User Experience with Devstral 2 123b
A Reddit user shares their experience using the Devstral 2 123b model, comparing it to the GPT OSS 120b model. They discuss the strengths and weaknesses of each model for different tasks.
Why it matters
This user feedback provides insights into the relative strengths and weaknesses of two prominent large language models, which can help inform AI researchers and developers.
Key Points
- 1Devstral 2 123b seems better at 'agentic stuff' than GPT OSS 120b
- 2GPT OSS 120b has better code quality but is faster due to being a Mixture of Experts (MoE) model
- 3Devstral 2 123b works well with speculative decoding using a heavily quantized Devstral 2 20b model
Details
The user has been testing the Devstral 2 123b model and comparing it to the GPT OSS 120b model. They find that the Devstral 2 123b model performs better at 'agentic stuff', which likely refers to tasks requiring more autonomous decision-making. However, the GPT OSS 120b model has better code quality. The user notes that the GPT OSS 120b model is faster because it uses a Mixture of Experts (MoE) architecture. They also mention that the Devstral 2 123b model works well with speculative decoding using a heavily quantized Devstral 2 20b model.
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