Hero AI Models
Overview
Hero AI does not use a single model for every feature. For default Swimlane-managed routing, inference uses Anthropic Claude on Amazon Bedrock, with a different primary model per feature. Hero AI Native Action defaults to Claude Haiku 4.5. Starting in Turbine 26.4.0, Agents (plan generation, remediation, playbook builder, and component agents) default to Claude Sonnet 5, with Claude Sonnet 4.5 as fallback. Hero AI Companion stays on Claude Sonnet 4.5.
Starting in 26.2.0, you choose the model for each Hero AI Native ActionHero AI Native Action on the Prompt tab (Model Selection), or leave Use Default Model for Claude Haiku 4.5. If a saved modelId is no longer in the available models list (for example after a Custom LLMCustom LLM provider change), the action uses the Small model at run time and shows Previously Selected Model is not available in the action dialog. See When the Saved Model Is Unavailable in Hero AI Native ActionHero AI Native Action.
You can replace Swimlane-managed models with Custom LLMCustom LLM or Turbine Platform installer settings. Swimlane does not charge Hero AI Credits for usage through your Custom LLM models.
Use the sections below for default models by feature, data residency when you pick models, and how tokens convert to credits on Swimlane-managed models.
Default Swimlane Models
For standard Turbine deployments, Swimlane routes these features to the primary Claude model on Bedrock when you use Swimlane-managed routing:
Feature | Default (primary) |
|---|---|
Hero AI Native ActionHero AI Native Action | Claude Haiku 4.5 |
Hero AI CompanionHero AI Companion | Claude Sonnet 4.5 |
Agents (plan generation, remediation, playbook builder, component agents) | Claude Sonnet 5 (fallback Claude Sonnet 4.5) |
Use Default Model on a Hero AI Native ActionHero AI Native Action is Claude Haiku 4.5. Claude Sonnet 5 is the default for Agents. Claude Sonnet 4.5 is the default for Hero AI CompanionHero AI Companion. Sonnet 5 is not offered in the Native Action Model drop-down in Turbine 26.4.
Hero AI Companion uses Claude Sonnet 4.5 on Swimlane-managed routing, as shown in the table above.
Agents use Claude Sonnet 5 for AI SOC plan and remediation flows, Playbook Generation, and related agentic workflows. If Claude Sonnet 5 is unavailable, Swimlane-managed routing falls back to Claude Sonnet 4.5. Hero AI Companion continues to use Claude Sonnet 4.5 and does not support Sonnet 5. If Custom LLM is enabled and the Medium default is Sonnet 5, Companion does not work. Keep Medium on Sonnet 4.5 when users need Companion. You cannot configure Agent or Companion routing in the UI.
Swimlane does not use your content to train or fine-tune these foundation models.
When Defaults Do Not Apply
The table above describes Swimlane-managed default routing. Your environment may use different models when:
Override | Applies to | Details |
|---|---|---|
Custom LLMCustom LLM | Turbine Cloud (LiteLLM) and Turbine Platform (LiteLLM or Custom Bedrock) | Account-level Custom LLM settings replace default Bedrock routing with your proxy or Bedrock inference profiles. Usage through Custom LLM is not billed as Hero AI Credits. |
Turbine Platform Installer (LLM Proxy Settings; Turbine Platform 26.0.4 only) | Turbine Platform on-premises | Environment variables (for example LLM_MODEL_ID_MEDIUM, SWIMLANE_HEROAICHAT__Models__BedRock__Model) can override defaults. Confirm with your Swimlane contact which settings apply in your cluster. |
Hero AI Native Action model selection | Playbooks that set an explicit model on the Prompt tab | Starting in 26.2.0, choose a model in Model Selection or leave Use Default Model (Claude Haiku 4.5). The selected model overrides Swimlane-managed default routing for that action only. See Hero AI Native Action model residency. |
Regional Availability
Residency labels in the tables below describe where inference runs for your Swimlane instance:
Label | Meaning |
|---|---|
US, EU, AU, JP | Inference stays within that geography for your instance. |
Global | Inference may route across AWS Regions when residency rules allow. |
In-region | The model runs in the AWS Region for that Swimlane instance (not a cross-region geo profile). |
N/A | The model is not offered for that instance. |
Default Models (Haiku 4.5 and Sonnet 4.5)
The table below shows where Claude Haiku 4.5 (default when Hero AI Native Action uses Use Default Model) and Claude Sonnet 4.5 (default for Hero AI CompanionHero AI Companion; Agents fallback in 26.4.0) run for each Swimlane instance.
