babbage-002 vs Gemini 2.0 Flash
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | babbage-002 | Gemini 2.0 Flash |
|---|---|---|
| Provider | OpenAI | |
| Input Price (1M) | $0.40 | $0.10 |
| Output Price (1M) | $0.40 | $0.40 |
| Context Window | 16,384 | 1,000,000 |
Verdict
babbage-002 costs $0.40 per 1M input tokens and $0.40 per 1M output tokens. Gemini 2.0 Flash costs $0.10 per 1M input tokens and $0.40 per 1M output tokens. Gemini 2.0 Flash is 75% cheaper on input tokens than babbage-002. For output tokens, babbage-002 is the more affordable option at $0.40/1M vs $0.40.
On context window, Gemini 2.0 Flash supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose babbage-002
- ✓ You are already integrated with OpenAI
When to choose Gemini 2.0 Flash
- ✓ You need the lowest input token cost ($ 0.10/1M)
- ✓ You need a larger context window (1,000,000 tokens)
- ✓ You are already integrated with Google
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 Gemini 2.0 Flash? ▼
Gemini 2.0 Flash is cheaper on input tokens at $0.10/1M vs $0.40/1M for babbage-002 — a 75% saving.
What is the context window of babbage-002 vs Gemini 2.0 Flash? ▼
babbage-002 has a 16,384-token context window. Gemini 2.0 Flash has a 1,000,000-token context window. Gemini 2.0 Flash supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: babbage-002 or Gemini 2.0 Flash? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Gemini 2.0 Flash is the cheaper option. For maximum context length, Gemini 2.0 Flash supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.