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INTELLIGENCE, WELL DIRECTED.

Less choosing.
More doing.

Every task deserves
its own intelligence.

We train Aster to recognise what your task needs—and choose which model takes it on.

Meet aster-work & aster-code
ASTER / DECISION FIELD
aster-code / INCOMING TASKReview this pull request
Matched to Claude

Some tasks need a frontier model. Others don’t. You shouldn’t have to work out which. Using a frontier model for everything gets expensive. Always choosing the cheapest can compromise the result. The Aster Model uses intelligent algorithms trained to consider each task and its context, then select the model for that step.

We train
the decision.

Aster Router is our purpose-trained model for choosing which intelligence takes on your task.

A routing policy trained with reinforcement learning—using the task, its context and the cost of the next move.

A TASK ARRIVES

Code reviewFind the bug across these files
Tools & skills Repository + tool results Task requirements
RL TRAINING
Aster RouterTASK-AWARE ROUTING POLICY
Outcomes inform the next decision

THE RIGHT INTELLIGENCE

Claude
GPT
Gemini
Muse
Mistral
Nemotron
Matched to Claude
TRAIN ON THE WORK

Real task data + model outcomes.
Our own model, trained for model choice.

ADAPT TO WHAT’S NEXT

New models. More feedback.
Real-time adaptation is our research direction.

<500ms

Routing latency target

The cost of getting
the task done.

Estimated costs as a coding conversation grows to 100 turns, compared across five options.

  • Fable 5.1
  • GPT-6 Astra
  • Gemini
  • Open-source mix
  • Aster

Cost over 100 coding turns

Estimated total API cost · USD

Estimated total API cost across a growing coding conversationAdjustable preview estimates. Astra, Gemini and the open-source mix use manually selected totals, not published-rate calculations. Conversation length increases from 10 to 100 turns. Claude Fable 5.1: $2.70 to $117.00; GPT-6 Astra: $2.12 to $92.00; Gemini 3.8 Flash: $0.35 to $15.00; Mix OpenSource Models: $0.44 to $20.00; Aster: $0.19 to $9.12. A table following the charts contains every estimate.

Conversation turns

Task success rate

Unverified estimates · at 100 turns per task

Estimated share of tasks completed successfullyUnverified estimates, not benchmark results. Claude Fable 5.1: 94%; GPT-6 Astra: 93%; Gemini 3.8 Flash: 79%; Mix OpenSource Models: 73%; Aster: 94%. All bars share a zero-to-100 percent scale.

Successfully completed / attempted tasks

At 100 conversation turns Adjusted cost estimates · task success is unverified

  • Claude Fable 5.1
    Total cost
    $117.00
    Task success*
    94%
  • GPT-6 Astra
    Total cost
    $92.00
    Task success*
    93%
  • Gemini 3.8 Flash
    Total cost
    $15.00
    Task success*
    79%
  • Mix OpenSource Models
    Total cost
    $20.00
    Task success*
    73%
  • Aster
    Total cost
    $9.12
    Task success*
    94%
Adjustable total API cost estimates in USD, by coding conversation length
Conversation turnsClaude Fable 5.1GPT-6 AstraGemini 3.8 FlashMix OpenSource ModelsAster
10$2.70$2.12$0.35$0.44$0.19
20$7.40$5.82$0.95$1.23$0.54
30$14.10$11.09$1.81$2.36$1.06
40$22.80$17.93$2.92$3.84$1.73
50$33.50$26.34$4.29$5.67$2.56
60$46.20$36.33$5.92$7.84$3.55
70$60.90$47.89$7.81$10.36$4.70
80$77.60$61.02$9.95$13.23$6.02
90$96.30$75.72$12.35$16.44$7.49
100$117.00$92.00$15.00$20.00$9.12

Why the cost grows
with each turn.

You’re paying for more than your latest message. Each follow-up can carry the conversation, instructions, tools, skills and earlier results. A short request can arrive with a very long history.

Aster Context Method

Our method combines reinforcement learning algorithms with task analysis, caching and context management to shape each request and model choice.

  • Caching

    Reusable prompt prefixes, with cache handling that respects provider and model boundaries.

  • Task-aware routing

    Task intent, complexity and tool requirements inform model selection.

  • Context-aware selection

    Relevant history, instructions and dependencies shape the context sent to the model.

  • RL training & real-time feedback

    Reward signals from task outcomes and real-time feedback inform routing-policy refinement.

ACCUMULATED CONTEXT

System instructions
Tools & skills
Relevant history
Stale tool output
Unrelated history
Current task

SELECTED CONTEXT

System instructions
Tools & skills
Relevant history
Current task
A focused request, ready for the selected model.
TASK-RELEVANT CONTEXT PER TURN

Frontier models are
part of Aster.

A difficult step can still go to Astra, Fable or Gemini. The context system is designed to reduce what that model needs to process, while the router selects a suitable model for each step.

FROM OUR CURATED COLLECTION

  • AstraOpenAI
  • FableAnthropic
  • GeminiGoogle
And more.

Model availability depends on the product and enabled route.

Your work.
One model name.

Aster’s curated collection, ready to use.
Choose your product. We handle model selection.

YOUR NEXT REQUESTJSON
{
  "model": "aster-code",
  "messages": [{
    "role": "user",
    "content":
      "Find and fix the failing test in this repository."
  }]
}
20curated models.
And growing.
  • OpenAI
  • Anthropic
  • Google
  • Meta
  • NVIDIA
  • Mistral
  • Kimi
  • Z AI
  • Qwen
  • DeepSeek
  • MiniMax

Availability depends on the product and enabled route.

Your app. Your agent.
Same Aster.

Build with our API, or connect the agent you already use. Aster handles the model choice.

Build on the API.

For your apps, products and workflows.

Explore the API

Connect your agent.

Keep your tools. Let Aster choose the model behind them.

  1. Set your
    endpoint

  2. Add your
    Aster key

  3. Choose
    aster-code

View setup guide

FIND YOUR AGENT

Explore provider setup

IN DEVELOPMENT

Your keys.
Our intelligence.

Bring your provider keys. Build your model group.
Put Aster Router in charge of the choice.

Read about our research
Aster Router
YOUR PROVIDERS · YOUR MODELSOUR ROUTING POLICY

Pay providers directly.
Pay Aster for the intelligence in between.

INTELLIGENCE, WELL DIRECTED.

Bring the work.
We’ll find the intelligence.

Start with Aster