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Thinking Machines: Inkling Small vs DeepSeek: DeepSeek V3.2

Head-to-head API cost, context, and performance comparison. Synced at 1:45:07 PM.

Executive Summary

When evaluating Thinking Machines: Inkling Small against DeepSeek: DeepSeek V3.2, the pricing structure is a key differentiator. DeepSeek: DeepSeek V3.2 is approximately 58% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, DeepSeek: DeepSeek V3.2 leads with a statistical ELO score of 1427. For tasks involving complex logic, coding, or instruction-following, developers might prefer DeepSeek: DeepSeek V3.2, provided their budget allows for the API burn rate.

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Raw Technical comparison

Metric
Thinking Machines: Inkling Small
DeepSeek: DeepSeek V3.2
Performance (ELO)
1427
1427
Input Cost / 1M
$0.45
$0.28
Output Cost / 1M
$1.20
$0.42
Context Window
524,288 tokens
163,840 tokens

Verdict

If you are looking for pure performance and capability, Tie is statistically superior. However, if API burn rate is the primary concern, DeepSeek: DeepSeek V3.2 wins out aggressively in pricing.

People Also Ask

Is Thinking Machines: Inkling Small cheaper than DeepSeek: DeepSeek V3.2?

No. DeepSeek: DeepSeek V3.2 is the more cost-effective model, operating at a lower price point per 1 million tokens.

Which model has the larger context window?

The Thinking Machines: Inkling Small model has the advantage in memory, offering a massive 524,288 token limit for document ingestion.

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