# Models, Page 430 of 464 Source: https://savrn.com/models/page/430 Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- SAVRN Model Hub # Open-Weight Models An open-weight model is an AI model whose trained weights are published for anyone to download. The weights are what the model learned in training. With a copy of them you can run the model on hardware you control and train it further on your own data. Open weights are not the same as open source. Many publishers release the weights without the training data or code, and the license sets what you may do with the model. This library puts each model's full card, architecture, files, license and published evaluations on one page. 11,122Models 3,164Datasets 285Papers 6,792Publishers 11,852Sourced relationships Updated 2026-10-18 · [How the library is built](https://savrn.com/model-hub/methodology) ## Filter Models Task - [Text generation1,362](https://savrn.com/models?task=Text+generation) - [Image and text to text494](https://savrn.com/models?task=Image+and+text+to+text) - [Feature extraction332](https://savrn.com/models?task=Feature+extraction) - [Robotics329](https://savrn.com/models?task=Robotics) - [Text classification293](https://savrn.com/models?task=Text+classification) - [Text to image202](https://savrn.com/models?task=Text+to+image) - [Speech recognition170](https://savrn.com/models?task=Speech+recognition) - [Audio classification157](https://savrn.com/models?task=Audio+classification) - [Image classification135](https://savrn.com/models?task=Image+classification) - [Text to speech130](https://savrn.com/models?task=Text+to+speech) - 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Model · Text generation ### [stormdesk-triage](https://savrn.com/models/stormdesk-triage) [Nathan DeMoss](https://savrn.com/model-publishers/ndemoss28) This qwen3 model was trained 2x faster with Unsloth and Huggingface's TRL library. Open weights apache-2.0 1.7B parameters 40,960 tokens transformers [View model](https://savrn.com/models/stormdesk-triage) Model ### [storydd](https://savrn.com/models/storydd) [Kasivat Tangsakul](https://savrn.com/model-publishers/aruviss) Open weights mit [View model](https://savrn.com/models/storydd) Model ### [streaming-asr](https://savrn.com/models/streaming-asr) [Ebisuke](https://savrn.com/model-publishers/ebisuke) Open weights 824M parameters 8,192 tokens [View model](https://savrn.com/models/streaming-asr) Model ### [streaming-asr2](https://savrn.com/models/streaming-asr2) [Ebisuke](https://savrn.com/model-publishers/ebisuke) Open weights 570M parameters 8,192 tokens [View model](https://savrn.com/models/streaming-asr2) Model ### [streaming-asr3](https://savrn.com/models/streaming-asr3) [Ebisuke](https://savrn.com/model-publishers/ebisuke) Open weights 884M parameters 8,192 tokens [View model](https://savrn.com/models/streaming-asr3) Model · Text generation ### [stride-qwen3-1.7b-allref-correctonly-kl0-local-positive-20260925-resume](https://savrn.com/models/stride-qwen3-1-7b-allref-correctonly-kl0-local-positive-20260925-resume) [Kumar](https://savrn.com/model-publishers/sandeep123) This repository contains the final epoch-4 LoRA adapter from the 1.7B all-reference STRIDE experiment. The base model is Qwen/Qwen3-1.7B, used with thinking disabled during training and evaluation. Each prompt produced eight rollouts. Novelty was computed against eligible steps from all eight rollouts, including correct and incorrect trajectories. Only correct trajectories received the auxiliary STRIDE diversity bonus; incorrect trajectories retained their ordinary outcome/GRPO signal. This adapter uses local-positive step allocation. Use the Qwen chat template with enablethinking=False to reproduce the non-thinking evaluation setting. This is a research adapter for mathematical reasoning.… Open weights apache-2.0 peft [View model](https://savrn.com/models/stride-qwen3-1-7b-allref-correctonly-kl0-local-positive-20260925-resume) Model · Text generation ### [stride-qwen3-1.7b-allref-correctonly-local-positive-20260925](https://savrn.com/models/stride-qwen3-1-7b-allref-correctonly-local-positive-20260925) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE local step credit: all eligible rollouts define novelty; only correct rollouts receive the bonus. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The… Open weights peft [View model](https://savrn.com/models/stride-qwen3-1-7b-allref-correctonly-local-positive-20260925) Model ### [stride-qwen3-1.7b-allref-correctonly-token-uniform-20260925](https://savrn.com/models/stride-qwen3-1-7b-allref-correctonly-token-uniform-20260925) [Kumar](https://savrn.com/model-publishers/sandeep123) Open weights [View model](https://savrn.com/models/stride-qwen3-1-7b-allref-correctonly-token-uniform-20260925) Model · Text generation ### [stride-qwen3-1.7b-nonthinking-stabilized-2048-grpo-20260916](https://savrn.com/models/stride-qwen3-1-7b-nonthinking-stabilized-2048-grpo-20260916) [Kumar](https://savrn.com/model-publishers/sandeep123) GRPO with group-standardized answer correctness, without a STRIDE diversity bonus. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global prompt batch… Open weights peft [View model](https://savrn.com/models/stride-qwen3-1-7b-nonthinking-stabilized-2048-grpo-20260916) Model · Text generation ### [stride-qwen3-1.7b-nonthinking-stabilized-2048-local_positive-alpha05-20260917](https://savrn.com/models/stride-qwen3-1-7b-nonthinking-stabilized-2048-local-positive-alpha05-20260917) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE with nonnegative local step-diversity credit on eligible reasoning tokens. