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Baidu: ERNIE 4.5 21B A3B Thinking vs inclusionAI: Ling-2.6-flash

Head-to-head API cost, context, and performance comparison. Synced at 2:33:04 PM.

Executive Summary

When evaluating Baidu: ERNIE 4.5 21B A3B Thinking against inclusionAI: Ling-2.6-flash, the pricing structure is a key differentiator. inclusionAI: Ling-2.6-flash is approximately 9% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, Baidu: ERNIE 4.5 21B A3B Thinking leads with a statistical ELO score of 1418. For tasks involving complex logic, coding, or instruction-following, developers might prefer Baidu: ERNIE 4.5 21B A3B Thinking, provided their budget allows for the API burn rate.

Raw Technical comparison

Metric
Baidu: ERNIE 4.5 21B A3B Thinking
inclusionAI: Ling-2.6-flash
Performance (ELO)
1418
1417
Input Cost / 1M
$0.07
$0.08
Output Cost / 1M
$0.28
$0.24
Context Window
131,072 tokens
262,144 tokens

Verdict

If you are looking for pure performance and capability, Baidu: ERNIE 4.5 21B A3B Thinking is statistically superior. However, if API burn rate is the primary concern, inclusionAI: Ling-2.6-flash wins out aggressively in pricing.

People Also Ask

Is Baidu: ERNIE 4.5 21B A3B Thinking cheaper than inclusionAI: Ling-2.6-flash?

No. inclusionAI: Ling-2.6-flash is the more cost-effective model, operating at a lower price point per 1 million tokens.

Which model has the larger context window?

The inclusionAI: Ling-2.6-flash model has the advantage in memory, offering a massive 262,144 token limit for document ingestion.

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