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PrivacyNon-sensitive inputsDeploymentHosted service allowedScaleOccasional to moderate volumeLatencyInteractive, not real-timeBudgetBalanced quality and costReliabilityHuman review for consequential output
Refine these assumptions in the Calibration Room

3 candidates. No automatic winner.

These are dated starting points under the disclosed defaults. Evaluate these approaches against your workload.

Quality & reliability

GPT-5.6 Sol

Inside: direct model call

LifecyclecurrentVerified2026-08-27Evidence1 provider source + RS interpretationStatuscurrent

A strong starting point when editorial quality and difficult revision judgment matter.

TradeoffHigher unit cost than balanced and local alternatives.

Why?
  • supports write
  • accepts text
  • fits quality-reliability
Go deeper

This approach joins the release gpt-5.6-sol to the deployment offer openai-gpt-5-6-sol-api. The recommendation is dated RS interpretation, not a provider ranking.

Technical details

Modalities: text, image. Access: proprietary. Evidence class: rs-interpretation.

Evaluation plan

  1. Use ten representative drafts.
  2. Blind-review accuracy and voice.
  3. Record revision time latency and cost.
Inspect the model recordProvider source

Speed & cost

GPT-5.6 Terra

Inside: direct model call

LifecyclecurrentVerified2026-08-27Evidence1 provider source + RS interpretationStatuscurrent

A balanced hosted starting point for frequent writing and revision.

TradeoffTest nuanced editorial judgment against the quality-first candidate.

Why?
  • supports write
  • accepts text
  • fits speed-cost
Go deeper

This approach joins the release gpt-5.6-terra to the deployment offer openai-gpt-5-6-terra-api. The recommendation is dated RS interpretation, not a provider ranking.

Technical details

Modalities: text, image. Access: proprietary. Evidence class: rs-interpretation.

Evaluation plan

  1. Use ten representative drafts.
  2. Compare human revision effort.
  3. Record latency and cost.
Inspect the model recordProvider source

Control & locality

gpt-oss-20b

Inside: direct model call

LifecyclecurrentVerified2026-08-27Evidence1 provider source + RS interpretationStatuscurrent

A local starting point when data custody and inspectable deployment matter.

TradeoffLocal operation shifts performance tuning and infrastructure to you.

Why?
  • supports write
  • accepts text
  • fits control-locality
Go deeper

This approach joins the release openai/gpt-oss-20b to the deployment offer openai-gpt-oss-20b-local. The recommendation is dated RS interpretation, not a provider ranking.

Technical details

Modalities: text. Access: open-source. Evidence class: rs-interpretation.

Evaluation plan

  1. Run on intended hardware.
  2. Compare output quality with a hosted baseline.
  3. Measure operator effort and throughput.
Inspect the model recordProvider source
See what did not enter this shortlist

No additional approaches were evaluated for this job.