Model comparison

GPT-5.5 vs Qwen3 Max

Compare GPT-5.5 vs Qwen3 Max 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

Qwen3 Max

novita · novita/qwen/qwen3-max

Input
$2.11
Output
$8.45
Context
262.1K

Quick take

Qwen3 Max has the lower input price at $2.11 per 1M input tokens. Qwen3 Max 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 gives more room for long generated answers, reports, or code output.
  • GPT-5.5 is stronger when the same large prompt or document is reused because it supports prompt caching.

Choose Qwen3 Max if...

  • Qwen3 Max is the better default for cost-sensitive traffic and repeated high-volume calls.

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 Qwen3 Max Cheaper
1M input + 200K output $11.00 $3.80 Qwen3 Max
10M input + 2M output $110.00 $38.00 Qwen3 Max
100M input + 20M output $1,100.00 $380.00 Qwen3 Max

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
Qwen3 Max max output
65.5K
GPT-5.5 features
prompt caching, function calling, vision
Qwen3 Max features
function calling

Risk notes for GPT-5.5

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

Risk notes for Qwen3 Max

  • No prompt caching in this snapshot: repeated long-context calls may be more expensive.

Routing tags

frontierreasoningcodingagentslong-contextmultimodalcache-friendlyragopen-weightlocal-open

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