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OpenAI: o4 Mini High (batch) vs Thinking Machines: Inkling (batch)

Head-to-head API cost, context, and performance comparison. Synced at 4:17:37 PM.

Executive Summary

When evaluating OpenAI: o4 Mini High (batch) against Thinking Machines: Inkling (batch), the pricing structure is a key differentiator. Thinking Machines: Inkling (batch) is approximately 8% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, Thinking Machines: Inkling (batch) leads with a statistical ELO score of 1423. For tasks involving complex logic, coding, or instruction-following, developers might prefer Thinking Machines: Inkling (batch), provided their budget allows for the API burn rate.

Raw Technical comparison

Metric
OpenAI: o4 Mini High (batch)
Thinking Machines: Inkling (batch)
Performance (ELO)
1423
1423
Input Cost / 1M
$0.55
$0.50
Output Cost / 1M
$2.20
$2.02
Context Window
200,000 tokens
524,288 tokens

Verdict

If you are looking for pure performance and capability, Tie is statistically superior. However, if API burn rate is the primary concern, Thinking Machines: Inkling (batch) wins out aggressively in pricing.

People Also Ask

Is OpenAI: o4 Mini High (batch) cheaper than Thinking Machines: Inkling (batch)?

No. Thinking Machines: Inkling (batch) 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 (batch) model has the advantage in memory, offering a massive 524,288 token limit for document ingestion.

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