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babbage-002 vs Qwen3.8-Flash

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

babbage-002 Cost
$0.48
Qwen3.8-Flash Cost
$0.24
Qwen3.8-Flash is 49% cheaper
Featurebabbage-002Qwen3.8-Flash
ProviderOpenAIAlibaba
Input Price (1M)$0.40$0.15
Output Price (1M)$0.40$0.47
Context Window16,3841,000,000

Verdict

babbage-002 costs $0.40 per 1M input tokens and $0.40 per 1M output tokens. Qwen3.8-Flash costs $0.15 per 1M input tokens and $0.47 per 1M output tokens. Qwen3.8-Flash is 63% cheaper on input tokens than babbage-002. For output tokens, babbage-002 is the more affordable option at $0.40/1M vs $0.47.

On context window, Qwen3.8-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

  • ✓ Your workload is output-heavy — babbage-002 generates text cheaper
  • ✓ You are already integrated with OpenAI

When to choose Qwen3.8-Flash

  • ✓ You need the lowest input token cost ($ 0.15/1M)
  • ✓ You need a larger context window (1,000,000 tokens)
  • ✓ You are already integrated with Alibaba

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 Qwen3.8-Flash?

Qwen3.8-Flash is cheaper on input tokens at $0.15/1M vs $0.40/1M for babbage-002 — a 63% saving.

What is the context window of babbage-002 vs Qwen3.8-Flash?

babbage-002 has a 16,384-token context window. Qwen3.8-Flash has a 1,000,000-token context window. Qwen3.8-Flash supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: babbage-002 or Qwen3.8-Flash?

The best choice depends on your use case. For cost efficiency on input tokens, Qwen3.8-Flash is the cheaper option. For maximum context length, Qwen3.8-Flash supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.