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OpenAI: GPT-5.6 Terra

GPT-5.6 Terra is a balanced model in OpenAI's GPT-5.6 series, positioned between the flagship Sol tier and the cost-efficient Luna tier. It is suited for everyday coding, reasoning, and agentic...

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

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Verdict

GPT-5.6 Terra 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 undercuts GPT-4o on input while matching it on output, though we're still waiting on public benchmarks to confirm reasoning quality at scale. Reach for this when context length is your bottleneck and you need OpenAI's multimodal tooling.

Best for

Processing entire codebases in one context
Multi-document legal or compliance analysis
Long-form transcript summarization and QA
Cross-referencing large technical documentation sets
Vision tasks across dozens of screenshots

Strengths

The 1.05M token window is 2.6× larger than GPT-4o's 400K, letting you load full repositories or 50+ PDFs without chunking. Input pricing at $1/Mtok is half of GPT-4o's rate, making high-volume document ingestion economical. Native file and image handling means you can drop in spreadsheets, diagrams, and screenshots alongside text without preprocessing. OpenAI's function calling and structured output modes carry over, so existing GPT-4 integrations migrate cleanly.

Trade-offs

Without published benchmarks, we can't yet compare reasoning quality to Claude 3.7 Sonnet or Gemini 2.0 Flash Thinking on complex tasks. The $6/Mtok output cost matches GPT-4o, so long-form generation gets expensive fast—Claude 3.7 Sonnet charges $15/Mtok but may justify the premium on nuanced writing. Early adopters report occasional attention degradation past 800K tokens, though OpenAI hasn't confirmed this publicly. If you need proven performance on MMLU-Pro or HumanEval, wait for third-party evals.

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

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 Dependency Audit

I've uploaded our entire Python codebase (47 files). List every third-party package imported, then identify any packages in requirements.txt that are never actually imported in the code.

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Multi-Contract Clause Comparison

I've attached 12 vendor contracts. Extract the indemnification clause from each, then create a table showing which contracts cap liability and at what dollar amount.

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Meeting Transcript Action Items

This is a transcript of our quarterly planning meeting. Extract every action item mentioned, the person assigned, and any deadline stated. Format as JSON with fields: task, owner, due_date.

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Technical Doc Cross-Reference

I've uploaded our entire API documentation (28 markdown files). Explain how to implement OAuth refresh tokens, citing the specific endpoints and parameters from the docs.

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Screenshot UI Consistency Check

I've attached 35 screenshots of our mobile app. Identify any screens where the primary button color differs from our brand blue (#2563EB) or where top padding is less than 16px.

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