Hermes 4 405B: Unpacking the Benchmark Hype
This article examines the nuances behind the impressive 96.3% MATH-500 score of the Hermes 4 405B language model, highlighting that it only applies when the model is in 'reasoning mode' and that its overall performance is more complex.
Why it matters
This article provides important context around the Hermes 4 405B model's capabilities and limitations, which is crucial for organizations evaluating its suitability for their use cases.
Key Points
- 1Hermes 4 405B has a 96.3% MATH-500 score, but this is only when the model is in 'reasoning mode'
- 2The model's overall performance is more mixed, with a lower 57.1% score on the RefusalBench test
- 3The model has a single checkpoint that can switch between standard inference and chain-of-thought reasoning via a <think> toggle
- 4Most hosted deployments do not enable the reasoning mode by default, leading to lower benchmark scores
Details
The Hermes 4 405B language model made headlines for achieving a 96.3% score on the MATH-500 benchmark. However, this number only applies when the model is in 'reasoning mode', which is enabled via a <think> toggle. In standard inference mode, the model scores much lower, with Artificial Analysis ranking it #22 out of 37 models. The article argues that the more interesting number is the 57.1% score on the RefusalBench test, which reflects the model's 'neutral alignment' stance. This has significant implications for how the model should be deployed in production environments. The single checkpoint design that allows switching between reasoning and non-reasoning modes is highlighted as a technically novel aspect of the model.
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