Amazon engineers are reportedly distilling Anthropic models to cut costs before new token-based pricing kicks in
Quick Answer
Amazon engineers are distilling Anthropic's Claude models to create cost-effective versions ahead of a new token-based pricing model set for next year.
Quick Take
This shift, which could increase expenses significantly, comes as Amazon explores alternatives like OpenAI and invests heavily in AI technologies.
Key Points
- Amazon is distilling Anthropic models to reduce internal costs.
- New token-based pricing for Anthropic models starts next year.
- Amazon's distillation service currently does not support Claude models.
- The company has invested up to $25 billion in Anthropic this year.
- Amazon is also considering alternatives like OpenAI's models.
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~1 min read
Jun 29, 2026
Worried about rising costs, some Amazon engineers are already distilling Anthropic models to build smaller, cheaper versions for internal use. That's according to a report from The Information. Distillation works by having a smaller model learn from a larger model's outputs. Amazon has certain rights to use Anthropic's models for this purpose, according to a person familiar with the matter, similar to Apple's arrangement with Google Gemini. Amazon does offer a distillation service on its Bedrock cloud platform, but Anthropic's Claude models aren't available there; only Amazon's own Nova models and Meta's Llama models are supported.
The effort ties back to a renegotiation of the partnership, according to The Information. Starting next year, Amazon will pay for Anthropic's models based on tokens processed rather than compute hours, which could push costs up sharply. An Amazon spokesperson pushed back, saying the changes from the expanded partnership won't raise costs. Anthropic points to lower prices relative to the performance its models deliver.
Amazon is reportedly exploring alternatives like OpenAI and its own Nova models. The company has invested up to $25 billion more in Anthropic and up to $50 billion in OpenAI this year.
— Originally published at the-decoder.com
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