DeepSeek V3.2 vs babbage-002
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | DeepSeek V3.2 | babbage-002 |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Input Price (1M) | $0.28 | $0.40 |
| Output Price (1M) | $0.42 | $0.40 |
| Context Window | 128,000 | 16,384 |
Verdict
DeepSeek V3.2 costs $0.28 per 1M input tokens and $0.42 per 1M output tokens. babbage-002 costs $0.40 per 1M input tokens and $0.40 per 1M output tokens. DeepSeek V3.2 is 30% cheaper on input tokens than babbage-002. For output tokens, babbage-002 is the more affordable option at $0.40/1M vs $0.42.
On context window, DeepSeek V3.2 supports 128,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose DeepSeek V3.2
- ✓ You need the lowest input token cost ($ 0.28/1M)
- ✓ You need a larger context window (128,000 tokens)
- ✓ You are already integrated with DeepSeek
When to choose babbage-002
- ✓ Your workload is output-heavy — babbage-002 generates text cheaper
- ✓ You are already integrated with OpenAI
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is DeepSeek V3.2 cheaper than babbage-002? ▼
DeepSeek V3.2 is cheaper on input tokens at $0.28/1M vs $0.40/1M for babbage-002 — a 30% saving.
What is the context window of DeepSeek V3.2 vs babbage-002? ▼
DeepSeek V3.2 has a 128,000-token context window. babbage-002 has a 16,384-token context window. DeepSeek V3.2 supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: DeepSeek V3.2 or babbage-002? ▼
The best choice depends on your use case. For cost efficiency on input tokens, DeepSeek V3.2 is the cheaper option. For maximum context length, DeepSeek V3.2 supports 128,000 tokens. Use the comparison table above to find the right fit for your workload.