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Magnum v4 72B vs OpenAI: GPT-5.2-Codex

Head-to-head API cost, context, and performance comparison. Synced at 11:17:11 AM.

Executive Summary

When evaluating Magnum v4 72B against OpenAI: GPT-5.2-Codex, the pricing structure is a key differentiator. Magnum v4 72B is approximately 49% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, OpenAI: GPT-5.2-Codex leads with a statistical ELO score of 1300. For tasks involving complex logic, coding, or instruction-following, developers might prefer OpenAI: GPT-5.2-Codex, provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
Magnum v4 72B
OpenAI: GPT-5.2-Codex
Performance (ELO)
1300
1300
Input Cost / 1M
$3.00
$1.75
Output Cost / 1M
$5.00
$14.00
Context Window
16,384 tokens
400,000 tokens

Verdict

If you are looking for pure performance and capability, Tie is statistically superior. However, if API burn rate is the primary concern, Magnum v4 72B wins out aggressively in pricing.

People Also Ask

Is Magnum v4 72B cheaper than OpenAI: GPT-5.2-Codex?

Yes. Magnum v4 72B is cheaper for both input and output generation compared to OpenAI: GPT-5.2-Codex. Exploring alternatives often yields cost reductions.

Which model has the larger context window?

The OpenAI: GPT-5.2-Codex model has the advantage in memory, offering a massive 400,000 token limit for document ingestion.

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