Speck1-140M / Base model
Speck1-140M
An open English base language model for local inference, fine-tuning, and architecture research.
140.7M
Parameters
5B
Pretraining tokens
2,048
Validated context
MIT
Open license
01 / Overview
About Speck1
Base model
Use it for text completion, fine-tuning, or language-model research. For chat-style prompts, use an Instruct checkpoint.
Hybrid network
Grouped-query attention is combined with gated causal convolution to reduce runtime state while retaining global attention.
Local formats
Available as BF16 Safetensors for Transformers and quantized GGUF files for llama.cpp-compatible applications.
02 / Comparison
Size, speed, and memory
Speck1 is shown alongside four similarly sized models. Switch views to compare evaluation score, training budget, inference speed, and memory.
Open SLM Intelligence Index
Higher is better
Score / 30
Pretraining tokens
Lower means fewer tokens
Log scale
Scores use a pinned Open SLM configuration. Speck is not yet a published leaderboard row, and training budgets are not compute-matched.
03 / Before use
Practical notes
Context length
Training and validation used sequences up to 2,048 tokens. The 4,096-token configuration has not been validated.
Capabilities
At 140M parameters, knowledge, reasoning, arithmetic, coding, and multilingual performance are limited.
Safety
The model has no dedicated safety alignment and can produce incorrect, biased, or unsafe text. It is not intended for high-stakes use.
Methodology
Sources
Model details and local performance measurements come from the public model card and repository. Quality scores use a pinned Open SLM evaluation configuration; Speck is not currently a published row in the linked leaderboard snapshot.