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babbage-002 vs DeepSeek V4-Pro

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

babbage-002 Cost
$0.48
DeepSeek V4-Pro Cost
$2.11
babbage-002 is 77% cheaper
Featurebabbage-002DeepSeek V4-Pro
ProviderOpenAIDeepSeek
Input Price (1M)$0.40$1.32
Output Price (1M)$0.40$3.96
Context Window16,3841,000,000

Verdict

babbage-002 costs $0.40 per 1M input tokens and $0.40 per 1M output tokens. DeepSeek V4-Pro costs $1.32 per 1M input tokens and $3.96 per 1M output tokens. babbage-002 is 70% cheaper on input tokens than DeepSeek V4-Pro. For output tokens, babbage-002 is the more affordable option at $0.40/1M vs $3.96.

On context window, DeepSeek V4-Pro supports 1,000,000 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 babbage-002

  • ✓ You need the lowest input token cost ($ 0.40/1M)
  • ✓ Your workload is output-heavy — babbage-002 generates text cheaper
  • ✓ You are already integrated with OpenAI

When to choose DeepSeek V4-Pro

  • ✓ You need a larger context window (1,000,000 tokens)
  • ✓ You are already integrated with DeepSeek

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 babbage-002 cheaper than DeepSeek V4-Pro?

babbage-002 is cheaper on input tokens at $0.40/1M vs $1.32/1M for DeepSeek V4-Pro — a 70% saving.

What is the context window of babbage-002 vs DeepSeek V4-Pro?

babbage-002 has a 16,384-token context window. DeepSeek V4-Pro has a 1,000,000-token context window. DeepSeek V4-Pro supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: babbage-002 or DeepSeek V4-Pro?

The best choice depends on your use case. For cost efficiency on input tokens, babbage-002 is the cheaper option. For maximum context length, DeepSeek V4-Pro supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.