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global prompt batch is… Open weights peft [View model](https://savrn.com/models/stride-qwen3-1-7b-nonthinking-stabilized-2048-local-positive-alpha05-20260917) Model · Text generation ### [stride-qwen3-1.7b-nonthinking-stabilized-2048-local_positive-alpha2-20260916](https://savrn.com/models/stride-qwen3-1-7b-nonthinking-stabilized-2048-local-positive-alpha2-20260916) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE with nonnegative local step-diversity credit on eligible reasoning tokens. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global prompt batch is… Open weights peft [View model](https://savrn.com/models/stride-qwen3-1-7b-nonthinking-stabilized-2048-local-positive-alpha2-20260916) Model · Text generation ### [stride-qwen3-1.7b-nonthinking-stabilized-2048-local_positive-alpha3-20260917](https://savrn.com/models/stride-qwen3-1-7b-nonthinking-stabilized-2048-local-positive-alpha3-20260917) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE with nonnegative local step-diversity credit on eligible reasoning tokens. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global prompt batch is… Open weights peft [View model](https://savrn.com/models/stride-qwen3-1-7b-nonthinking-stabilized-2048-local-positive-alpha3-20260917) Model · Text generation ### [stride-qwen3-1.7b-nonthinking-stabilized-2048-single_step-20260916](https://savrn.com/models/stride-qwen3-1-7b-nonthinking-stabilized-2048-single-step-20260916) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE ablation using one pooled reasoning embedding per eligible response. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global prompt batch is 64… Open weights peft [View model](https://savrn.com/models/stride-qwen3-1-7b-nonthinking-stabilized-2048-single-step-20260916) Model · Text generation ### [stride-qwen3-1.7b-nonthinking-stabilized-2048-token_uniform-20260916](https://savrn.com/models/stride-qwen3-1-7b-nonthinking-stabilized-2048-token-uniform-20260916) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE ablation distributing each response diversity bonus uniformly over its eligible tokens. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global… Open weights peft [View model](https://savrn.com/models/stride-qwen3-1-7b-nonthinking-stabilized-2048-token-uniform-20260916) Model · Text generation ### [stride-qwen3-4b-allref-correctonly-local-positive-20260925](https://savrn.com/models/stride-qwen3-4b-allref-correctonly-local-positive-20260925) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE local step credit: all eligible rollouts define novelty; only correct rollouts receive the bonus. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The… Open weights peft [View model](https://savrn.com/models/stride-qwen3-4b-allref-correctonly-local-positive-20260925) Model · Text generation ### [stride-qwen3-4b-allref-correctonly-token-uniform-20260925](https://savrn.com/models/stride-qwen3-4b-allref-correctonly-token-uniform-20260925) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE token-uniform: all eligible rollouts define novelty; only correct rollouts receive a mass-preserving uniform token bonus. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the… Open weights peft [View model](https://savrn.com/models/stride-qwen3-4b-allref-correctonly-token-uniform-20260925) Model · Text generation ### [stride-qwen3-4b-stabilized-2048-grpo-20260916](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-grpo-20260916) [Kumar](https://savrn.com/model-publishers/sandeep123) GRPO with group-standardized answer correctness, without a STRIDE diversity bonus. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global prompt batch… Open weights peft [View model](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-grpo-20260916) Model · Text generation ### [stride-qwen3-4b-stabilized-2048-local_positive-20260916](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-local-positive-20260916) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE with nonnegative local step-diversity credit on eligible reasoning tokens. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global prompt batch is… Open weights peft [View model](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-local-positive-20260916) Model · Text generation ### [stride-qwen3-4b-stabilized-2048-local_positive-alpha05-20260917](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-local-positive-alpha05-20260917) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE with nonnegative local step-diversity credit on eligible reasoning tokens. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global prompt batch is… Open weights peft [View model](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-local-positive-alpha05-20260917) Model · Text generation ### [stride-qwen3-4b-stabilized-2048-local_positive-alpha2-20260916](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-local-positive-alpha2-20260916) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE with nonnegative local step-diversity credit on eligible reasoning tokens. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global prompt batch is… Open weights peft [View model](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-local-positive-alpha2-20260916) Model · Text generation ### [stride-qwen3-4b-stabilized-2048-local_positive-alpha3-20260917](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-local-positive-alpha3-20260917) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE with nonnegative local step-diversity credit on eligible reasoning tokens. