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Model comparison

GPT-5.5 vs Llama 3.3 70B

Not a benchmark table. This puts pricing, context, interface fit, and key visibility into one decision card.

Provider
OpenAI / Meta
global / global
Context
1M / 131.1K
text+image+file->text / text->text
Input price
$5.00 / $0.12
per 1M tokens
Output price
$30.00 / $0.30
per 1M tokens
Left model
GPT-5.5
OpenAI
FamilyGPT-5.5
Modalitytext+image+file->text

当前主推旗舰模型,适合复杂推理、编码、多工具企业工作流。

Right model
Llama 3.3 70B
Meta
FamilyLlama
Modalitytext->text

经典开源旗舰型号,适合对比和托管平台目录。

Comparison summary

How to choose first

This is a cross-provider comparison. Start with the job boundary, then verify what your key can actually see.

On the listed price snapshot, Llama 3.3 70B is cheaper on combined input and output, but real routing, discounts, and limits still matter.

GPT-5.5 has the larger context window, which helps with long documents, knowledge bases, logs, and multi-turn workflows.

Decision boundary

Do not start with which model is absolutely stronger. Start with the boundary: cost, context, speed, quality, ecosystem, or supply stability.

  • GPT-5.5 is worth checking first when the GPT-5.5 family, 1M context, and text+image+file->text capability match the job.
  • Llama 3.3 70B is worth checking first when the Llama family, 131.1K context, and text->text capability match the job.

Key checking route

If you already hold a key, the valuable check is provider identity, callable models, and whether balance, limits, or subscription status are visible.

  • OpenAI: GPT-5.5, GPT-5.5, text+image+file->text
  • Meta: Llama 3.3 70B, Llama, text->text

Commercial fit

Commercially, do not look at model names alone. Combine price, limits, region, upstream stability, and ongoing monitoring.

  • GPT-5.5: 当前主推旗舰模型,适合复杂推理、编码、多工具企业工作流。
  • Llama 3.3 70B: 经典开源旗舰型号,适合对比和托管平台目录。