Featherless to add MiniMax M3.1 Flash model for coding tasks
Singapore AI startup Featherless plans to add MiniMax M3.1 Flash, a 428-billion-parameter model with 23 billion active per token, aimed at coding.
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giftdetect· the right gift in minutesSingapore-based AI startup Featherless is adding MiniMax M3.1 Flash to its platform, with coding as the intended use case, the company said.
According to Featherless, the model has 428 billion parameters in total, of which 23 billion are active for each token it processes. That means only a small share of the network, roughly 5 percent, does the work on any given step of generation.
Why the parameter split matters
The gap between total and active parameters is typical of sparse designs, where a model keeps a very large pool of weights but uses only part of it per token. In practice, this approach can lower the compute needed per response compared with a dense model of the same overall size, which is relevant for developers who run code generation, completion and review at volume.
The "Flash" label in the name suggests a focus on speed and efficiency, though the company has not provided benchmark results or latency figures in the material available.
What is still unclear
Featherless did not detail pricing, a launch date, context length or how the model will be offered to users in the information released so far. Performance on coding benchmarks has also not been disclosed.
For developers, the addition signals that Featherless wants to widen the set of models it offers for programming work, drawing on a model from MiniMax. Teams that choose between hosted models will likely wait for concrete availability and cost details before deciding whether it fits their workflows.
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