--- title: Snowflake Bring Your Own AI Model to AI_COMPLETE: Choose... description: Snowflake's Bring Your Own Model (BYOM) feature lets organizations import custom or open-source models from Hugging Face and use them through the familiar... canonical: https://daily.dev/posts/snowflake-bring-your-own-ai-model-to-ai-complete-choose-the-right-model-for-every-ai-workload-jucwojwmp twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Snowflake Bring Your Own AI Model to AI_COMPLETE: Choose the Right Model for Every AI Workload | daily.dev og:description: Snowflake's Bring Your Own Model (BYOM) feature lets organizations import custom or open-source models from Hugging Face and use them through the familiar... og:url: https://daily.dev/posts/snowflake-bring-your-own-ai-model-to-ai-complete-choose-the-right-model-for-every-ai-workload-jucwojwmp og:image: https://api.daily.dev/og/posts/jUCWojwmp.png og:image:alt: Snowflake Bring Your Own AI Model to AI_COMPLETE: Choose the Right Model for Every AI Workload og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Snowflake Bring Your Own AI Model to AI_COMPLETE: Choose the Right Model for Every AI Workload **[Snowflake Community](https://daily.dev/sources/snowflake_comm)** · 17 min read · 2 upvotes · 0 comments ## Summary Snowflake's Bring Your Own Model (BYOM) feature lets organizations import custom or open-source models from Hugging Face and use them through the familiar AI_COMPLETE SQL function and REST API. The tutorial walks through creating a HuggingFace token, storing it as a Snowflake secret, importing a model via Snowsight, deploying it as an SPCS service, and calling it via SQL or a Streamlit-based Python app. Key benefits include model flexibility for domain-specific workloads (healthcare, finance, code generation), consistent developer experience without application rewrites, faster adoption of new open-source models, improved governance and data residency control, and more predictable GPU-based infrastructure costs compared to per-token pricing. The feature is currently in Private Preview. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### How do I bring my own Hugging Face model into Snowflake and use it with AI_COMPLETE? Create a Hugging Face account and access token, store it as a Snowflake secret using CREATE SECRET with TYPE = GENERIC_STRING, then in Snowsight go to AI & ML > Models > Create > Import Model, select the Hugging Face model (for example GPT-OSS-20B), choose the secret and target schema, then deploy it as a service on a GPU compute pool. Once deployed, call it with AI_COMPLETE using the fully-qualified service name like MODELS.PUBLIC.GPT_OSS_20B_SERVICE. _daily.dev surfaces practical walkthroughs like this for teams evaluating self-hosted models inside Snowflake._ ### Why would I host my own model in Snowflake instead of using Snowflake's built-in Cortex models? Hosting a custom model, known as Bring Your Own Model (BYOM), lets teams choose domain-specific models (medical, financial, code-generation, multilingual, or fine-tuned) for better accuracy, pay for GPU compute instead of token-based pricing, meet stricter governance and data residency requirements, and adopt new open-source models like Llama, Mistral, or Gemma faster than waiting for a managed Cortex release. _daily.dev helps developers weighing custom versus managed model hosting keep track of options like Snowflake BYOM._ ### Why do BYOM SPCS ingress endpoint calls fail with a session token in Snowflake? SPCS public ingress endpoints reject Snowflake session tokens and require a Programmatic Access Token (PAT) for authentication instead. A PAT can be generated in Snowsight under Admin > Users > your user > Programmatic Access Tokens, and configured in .streamlit/secrets.toml or the SNOWFLAKE_PAT environment variable when calling a BYOM service directly via its ingress URL rather than through AI_COMPLETE. _daily.dev keeps developers debugging Snowflake SPCS auth issues close to real implementation detail like this._ ## Similar posts on daily.dev - [Snowflake Unlocks Better AI Economics with Dynamic Model Routing](https://daily.dev/posts/snowflake-unlocks-better-ai-economics-with-dynamic-model-routing-ia2m0zeyl) · SD Times · 0 upvotes · 0 comments - [Hugging Face for Snowflake Data Engineers: A Comprehensive Guide](https://daily.dev/posts/hugging-face-for-snowflake-data-engineers-a-comprehensive-guide-ptrfez54x) · Infostrux · 1 upvotes · 0 comments - [How Snowflake AI Functions Eliminate 80% of Custom Pipeline Code](https://daily.dev/posts/how-snowflake-ai-functions-eliminate-80-of-custom-pipeline-code-pknoewdku) · Snowflake Community · 2 upvotes · 0 comments - [Dynamic Model Routing & Open Models in Snowflake Cortex AI](https://daily.dev/posts/dynamic-model-routing-open-models-in-snowflake-cortex-ai-rfbvecf1g) · Snowflake · 0 upvotes · 0 comments - [Snowflake adds Google Gemini support](https://daily.dev/posts/snowflake-adds-google-gemini-support-0cxkgm4ev) · The Register · 0 upvotes · 0 comments --- Tags: [#llm](https://daily.dev/tags/llm), [#snowflake](https://daily.dev/tags/snowflake), [#ai-inference](https://daily.dev/tags/ai-inference) [View this post on daily.dev](https://daily.dev/posts/snowflake-bring-your-own-ai-model-to-ai-complete-choose-the-right-model-for-every-ai-workload-jucwojwmp) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Snowflake Bring Your Own AI Model to AI_COMPLETE: Choose the Right Model for Every AI Workload","url":"https://daily.dev/posts/snowflake-bring-your-own-ai-model-to-ai-complete-choose-the-right-model-for-every-ai-workload-jucwojwmp","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/snowflake-bring-your-own-ai-model-to-ai-complete-choose-the-right-model-for-every-ai-workload-jucwojwmp"},"datePublished":"2026-07-07T21:08:40.110Z","dateModified":"2026-09-13T20:15:51.708Z","description":"Snowflake's Bring Your Own Model (BYOM) feature lets organizations import custom or open-source models from Hugging Face and use them through the familiar...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/e0dd32dc94be79e396cf7138570e9648?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/e0dd32dc94be79e396cf7138570e9648?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Snowflake Community","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Snowflake Community","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/3eb5260f70bb4653be0f9581c0d937c8","url":"https://daily.dev/sources/snowflake_comm"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/snowflake-bring-your-own-ai-model-to-ai-complete-choose-the-right-model-for-every-ai-workload-jucwojwmp","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":2},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"llm,snowflake,ai-inference","timeRequired":"PT17M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Snowflake Community","item":"https://daily.dev/sources/snowflake_comm"},{"@type":"ListItem","position":3,"name":"Snowflake Bring Your Own AI Model to AI_COMPLETE: Choose the Right Model for Every AI Workload"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/snowflake-bring-your-own-ai-model-to-ai-complete-choose-the-right-model-for-every-ai-workload-jucwojwmp#faq","mainEntity":[{"@type":"Question","name":"How do I bring my own Hugging Face model into Snowflake and use it with AI_COMPLETE?","acceptedAnswer":{"@type":"Answer","text":"Create a Hugging Face account and access token, store it as a Snowflake secret using CREATE SECRET with TYPE = GENERIC_STRING, then in Snowsight go to AI & ML > Models > Create > Import Model, select the Hugging Face model (for example GPT-OSS-20B), choose the secret and target schema, then deploy it as a service on a GPU compute pool. 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