LLMopenaiPlan: Pro and up

OpenAI: GPT-5.6 Terra Pro

GPT-5.6 Terra Pro is the same underlying model as [GPT-5.6 Terra](https://openrouter.ai/openai/gpt-5.6-terra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

Anyone in the Project can @-mention OpenAI: GPT-5.6 Terra Pro with the team's shared context - pooled credits, one chat, one memory.

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Verdict

GPT-5.6 Terra Pro delivers OpenAI's largest context window yet at 1.05M tokens, making it the go-to for processing entire codebases, legal document sets, or multi-hour transcripts in a single pass. The $1/$6 per Mtok pricing sits between o1 and GPT-4o, positioning it as a mid-tier option for long-context work. Reach for this when you need to reason across massive inputs without chunking, but expect to pay more than GPT-4o for comparable short-context tasks.

Best for

Processing entire codebases in one context
Multi-document legal or compliance review
Analyzing full-length transcripts or manuscripts
Cross-referencing large knowledge bases
Long-context reasoning without RAG overhead

Strengths

The 1.05M token window is the largest in OpenAI's lineup, enabling true whole-repository analysis or multi-file reasoning without retrieval augmentation. Multimodal support extends this to image-heavy documents like technical manuals or design specs. At $1 input per Mtok, it undercuts o1-preview for bulk ingestion while maintaining GPT-4-class reasoning. The file modality handles PDFs and structured data natively, reducing preprocessing overhead for document-heavy workflows.

Trade-offs

Without public benchmarks, performance on standard evals remains unverified — early adopters are flying blind relative to Claude 3.5 Sonnet or Gemini 1.5 Pro on MMLU or HumanEval. The $6 output cost is 6x the input rate, penalizing verbose responses or iterative drafting. For short-context tasks under 32K tokens, GPT-4o delivers similar quality at half the price. The proprietary license locks you into OpenAI's API with no self-hosting or fine-tuning path.

Specifications

Provider: openai
Category: llm
Context length: 1,050,000 tokens
Max output: 128,000 tokens
Modalities: file, image, text
License: proprietary
Released: 2026-07-09

Pricing

Input: $2.00/Mtok
Output: $12.00/Mtok
Model ID: openai/gpt-5.6-terra-pro

Per-token prices show what the model costs upstream. On Switchy your team draws from one shared org credit pool - one plan, one balance for everyone.

Team cost calculator

Seats5 peopleMessages / seat / day80Avg turn size2 ktokOutput share30 %

Estimated monthly spend

$88.00

17.6M tokens / month
5 seats · 80 msgs/day

Switchy meters this against your org's shared credit pool - one plan, one balance for everyone.

Providers

Provider-level routing data is not available yet for this model.

Performance

Performance snapshots are collected daily. Check back after the next ingestion run.

Benchmarks

Public benchmark scores are not available yet for this model. Check back after the next ingestion run.

Works well with

Top MCPs

Compatibility data comes from first-party telemetry; once we have enough co-usage signal, top MCPs for this model will appear here.

How Switchy teams use it

Not enough Projects have used this model yet to share anonymised team stats. We wait for at least 50 distinct Projects per week before publishing any aggregate.

Starter prompts

Codebase Architecture Review

Review this codebase for architectural issues. Identify tight coupling, circular dependencies, and code that violates single responsibility. Provide a prioritized refactoring roadmap with file-specific recommendations.

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Multi-Contract Compliance Check

Compare these contracts and flag any conflicting obligations, missing standard clauses, or terms that create legal risk. Cite specific sections and explain the conflict in plain language.

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Full Transcript Insight Extraction

Extract all decisions, action items, and unresolved questions from this transcript. Group by topic and note who committed to each action. Flag any contradictory statements made across the discussion.

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Technical Manual Q&A

Using this full manual, explain the step-by-step troubleshooting process for [specific issue]. Reference relevant diagrams and part numbers, and note any safety warnings that apply.

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Research Paper Synthesis

Synthesize the findings from these papers on [topic]. Identify areas of consensus, conflicting results, and gaps in the research. Suggest three specific follow-up studies that would address the most critical unknowns.

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