Model comparison

GPT-5.5 vs DeepSeek V3.2

Compare GPT-5.5 vs DeepSeek V3.2 API pricing: input/output token costs, cache pricing, context windows, workload estimates, and routing fit.

GPT-5.5

openai · gpt-5.5

Input
$5
Output
$30
Context
1.1M

DeepSeek V3.2

deepseek · deepseek/deepseek-v3.2

Input
$0.28
Output
$0.4
Context
163.8K

Quick take

DeepSeek V3.2 has the lower input price at $0.28 per 1M input tokens. DeepSeek V3.2 is cheaper for the example blended workload below. GPT-5.5 has the larger context window at 1.1M tokens.

Choose GPT-5.5 if...

  • GPT-5.5 is safer for long documents, repository analysis, and RAG prompts because it has the larger context window.
  • GPT-5.5 is required if images, screenshots, or visual documents are part of the workflow.

Choose DeepSeek V3.2 if...

  • DeepSeek V3.2 is the better default for cost-sensitive traffic and repeated high-volume calls.
  • DeepSeek V3.2 gives more room for long generated answers, reports, or code output.

Example workload cost

Estimates use input tokens plus 20% output tokens. They exclude provider discounts, cache hits, and tool/search surcharges.

Workload GPT-5.5 DeepSeek V3.2 Cheaper
1M input + 200K output $11.00 $0.36 DeepSeek V3.2
10M input + 2M output $110.00 $3.60 DeepSeek V3.2
100M input + 20M output $1,100.00 $36.00 DeepSeek V3.2

Context, output, and capability fit

GPT-5.5 provides the larger context window. Check max output separately when the task needs long reports, code generation, or full-document rewrites.

GPT-5.5 max output
128K
DeepSeek V3.2 max output
163.8K
GPT-5.5 features
prompt caching, function calling, vision
DeepSeek V3.2 features
prompt caching, function calling

Risk notes for GPT-5.5

  • High output price: cap max tokens for verbose generation workloads.

Risk notes for DeepSeek V3.2

  • Smaller context window: long PDFs, codebases, or RAG prompts may need chunking.

Routing tags

frontierreasoningcodingagentslong-contextmultimodalcache-friendlyragbudgethigh-volumeopen-weightlocal-open

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