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OpenAI: GPT-3.5 Turbo 16k vs Qwen: Qwen3 Max

Head-to-head API cost, context, and performance comparison. Synced at 11:23:02 AM.

Executive Summary

When evaluating OpenAI: GPT-3.5 Turbo 16k against Qwen: Qwen3 Max, the pricing structure is a key differentiator. OpenAI: GPT-3.5 Turbo 16k is approximately 3% more cost-effective per 1 million tokens overall.

However, when looking at raw reasoning capabilities, Qwen: Qwen3 Max leads with a statistical ELO score of 1220. For tasks involving complex logic, coding, or instruction-following, developers might prefer Qwen: Qwen3 Max, provided their budget allows for the API burn rate.

Raw Technical comparison

Metric
OpenAI: GPT-3.5 Turbo 16k
Qwen: Qwen3 Max
Performance (ELO)
1220
1220
Input Cost / 1M
$3.00
$1.20
Output Cost / 1M
$4.00
$6.00
Context Window
16,385 tokens
262,144 tokens

Verdict

If you are looking for pure performance and capability, Tie is statistically superior. However, if API burn rate is the primary concern, OpenAI: GPT-3.5 Turbo 16k wins out aggressively in pricing.

People Also Ask

Is OpenAI: GPT-3.5 Turbo 16k cheaper than Qwen: Qwen3 Max?

Yes. OpenAI: GPT-3.5 Turbo 16k is cheaper for both input and output generation compared to Qwen: Qwen3 Max. Exploring alternatives often yields cost reductions.

Which model has the larger context window?

The Qwen: Qwen3 Max model has the advantage in memory, offering a massive 262,144 token limit for document ingestion.

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