision | No | No |
| Function calling | Yes | No |
| Extended thinking | No | No |
| Prompt caching | No | No |
| Batch API | No | Yes |
| Release date | Dec 2024 | 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 | DeepSeek V3 in | DeepSeek V3 out | Openai Gpt 4o in | Openai Gpt 4o out |
|---|---|---|---|---|
| Gradient | — | — | — | — |
Frequently asked questions
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Example: a multi-turn chat session
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