Now LLM Service updates
Summarize
Summary of Now LLM Service updates
The Now LLM Service offers access to specialized large language models (LLMs) developed by ServiceNow as well as selected and enhanced open-source models from the ServiceNow community and partners. These models support a variety of AI-driven language tasks such as text generation, summarization, conversational AI, and content moderation within ServiceNow workflows. Model cards provide detailed information about each model’s use cases, training data, and limitations, enabling teams to select the appropriate LLM for their needs.
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Recent Releases and Key Changes
- July 2026: Introduced new third-party models including Google Gemini 3.5 Flash (replacing Gemini 2.5 Flash), OpenAI GPT 5.1, and GPT 5.4 Mini. Now LLM is no longer the default model; teams must choose a small third-party model as default. Explicit model names are now required in prompt and AI configuration records. Large model usage requires an exception request.
- June 2026: Updated third-party default model versions with GAIC 13.1.2 required. The GPT-5 Mini’s default reasoningeffort setting changed from none to minimal, necessitating regression and functional testing. Claude Sonnet 4.0 has been retired with automatic backend redirection to Claude 4.5 Sonnet. Now LLM long-term support SKU was retired without impact on teams.
- May 2025: Released an advanced 12B general-purpose small language model fine-tuned on Mistral-Nemo-12B-Instruct, optimized for ServiceNow-specific tasks like Agent Assist, Text-to-Flow, Text-to-Cypher, Safety & Content Moderation, and Text-to-Code. Key enhancements include improved instruction adherence, doubled context window (16K to 32K tokens), enhanced multilingual support (notably Japanese), and consolidation of multiple capabilities into a single high-performance model.
- March 2025: Introduced a powerful 12B small language model fine-tuned on Mistral-Nemo-12B, improving case and chat summarization, resolution notes, and knowledge base generation. Enhanced text-to-code and text-to-cypher accuracy, robust content moderation against adversarial prompts, and unified deployment to reduce complexity and improve performance.
- November 2024: Added multilingual support for 8 additional languages (e.g., German, French, Japanese, Spanish, Italian). Introduced JSON output format for deterministic, structured responses—enhancing integration reliability and lowering token consumption. Instruction adherence improvements enable more precise and actionable outputs.
Practical Implications for ServiceNow Customers
- Customers can leverage a variety of ServiceNow-developed and third-party LLMs tailored for enterprise workflows, including natural language understanding, automation, content generation, and content moderation.
- Explicit model selection and configuration are now mandatory; generic references are deprecated. Teams must update AI configuration records accordingly to ensure compatibility with new releases.
- Default model shifts to small third-party LLMs require customers using large models to follow an exception process, emphasizing optimization and cost-efficiency.
- Model improvements such as extended context windows and enhanced instruction adherence help achieve more accurate, coherent, and context-aware AI responses within ServiceNow workflows.
- Support for multiple languages and structured JSON output format facilitates global deployments and seamless integration into existing applications and automation pipelines.
- Ongoing retirement of legacy models and SKUs (e.g., Now LLM LTS, Claude Sonnet 4.0) requires customers to stay current with model upgrades to maintain support and performance.
The Now LLM Service provides access to specialized large language models (LLMs) that are developed by ServiceNow. It also provides access to open-source LLMs that are selected, configured, or enhanced by ServiceNow, from the ServiceNow community and partners. Review these reference materials and model cards for additional information about the Now LLM Service and about the models used.
Model cards
Large language models (LLMs) are complex machine-learning models that are trained on large datasets like websites and documentation to perform language-related tasks, such as text generation for case summaries and resolution notes.
Model cards explain the specific model's context, intended use, training data, limitations, and other important information.
These model cards are for skills that use the Now LLM Service. There are certain skills, such as Now Assist Multi-Turn Catalog Ordering, that use Azure OpenAI instead. To see what LLM a skill is using, you can check the skill list in the AI Admin Hub console and review the LLM service column.
- Model card for ServiceNow large language model
- Model used for AI-driven solutions to support natural language understanding, automation, and decision support.
- Model card for ServiceNow large language model (V2)
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Model for enterprise AI that enhances text-based automation and content generation in ServiceNow workflows, including requester OOTB skills, custom skills, and agentic use cases.
This model is for Generative AI Controller application 11.2 or higher.
- Model card for ServiceNow small language model
- Model used for enterprise AI applications by enhancing text-based automation and content generation within ServiceNow workflows.
- Model card for ServiceNow small language model (V2)
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Model for enterprise AI that enhances text-based automation and content generation in ServiceNow workflows, including creator and fulfiller OOTB skills as well as custom skills.
This model is for Generative AI Controller application 11.2 or higher.
- Model card for ServiceNow third party large language model
- Model used for AI-driven solutions for text generation, summarization, and conversational AI.
- Model card for ServiceNow Voice AI Speech-to-Text and Text-to-Speech models
- Models used within ServiceNow AI Voice Agents for converting spoken user input to text and generating natural-sounding speech from AI responses.
- Model card for ServiceNow AI Guardian model
- This model provides content moderation and helps identify different kinds of prompt injection attacks and offensive content.
- Model card for ServiceNow Inferred CSAT and Factors large language model
- This model is designed to ingest a conversation and predict a CSAT score as well as factors that explain the predicted score.
July 2026
The July release introduces three new third-party models and shifts the platform default away from Now LLM. Teams must update their generative AI configuration records to reflect these changes.
