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 companion and agents (plan generation, remediation, playbook builder, and component agents) default to sonnet tiers suited to longer reasoning tasks starting in 26 2 0 , you choose the model for each hero ai native action docid\ c4ckmt7fhxgjbtlxxooc2 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 llm docid\ deoy k3jmcpdm c ikrq4 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 action docid\ c4ckmt7fhxgjbtlxxooc2 you can replace swimlane managed models with custom llm docid\ deoy k3jmcpdm c ikrq4 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 companion docid\ crqkfvngpcz wj8xthds7 claude sonnet 4 5 agents (plan generation, remediation, playbook builder, component agents) claude sonnet 4 5 hero ai companion uses claude sonnet 4 5 on swimlane managed routing, as shown in the table above agents use claude sonnet 4 5 for ai soc plan and remediation flows, playbook generation, and related agentic workflows if claude sonnet 4 5 is temporarily unavailable, swimlane managed routing for agent workflows may use another managed claude model hero ai companion does not use that substitution you cannot configure alternate model routing for either feature 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 llm docid\ deoy k3jmcpdm c ikrq4 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 https //docs swimlane com/turbine installer/configure the turbine platform for an embedded cluster install#llm proxy settings ( 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 the selected model overrides swimlane managed default routing for that action only see hero ai native action model residency https //docs swimlane com/hero ai models#hero ai native action model residency 2620 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 companion docid\ crqkfvngpcz wj8xthds7 and agents ) 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 claude haiku 4 5 on amazon bedrock https //docs aws amazon com/bedrock/latest/userguide/model card anthropic claude haiku 4 5 htmlclaude sonnet 4 5 on amazon bedrock https //docs aws amazon com/bedrock/latest/userguide/model card anthropic claude sonnet 4 5 html 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 https //docs swimlane com/hero ai models#regional availability 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 https //docs aws amazon com/bedrock/latest/userguide/models region compatibility html to confirm which models are offered in each aws region usage (tokens and credits) hero ai consumption is reported under admin panel > usage report what it shows hero ai credits docid\ fpbh2j8xm1tfdvejnc8kb credit usage and contract caps for the current billing period β playbook usage and user prompts tabs hero ai prompts docid\ rv7wvn3wx2uwa bchy7ur prompt counts by playbook, component, or user hero ai tokens docid 8g7pp4zuiwuisuvyq32s9 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 tokens docid 8g7pp4zuiwuisuvyq32s9 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 llm docid\ deoy k3jmcpdm c ikrq4 credits, prompts, and tokens measure different aspects of hero ai usage use the dashboard that matches the metric you need