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## **Industry Status: Inference ≠ The More, The Better**
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Over the past year, **hybrid inference / automatic routing** has become one of the hottest topics in the large model industry.
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Over the past year, **Hybrid inference / automatic routing** has become one of the hottest topics in the large model industry.
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Take **GPT-5** as an example. Its real breakthrough isn't in the number of parameters, but in the **"automatic routing + thinking quota"**:
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@@ -39,7 +39,7 @@ In summary: The industry is entering a new era where **"not a single token shoul
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## **Recent Research: vLLM Semantic Router**
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Amid the industry's push for "hybrid inference," we focus on the **open-source inference engine vLLM**.
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Amid the industry's push for "Hybrid inference," we focus on the **open-source inference engine vLLM**.
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vLLM has become the de facto standard for deploying large models in the industry. However, it lacks "semantic-level fine control." Developers either enable full inference (wasting computation) or disable inference entirely (losing accuracy).
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@@ -54,7 +54,7 @@ Thus, we propose the **vLLM Semantic Router**, bringing GPT-5's "smart routing"
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2.**Smart Routing**:
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* Simple queries → Directly call the non-inference mode for fast responses.
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* Complex inference queries → Enable Chain-of-Thought to ensure accuracy.
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3.**Rust High-Performance Engine**: Using the HuggingFace Candle framework to achieve high concurrency and zero-copy efficient inference.
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Thus, the next frontier will be: **Intelligent self-adjusting inference mechanisms**. No need for explicit user switches or hardcoding; instead, the model/system can autonomously decide when to "think deeply" or provide a quick answer.
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# **Summary in One Sentence**
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##**Summary in One Sentence**
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***GPT-5**: Uses routing for business, driving widespread intelligence.
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***vLLM Semantic Router**: Uses semantic routing for efficiency, driving green AI.
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