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New model offerings: The following models are introduced and supported in the July release.
- Google Gemini 3.5 Flash, which replaces Gemini 2.5 Flash
- OpenAI GPT 5.1
- OpenAI GPT 5.4 Mini
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Third-party provider required as default: As of the July release, Now LLM must not be the default model for skills or agents. Teams should select an optimal small third-party model as their default. The Generative AI Controller version required to route to the new July models will be announced separately.
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Large model exception: Teams that require a large model must request an exception and demonstrate that no small model is a viable option. The exception process is expected to follow the prior process format, with an updated form and test reference materials. Final details are pending PM approval.
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Explicit model names required: Generic model references such as
cloud_smallandcloud_largeare no longer supported. Teams must update prompt configuration records and generative AI config records to use explicit model names.
June 2026
The June release includes updates to third-party model defaults, a change to the default reasoning effort setting for GPT-5 Mini, and the retirement of the Now LLM long-term support (LTS) SKU.
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Third-party default model version update: Teams that did not update their third-party default model versions to the latest available versions in the May release must do so in the June release. GAIC 13.1.2 is the required version for this update.
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GPT-5 Mini:
reasoning_effortdefault change: The defaultreasoning_effortsetting for GPT-5 Mini has changed fromnonetominimal. This change is included in GAIC Snapshot 14.0.0, which is compatible with Now Assist for Platform 12.0.0.Teams using GPT-5 Mini should run regression and functional testing to confirm that the new default works as expected. If you explicitly set
reasoning_effortin your generative AI config additional properties, smoke test to verify there are no unexpected effects. If you havereasoning_effort: noneset in additional properties, update the value tominimaland run regression and functional testing. -
Claude Sonnet 4.0 retirement: Claude Sonnet 4.0 references are being redirected on the backend. No team action is required.
claude_large/ Claude 4.0 Sonnet redirects to Claude 4.5 Sonnetclaude_small/ Claude 4.0 Sonnet redirects to Claude 4.5 Sonnet
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Now LLM LTS SKU retired: ServiceNow no longer offers the LTS model SKU. There are no testing requirements or expectations for teams related to this retirement.
May 2025
An advanced 12B general-purpose small language model (SLM) with a singular, high-performance architecture that supports a wide range of tasks in ServiceNow’s context was released. Fine-tuned on Mistral-Nemo-12B-Instruct, this model is designed and optimized for tasks like Agent Assist, Text-to-Flow, Text-to-Cypher, Safety & Content Moderation and Text-to-Code.
- Enhanced instruction adherence: Improved the model’s capability to accurately interpret and follow user instructions, ensuring that the model can better understand and execute complex commands. Leading to more precise and reliable outcomes than previous releases.
- Increased context window: increased context window from 16K to 32K, enabling the model to better understand long-form inputs, maintain coherence over extended interactions, and support more complex tasks with richer contextual awareness.
- Improved multilingual proficiency: Boosted performance across languages compared to previous releases, with notable enhancements in Japanese processing.
- Optimized for ServiceNow workflow related capabilities: Extended support coverage for Text-to-Flow, and improved the performance of Text-to-Code, Text-to-Cypher etc.
- Continuously enhanced model deployment consolidation: Integrates ServiceNow-related tasks into a single model, reducing system complexity at the same time while elevating overall performance.
March 2025
A powerful 12B general-purpose small language model (SLM) designed to enhance a wide range of applications, including text-to-code and agent use cases was released. Fine-tuned on Mistral-Nemo-12B, it streamlines deployment and consolidates multiple functionalities into a singular, architecture.
- Optimized to fulfill use cases: Enhances case summarization, chat summarization, resolution notes, and knowledge base generation across supported languages, including improvements in Japanese quality.
- Superior text-to-code and text-to-cypher performance: Delivers major advancements in Glide JavaScript and generic JavaScript editing and generation, along with improved accuracy in query generation and execution for structured databases.
- Robust content moderation and safety: Provides stronger protection against adversarial prompts, jail-breaking attempts, and harmful content generation, ensuring safer deployment with built-in content filtering.
- Unified model deployment:integrates ServiceNow-related tasks into a single model, thereby reducing system complexity while elevating overall performance.
- Improved instruction adherence: Delivers better instruction following and consistency across varying levels of prompt and instruction strictness than the current text-to-text NowLLM.
November 2024
Several key improvements were added to the Now LLM Service that are aimed at enhancing performance and quality.
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Multilingual support: Now LLM Service supports 8 additional languages, enabling global teams to use the model in their native languages.
The supported languages are: English, German, French, Japanese, Dutch, French Canadian, Spanish, Brazilian Portuguese, and Italian.
- JSON format support: The model now provides output in JSON format, making it easier for developers to integrate with various applications and automate workflows seamlessly.
- Deterministic responses: JSON mode ensures structured, consistent output, which improves predictability and reliability when integrating with applications.
- Error reduction: Unlike free-form text mode, JSON responses are less prone to format errors or stray characters, minimizing integration issues.
- Lower token consumption: The fixed structure of JSON can reduce token usage, making it more efficient and cost-effective for applications with high response frequency.
- Improvements in instruction following: The model has been fine-tuned to understand and follow instructions more precisely. This enables the model to deliver more to-the-point and actionable responses, helping users get the information they need faster and more efficiently.