DeepSeek updated their R1 reasoning model. The model card has not a lot of details (more compute + algorithmic improvements), but the benchmarks show that the whale is yet again at the frontier, rivaling closed models.
Even more exciting as we enter the agentic era is the support for tools. R1 is close to the frontier in popular function-calling benchmarks as well:
In my quick tests it seems like the new R1 at least has the same distinctive character, but could be even more clever. Here's an example:
Another example is it seeming to do better on the search APIs (at least what is built into OpenRouter), boosted by the new tool-calling capabilities.
This new version of R1 is much less likely to start every reasoning chain with "Okay," which should be good for diversity and token efficiency.
And, to top it all off: They also used the new R1 thinking traces to fine-tune DeepSeek-R1-0528-Qwen3-8B, boosting scores significantly in math benchmarks.
For more, see DeepSeek's announcement or Artificial Analysis's scores.
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