granite-switch-4.1-8b: What's New, Hardware Needed, How to Run It Free

Granite Switch 4.1 packs chat, decision-making and speech-to-text into a single 8 billion-parameter endpoint. It lets you switch functions with just a control token.

Granite Switch 4.1 8B is a modular large language model built by IBM-Granite. The core has eight billion parameters and can handle a context window of one hundred twenty-eight thousand tokens. It is released under the Apache 2.0 license, so you can download the weights from Hugging Face and run them yourself.

What makes this model stand out is its composition. Two LoRA adapters, decision and guardian-core, are activated by special control tokens, so you can ask the same endpoint for pure chat, probability-based decisions, or safety checks. It also bundles a 470-million-parameter English speech-to-text encoder, letting you transcribe audio without a separate server. All three capabilities share the same model checkpoint.

The model card reports a Decision Index v0.3 score of 42.9 overall. By domain, it scores 48.9 on language tasks, 49.8 on retrieval, 59.8 on tool use, 29.1 on knowledge, and 18.0 on arts. The hosted and local serving paths differ by only about 0.6 points, confirming consistent performance.

Granite Switch shines for quick English speech transcription and for returning calibrated probability distributions over option labels in a single forward pass. The guardian-core adapter adds safety detection for harmful content. However, the speech encoder works only in English, produces lowercase unpunctuated text, and is not jointly trained with the language model. The decision adapter can handle up to 128 option tokens per request; larger sets need manual chunking.

If you run models on a consumer GPU, say an RTX 4060 or RTX 3060, you can fit Granite Switch 8B in memory and get around forty tokens per second on a 3060. It’s ideal for hobbyists who want a single model that can chat, make decisions, and transcribe speech without managing multiple services. Developers building prototypes that need safety checks or decision probabilities will also find the built-in adapters convenient.

What do you need to run it at home? At 4-bit it takes about 8 gigabytes of memory. The smallest home machine that holds it fully is an RTX 4060. On an RTX 3060 12 GB with 32 gigabytes of RAM it writes about 40 tokens per second. On an RTX 4090 with 64 gigabytes of RAM it writes about 104 tokens per second.

There is no free API for it yet. The weights are open: you can download them from Hugging Face under the Apache 2.0 license. Arena has not ranked it yet: we add the score as soon as the votes arrive.

Compare granite switch 4.1 8b with every free model, and check what your own GPU can run, on FreeLLMArena.