GoSearch just added two new models to its lineup: GPT-5.6 Sol and GPT-5.6 Terra. If you’re building no-code agents, automating workflows, or just using GoAI for everyday chat, you now have a choice between OpenAI’s flagship reasoning model and its balanced, faster everyday model, without touching an API key or managing infrastructure yourself.
This post breaks down what each model is actually good for, when to reach for one over the other, and how GoSearch puts that choice to work across agents, workflows, and chat.
Quick answer: GPT-5.6 Sol is OpenAI’s flagship model, built for complex, long-horizon reasoning and agentic work, like coding agents, multi-step research, or workflows that need to stay oriented across many steps. GPT-5.6 Terra is the balanced, everyday model, competitive with the previous generation’s flagship while running faster, and it’s the better default for scoped, high-volume, or speed-sensitive work. In GoSearch, both are available for no-code agents, automated workflows, and AI chat, so you can match model power to task complexity instead of defaulting to a single model for everything. GoSearch doesn’t pass query or token costs back to users, so the choice between Sol and Terra comes down to what a task needs, not what it costs.
What is GPT-5.6 Sol?
GPT-5.6 Sol is OpenAI’s flagship model in the GPT-5.6 family, built for the hardest, most open-ended tasks: long-horizon agentic work, complex multi-step reasoning, and demanding coding tasks. OpenAI reports that Sol sets a new state of the art on the Artificial Analysis Coding Agent Index and shows strong gains on evaluations of long-running professional workflows spanning dozens of fields. Independent hands-on testing backs up the coding claim: CodeRabbit’s benchmark review found Sol stays oriented longer on messy, multi-file repo tasks and surfaces more real issues in code review than prior-generation models. In practice, that means Sol is built to stay oriented through complicated, many-step tasks rather than losing the thread partway through.
Sol is the model to reach for when a task genuinely benefits from deeper reasoning: an agent that has to plan, execute, check its own work, and adjust across many steps, or a workflow pulling from multiple systems where getting an intermediate step wrong compounds downstream.
Where Sol fits:
- Complex, multi-step agents, like a research agent that has to search, synthesize across sources, and produce a structured output without losing context along the way.
- High-stakes automation, where the risk of an agent getting a step wrong outweighs the extra reasoning time a stronger model takes.
- Engineering and technical workflows, such as code review or debugging agents, where Sol’s coding performance is a meaningful step up.
What is GPT-5.6 Terra?
GPT-5.6 Terra is the balanced, everyday tier of the GPT-5.6 family. OpenAI positions it as competitive with the prior generation’s flagship model while being a smaller, more lightweight model, which generally translates to faster response times and makes it the practical default for most day-to-day agentic and chat work rather than a stripped-down fallback option.
Terra is built for the volume of work that doesn’t need Sol’s ceiling: scoped tasks with a clear structure, everyday chat, and workflows that run frequently enough that speed and responsiveness matter most.
Where Terra fits:
- Everyday chat and quick lookups, where speed matters more than squeezing out the last bit of reasoning depth.
- Scoped, well-defined agents, like a ticket triage agent or a status summary agent, where the task shape is consistent and predictable.
- High-frequency workflows, such as a daily digest or a recurring report, where the task doesn’t need Sol’s level of reasoning to get right.
When should you use Sol vs. Terra for agents and workflows?
The short version: match the model to how much the task actually needs to reason. If an agent has to plan across multiple steps, adapt to unexpected results, or work through a genuinely hard problem, Sol is worth the extra reasoning time. If the task is scoped, repeated often, or doesn’t require deep reasoning to get right, Terra gets you most of the performance with faster response times.
