# Myosotis-1-base by FWKV Project: Open-Weight Model Source: https://savrn.com/models/myosotis-1-base Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- ## Runs On What it takes to serve Myosotis-1-base (102M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them. | Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits | | --- | --- | --- | --- | --- | --- | | 16-bit | 0.2 GB | 0.2 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 8-bit | 0.1 GB | 0.1 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 4-bit | 0.1 GB | 0.1 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the [SAVRN Index](https://savrn.com/ai-index/pricing/gpus), read Oct 7, 2026. [Myosotis-1-base on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/myosotis-1-base/gpus) ## Model Card By FWKV Project, published under apache-2.0, revision 392bfa209da1. ### Myosotis-1-base (100M) Myosotis-1-base is the first flagship release from us, introducing a 100-million parameter recurrent language model built on the FWKV architecture. Myosotis-1 is engineered to never truly forget—using a mathematically clamped exponential decay that guarantees an infinite effective context window while maintaining blazing-fast inference on consumer hardware. ### Architecture at a Glance | Component | Specification | | --- | --- | | Type | RWKV-style Gating | | Total Parameters | ~100 Million | | Hidden Dimension (d_model) | 768 | | Embedding Bottleneck (d_emb) | 192 | | Layers (n_layers) | 13 | | FFN Expansion Factor | 4× (GELU activation) | | Context Length | 1024 tokens (packed training) | | Vocabulary | 50,257 (GPT-2 tokenizer | | Weight Tying | Fully tied, factorized input/output head | ### Core Technical Innovations #### 1. The FWKV Recurrent Core Instead of pairwise attention, Myosotis uses a fixed-size state vector updated via a gated linear recurrence: $$ S_t = S_{t-1} \odot W + k_t \odot v_t $$ [Read the full model card (789 words)](https://savrn.com/models/myosotis-1-base/card) ## Configuration Architecture FWKVLanguageModel Vocabulary size 50,257 Model type fwkv ## Identity and Version Repository FWKV/Myosotis-1-base Publisher FWKV Project Task Text generation Modality Text Library transformers Parameters 102M parameters Languages en Revision 392bfa209da18fd749f257740359e8e008067d7b First published 2026-09-01 Last updated 2026-09-24 ## Files and Weights 10 files, 411.0 MB in total. The weights are 1 file totalling 407.5 MB in safetensors. Weights1 file · 407.5 MB Configuration4 files · 10.9 KB Tokenizer2 files · 3.6 MB Documentation2 files · 7.3 KB Repository1 file · 1.5 KB Every file | File | Type | Size | SHA-256 | | --- | --- | --- | --- | | model.safetensors | Weights | 407.5 MB | 191eb88fb1f3 | | config.json | Configuration | 1.1 KB | — | | configuration_fwkv.py | Configuration | 826 B | — | | generation_config.json | Configuration | 172 B | — | | modeling_fwkv.py | Configuration | 8.9 KB | — | | .ipynb_checkpoints/README-checkpoint.md | Documentation | 308 B | — | | README.md | Documentation | 7.0 KB | — | | .gitattributes | Repository | 1.5 KB | — | | tokenizer.json | Tokenizer | 3.6 MB | — | | tokenizer_config.json | Tokenizer | 326 B | — | ## License and Download License apache-2.0 Access Open weights, no gate Download size 407.5 MB [Download from FWKV Project](https://huggingface.co/FWKV/Myosotis-1-base) Released by FWKV Project through its official repository on Hugging Face. [Read the license](https://www.apache.org/licenses/LICENSE-2.0). ## Memory Requirements | Precision | Weights in memory | | --- | --- | | As published | 407.5 MB | | 16-bit | 0.2 GB | | 8-bit | 0.1 GB | | 4-bit | 0.1 GB | Weights only, from the published parameter count; the key-value cache and runtime add to this. ## Questions About Myosotis-1-base ### How much GPU memory does Myosotis-1-base need? About 0.2 GB at 16-bit and 0.1 GB at 4-bit: the weights (102M parameters) plus a working margin. A long context needs more. ### What is the cheapest GPU to run Myosotis-1-base on? At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists. ### Can I use Myosotis-1-base commercially? Yes. Myosotis-1-base is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors. ## Similar Models Model · Text generation ### [uuu_fine_tune_gpt2](https://savrn.com/models/uuu-fine-tune-gpt2) [David Lanz](https://savrn.com/model-publishers/davidlanz) Fine tuning pre-trained language models for text generation. Pretrained model on Chinese language using a GPT2 for Large Language Head Model objective. transferlearning from DavidLanz/uuufinetunetaipower and fine-tuning with medical dataset for the GPT-2 architecture. You can use this model directly with a pipeline for text generation. 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It is a complete, small, from-scratch GPT, with its training… Open weights apache-2.0 98M parameters pytorch [View model](https://savrn.com/models/lmlm-97m-1) ## FWKV Project [All models and datasets](https://savrn.com/model-publishers/fwkv) ## Versions - [392bfa209da1](https://savrn.com/models/myosotis-1-base/versions/392bfa209da1) · current 2026-09-24 ## Explore More - [All text generation models](https://savrn.com/models/tasks/text-generation) - [All models under apache-2.0](https://savrn.com/models/licenses/apache-2-0) - [Model comparisons](https://savrn.com/models/comparisons) - [The model directory](https://savrn.com/models) - [Open model prices by host](https://savrn.com/ai-index/pricing/open-models) ## Source - Repository metadata, read 2026-09-24. - [Hugging Face record](https://huggingface.co/FWKV/Myosotis-1-base) - [How the hub is built](https://savrn.com/model-hub/methodology)