Swimlane instance | Claude Haiku 4.5 | Claude Sonnet 4.5 |
|---|---|---|
usn.swimlane.app | US | US |
us1.swimlane.app | US | US |
gov.swimlane.app | US | US |
uk1.swimlane.app | EU | EU |
de1.swimlane.app | EU | EU |
ca1.swimlane.app | US | US |
au1.swimlane.app | AU | AU |
sg1.swimlane.app | Global | Global |
jp1.swimlane.app | JP | JP |
For AWS Region details within each geo profile, see Geo inference details on the matching model card:
Hero AI Native Action Model Residency (26.2.0)
Starting in 26.2.0, you can select additional models on the Hero AI Native Action Prompt tab. The table below shows residency for each optional model by Swimlane instance. See the residency labels table for US, EU, Global, and In-region.
Model | usn | us1 | gov | uk1 | de1 | ca1 | au1 | sg1 | jp1 |
|---|---|---|---|---|---|---|---|---|---|
Claude Haiku 4.5 | US | US | US | EU | EU | US | AU | Global | JP |
Claude Sonnet 4.5 | US | US | US | EU | EU | US | AU | Global | JP |
OpenAI gpt-oss-20b | In-region | In-region | In-region | In-region | In-region | N/A | In-region | N/A | In-region |
OpenAI gpt-oss-120b | In-region | In-region | In-region | In-region | In-region | N/A | In-region | N/A | In-region |
Gemma 3 27B | In-region | In-region | In-region | In-region | In-region | N/A | In-region | N/A | In-region |
Qwen3 32B | In-region | In-region | In-region | In-region | In-region | N/A | In-region | N/A | In-region |
Claude Sonnet 4.6 | US | US | US | In-region | EU | US | AU | Global | JP |
Claude Opus 4.5 | US | US | US | EU | EU | US | Global | Global | Global |
Claude Opus 4.6 | US | US | US | In-region | EU | US | AU | Global | Global |
For open-weight models, use Regional Availability in Amazon Bedrock to confirm which models are offered in each AWS Region.
How Credits Are Calculated
When Hero AI Credits is enabled for your account and inference uses Swimlane-managed models, Turbine converts token usage into credits.
At a high level:
- The platform records token counts by category: input, output, cache read, and cache write (when caching applies).
- Each category is multiplied by a weight for that model.
- Weighted tokens are divided by the modelβs Tokens per credit rate to produce credit consumption.
For Swimlane-managed Claude models in the catalog (Haiku, Sonnet, Opus), the seeded weights are:
Category | Weight |
|---|---|
Input | 1 |
Output | 5 |
Cache write | 1.3 |
Cache read | 0.1 |
So output tokens count five times as much as input tokens toward credits for those Claude models. Open-weight models in the catalog use similar input weight 1, with output weights of 4.3 (gpt-oss-20b) or 4 (gpt-oss-120b, Qwen3 32B), and 0 for cache categories when caching does not apply.
You do not configure these weights in the product UI.
On the Hero AI Native Action Model drop-down, models can show a secondary line such as Claude / 300 Tokens per Credit so you can compare relative cost when selecting a model. See Hero AI Native ActionHero AI Native Action. Sonnet 5 is filtered out of that drop-down in Turbine 26.4.
Usage (Tokens and Credits)
Hero AI consumption is reported under Admin Panel > Usage:
Report | What it shows |
|---|---|
Hero AI CreditsHero AI Credits | Credit usage and contract caps for the current billing period β Playbook Usage and User Prompts tabs |
Hero AI PromptsHero AI Prompts | Prompt counts by playbook, component, or user |
Hero AI TokensHero AI Tokens | Token volume (input, output, cache read, cache write) |
Model and Tokens Per Credit
When your account uses Hero AI Credits, Turbine converts token usage to credits using the rates below. Tokens per credit is how many tokens of that model equal one credit before category weights are applied. Output tokens count more heavily than input tokens when credits are calculated. Cache read and cache write token counts appear on the Hero AI TokensHero AI Tokens dashboard; you do not configure those weights in the product.
Model | Tokens per credit |
|---|---|
Haiku 4.5 | 300 |
Opus 4.5 | 60 |
Opus 4.6 | 60 |
OpenAI gpt-oss-20b | 4500 |
OpenAI gpt-oss-120b | 2200 |
Qwen3 32B | 2200 |
Sonnet 4.5 | 100 |
Sonnet 4.6 | 100 |
These rates apply to Swimlane-managed models on Turbine Cloud when Hero AI Credits is enabled for your account. Swimlane does not charge Hero AI Credits for usage through Custom LLMCustom LLM.
Credits, prompts, and tokens measure different aspects of Hero AI usage. Use the dashboard that matches the metric you need.