Qwen3.5-9B Claude Opus Reasoning API: Claude 4.6 Intelligence for Pennies
This article introduces a knowledge distillation technique that allows a 9-billion parameter model to reason like the powerful Claude 4.6 Opus model. It also shows how to access this capability via the NexaAPI platform at a fraction of the cost of official pricing.
Why it matters
This technique demonstrates how knowledge distillation can be used to compress powerful AI models into more efficient and cost-effective versions, making advanced reasoning capabilities more accessible.
Key Points
- 1A fine-tuned Qwen3.5-9B model was trained to reason like the Claude 4.6 Opus model using chain-of-thought distillation
- 2The resulting model structures its thinking in a step-by-step manner similar to Claude 4.6 Opus
- 3NexaAPI provides OpenAI-compatible access to this powerful reasoning model at 5x cheaper than official pricing
- 4Python examples are provided to demonstrate basic reasoning and streaming output capabilities
Details
The Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled model was created by fine-tuning the Qwen3.5-9B model to learn the reasoning capabilities of the larger and more powerful Claude 4.6 Opus model. This was achieved through a process called chain-of-thought distillation, where the Claude 4.6 Opus model was used to generate a large number of reasoning examples that the Qwen3.5-9B model then learned to emulate. The result is a compact model that structures its thinking in a step-by-step manner similar to the original Claude 4.6 Opus. While running large models like this locally can be challenging, the NexaAPI platform provides easy access to this reasoning capability at a fraction of the cost of official pricing from OpenAI or other providers.
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