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global prompt batch is… Open weights peft [View model](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-local-positive-alpha3-20260917) Model · Text generation ### [stride-qwen3-4b-stabilized-2048-single_step-20260916](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-single-step-20260916) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE ablation using one pooled reasoning embedding per eligible response. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global prompt batch is 64… Open weights peft [View model](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-single-step-20260916) Model · Text generation ### [stride-qwen3-4b-stabilized-2048-token_uniform-20260916](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-token-uniform-20260916) [Kumar](https://savrn.com/model-publishers/sandeep123) STRIDE ablation distributing each response diversity bonus uniformly over its eligible tokens. Training explicitly renders enablethinking=False, recorded as thinkingmode: false in the scientific contract. The pinned tokenizer and chat template remain unchanged. Use the same explicit keyword at inference, particularly for Qwen3-1.7B, whose default template enables thinking. Every checkpoint in this repository requires explicit nonthinking provenance. This public repository retains every published optimizer-update adapter, including update zero (the initial, untrained adapter). Training is planned for 4 epochs on the same 2,048-question training split as the earlier STRIDE runs. The global… Open weights peft [View model](https://savrn.com/models/stride-qwen3-4b-stabilized-2048-token-uniform-20260916) Model · Audio text to text ### [strixAE](https://savrn.com/models/strixae) [Wujunjie](https://savrn.com/model-publishers/wujunjiehhs) strixAE is an audio-language reasoning agent obtained by applying Group Relative Policy Optimization (GRPO) to Audio-Reasoner and merging the trained weights into a standalone checkpoint. It uses the Qwen2AudioForConditionalGeneration architecture and is intended for audio understanding, structured reasoning, and audio-restoration pipeline decisions. The model is designed for research involving: - audio understanding across speech, music, and environmental sounds; - audio-quality and degradation analysis; - deciding whether candidate restoration operations should be applied or skipped; - selecting and ordering an audio-restoration pipeline; - structured audio reasoning and question… Open weights mit 8.4B parameters 8,192 tokens transformers [View model](https://savrn.com/models/strixae) ## Model Collections Hand-picked starting points, each with the reason it exists. Collection · 4 entries ### [Embedding models for retrieval](https://savrn.com/collections/embedding-models-for-retrieval) Sentence and document embedding models used to build retrieval systems. Dimension and sequence length matter more than size here, and both come from the publisher. [View collection](https://savrn.com/collections/embedding-models-for-retrieval) Collection · 4 entries ### [Models that fit on one accelerator](https://savrn.com/collections/models-that-run-on-one-accelerator) Models whose publisher-reported parameter count puts them within reach of a single accelerator at common precisions. Memory needed depends on precision and serving configuration, so treat the parameter count as the starting point, not the answer. [View collection](https://savrn.com/collections/models-that-run-on-one-accelerator) Collection · 6 entries ### [Open-weight text models worth knowing](https://savrn.com/collections/open-weight-text-models-worth-knowing) Widely used open-weight language models, chosen because each one is a distinct family rather than a variant of the one above it. Selection, not a ranking. [View collection](https://savrn.com/collections/open-weight-text-models-worth-knowing) Collection · 3 entries ### [Speech and audio models](https://savrn.com/collections/speech-and-audio) Recognition and synthesis models, grouped so the two directions are easy to compare. [View collection](https://savrn.com/collections/speech-and-audio) ## Open-Weight Models Explained ### What is an open-weight model? An AI model whose trained weights are published for anyone to download, so it can be run, tested and fine-tuned on hardware the user controls. ### Is an open-weight model the same as open source? Not always. Open weights means the trained model can be downloaded. Open source usually also means the training code and data are available and the license allows broad reuse. Many open-weight models release the weights only. ### Can I use an open-weight model commercially? It depends on the license. Apache 2.0 and MIT allow commercial use. Other licenses limit it, for example to non-commercial use or below a set number of users. Every model page here shows its license. ### How much memory does an open-weight model need? About two bytes per parameter at 16-bit precision, so a 7-billion-parameter model needs roughly 14 GB for its weights, plus memory for the context it processes. Each model page lists its parameter count and the size of its files. ## Related SAVRN Research The hub sits beside SAVRN's market data and infrastructure research: what models cost to run, and what it takes to run them. SAVRN Index ### [What open models cost to run](https://savrn.com/ai-index/pricing/open-models) The same open-weight model priced by every host that serves it, per million tokens. Research Hub ### [Data center trackers and maps](https://savrn.com/data-center-research) Moratoriums, permits, power, water and capital behind the facilities that run these models. Method ### [How the Model Hub is built](https://savrn.com/model-hub/methodology) Sources, evidence labels, refresh behaviour, and the limits of every comparison here.