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Orchestra vs Martian

Martian
An AI research lab whose products include a lightweight model gateway and Ship, lower-cost models matched to frontier models.1,2,5
Orchestra
Measures every workflow against your definition of success, improves each one, and trains models your team owns.8

Side by side

Orchestra and Martian compared on 5 dimensions
Primary jobMartianMartian is a research lab focused on understanding machine intelligence. Its products include the Martian Gateway, one API for 200+ models, and Ship, which matches a reference model such as Claude Opus at half the price.1,2,5OrchestraEvaluates production work, improves the prompts and routes behind it, and trains specialist models your team owns.8
Who it servesMartianEngineering and machine learning teams that want a research partner for deep or custom work.OrchestraEvery department, from technical and non-technical product teams to engineering and machine learning teams.
How you connectMartianThe gateway works with existing OpenAI and Anthropic SDKs, and you name the model in each request. To use Ship, you change the model name to its ship-like version.3,4,6OrchestraExisting OpenAI or Anthropic SDK with an Orchestra API key and the gateway base URL. Approved changes roll out gradually with the prior route kept as a fallback.8
Evaluation approachMartianShip is graded against its reference model on public benchmarks and on how closely its behavior matches. The gateway dashboard shows usage, model performance, and request history.6,3OrchestraBuilds task-specific benchmarks, such as whether the model updated the right record or followed your policy, and compares models on the same held-out work.8
Model trainingMartianShip models follow reference models Martian chooses, such as Claude Opus 5 and GPT 5.6 Sol. Martian also publishes open-source research tools for RL training and for steering model behavior.5,6,2OrchestraTrains specialist models from accepted traces and expert corrections.8

Martian is a research lab first.Orchestra is a platform for every team.

Martian's products come out of its research, and its depth is best used on research projects. Orchestra measures and improves the AI work across your company.

What Martian offers

  • Research focused on understanding machine intelligence.1
  • The Martian Gateway: one API key and one endpoint for 200+ models.3
  • Ship: models graded to match a reference model at half its price, backed by a quality SLA.5
  • Open-source tools for RL training and for steering model behavior.2

What Orchestra offers

  • Support for every department, technical and non-technical.
  • Builds task-specific benchmarks, such as whether the model updated the right record or followed your policy, and compares models on the same held-out work.8
  • Repairs prompts, schemas, parsers, and tool contracts first. For a recurring task, trains a specialist from accepted traces and expert corrections.8
  • Trains specialist models from accepted traces and expert corrections.8

Where Orchestra is different

  1. A platform for every team

    Orchestra serves technical and non-technical product teams, engineering, and machine learning teams in the same place. Martian is best engaged as a research partner for deep engineering or custom work.

  2. Quality defined by your work

    Ship is graded against a reference model's benchmarks and behavior. Orchestra grades every workflow against what success means for your work.6,8

  3. Models that keep up

    Each Ship model is tied to a reference model Martian chose and has to be maintained as new models arrive. Orchestra compares the leading models on your own work and trains specialists from your accepted traces.5,8

When each approach makes sense

  • Martian makes sense when

    • Your machine learning team wants a research partner for deep or custom engineering work.
    • You want a lower-cost match for one frontier model, such as Claude Opus, with a quality guarantee.5

  • Orchestra makes sense when

    • You want to optimize inference across every workflow, not one model at a time.
    • Teams across the company, technical and non-technical, rely on AI in production.
    • You know what you want from the work, and every change is checked against that goal on your own examples.8
    • You want to improve prompts and routes, then train a specialist you own.8

  • Both can be part of the stack when

    • You use Martian models, such as Ship, through Orchestra's gateway.

Orchestra case studies

  • Orchestra case study

    Teaching a CRM agent to finish the job

    75.5%

    lower model cost than Sonnet 4.6

    Model spend per seven-task AutomationBench CRM run: $0.27 for Qwen 3.6 Plus with a revised prompt, $1.12 for Sonnet 4.6. The revised prompt also scored 13.1% higher on mean task score.

    Read the story
  • Orchestra case study

    Cutting response times for everyday operations

    5.2×

    faster median model response than Sonnet 4.6

    The small model passed every task check on 92.2% of attempts; Sonnet passed 100%. Both ran 30 AutomationBench workflows, with 90 attempts per model.

    Read the story
  • Orchestra case study

    Finding purchase intent in 40,000 comments

    $2.82

    model cost for 39,962 comments

    An Orchestra post-trained 30B open model labeled 39,962 YouTube comments from a Snowflake table and returned 39,949 valid outputs. Sonnet cost $12.48 on the same table.

    Read the story

These are Orchestra experiments that compare models on specific workloads. None of them compare Orchestra with Martian.

Sources (11)Show

Sources reviewed October 2026. Martian statements come from its own website and documentation. If something is not described there, we say so instead of assuming it is missing.

  1. 1.Martian homepage: Understanding intelligence withmartian.com (opens in a new tab)
  2. 2.Martian documentation: Overview docs.withmartian.com (opens in a new tab)
  3. 3.Martian documentation: Gateway docs.withmartian.com/gateway (opens in a new tab)
  4. 4.Martian documentation: API endpoints docs.withmartian.com/api-reference/endpoints (opens in a new tab)
  5. 5.Martian on LinkedIn: Announcing Ship (July 2026) www.linkedin.com/posts/withmartian_announcing-ship-an-endpoint-with-the-highest-activity-7485409783286738944-Zxgz (opens in a new tab)
  6. 6.Thesean blog: Ship for Claude Opus 5 (July 2026) www.thesean.ai/blog/ship-claude-opus-5 (opens in a new tab)
  7. 7.Orchestra homepage
  8. 8.Orchestra platform
  9. 9.Case study: Teaching a CRM agent to finish the job
  10. 10.Case study: Cutting response times for everyday operations
  11. 11.Case study: Finding purchase intent in 40,000 comments

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