GoSearch doesn’t pass query or token costs back to users, so this decision isn’t about managing a budget. Both models are included in your plan. The real trade-off is reasoning depth versus speed, not price.
| GPT-5.6 Sol | GPT-5.6 Terra | |
|---|---|---|
| Best for | Complex, long-horizon reasoning and agentic work | Everyday, scoped work at high volume |
| Reasoning depth | Highest in the GPT-5.6 family | Strong, competitive with the prior generation’s flagship |
| Speed | Slower, since it’s optimized for depth over response time | Faster, optimized for quick, high-volume responses |
| Ideal GoSearch use cases | Research agents, code review, multi-step workflows across systems | Ticket triage, status summaries, daily digests, everyday chat |
| Good default for | A specific agent that’s struggling with complexity on Terra | Most new agents and workflows, until proven otherwise |
A useful test: start with Terra. If it consistently handles the task well, stay there. If you notice it losing context on longer tasks, missing steps in a multi-part process, or struggling with genuinely complex reasoning, that’s the signal to move that specific agent or workflow to Sol. Not every agent in your organization needs the same model, and treating model choice as a per-agent decision rather than an org-wide default is usually the more effective way to match each agent to what it actually needs.
How does GoSearch use GPT-5.6 Sol and Terra?
GoSearch has always been multi-LLM, giving teams a choice across OpenAI, Anthropic, and Google Gemini models with Zero Data Retention, rather than locking customers into a single provider’s roadmap. Adding GPT-5.6 Sol and Terra extends that same choice to OpenAI’s newest model tier, available across three parts of the platform:
No-code agent builder: When you build an agent from scratch or start from a template, you can select which model powers it. A complex research or code-review agent can run on Sol, while a high-volume ticket triage agent can run on Terra, all inside the same no-code builder without writing any integration code.
Workflow automation: Scheduled and triggered workflows, like a daily digest or a stale-deal reminder, can be configured to use the model that fits their complexity and run frequency, so each workflow gets the reasoning depth and speed it actually needs.
GoAI chat: Conversational search and chat through GoAI can draw on GPT-5.6 Terra for everyday questions and Sol for more complex requests, giving employees frontier-model reasoning without needing to know which model to pick.
Benefits by team:
- IT and platform teams get model choice without managing separate API keys, billing, or infrastructure for each provider.
- Builders of agents and workflows can match reasoning depth to each use case instead of defaulting every agent to the same model regardless of what the task actually needs.
- Everyone choosing a model does so based on what the task requires, not on managing a budget, since GoSearch doesn’t pass query or token costs back to users.
- Everyday users of GoAI chat get access to a frontier-generation model without needing to understand the underlying model landscape at all.
How do I get started with GPT-5.6 Sol and Terra in GoSearch?
GPT-5.6 Sol and Terra are available now as model options across GoSearch’s agent builder, workflow automation, and GoAI chat. No migration is required for existing agents or workflows. If you’re unsure where to start, Terra is a safe default for most new agents, with an easy path to move a specific agent to Sol if it needs deeper reasoning.
New to GoSearch? Get a personalized walkthrough of how to apply GPT-5.6 Sol and Terra to your current tasks, or sign up for free to explore the platform yourself.
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FAQ
Sol is OpenAI’s flagship model, built for complex, long-horizon reasoning and demanding agentic or coding work. Terra is the balanced, everyday model, offering strong performance with faster response times, and is designed for scoped, high-volume tasks. Most day-to-day work fits well on Terra, while Sol is worth the added reasoning time for genuinely complex, multi-step tasks like coding agents or multi-step research that need to stay oriented across many steps without losing context.
Sol is OpenAI’s flagship model, built for complex, long-horizon reasoning and demanding agentic or coding work. Terra is the balanced, everyday model, offering strong performance with faster response times, and is designed for scoped, high-volume tasks. Most day-to-day work fits well on Terra, while Sol is worth the added reasoning time for genuinely complex, multi-step tasks like coding agents or multi-step research that need to stay oriented across many steps without losing context.
Yes. GoSearch added GPT-5.6 Sol and Terra to its model lineup, available for no-code agents, automated workflows, and GoAI chat. Both models can be selected per agent or workflow, so teams can match model power to task complexity rather than defaulting to one model for everything on the platform. This is part of GoSearch’s broader multi-LLM approach, which also includes models from Anthropic and Google Gemini, all with Zero Data Retention support.
No. GoSearch doesn’t pass query or token costs back to users, so choosing between Sol and Terra doesn’t change your bill. Both models are included in your plan, and this holds whether you’re using them in the no-code agent builder, an automated workflow, or GoAI chat. That means the decision comes down entirely to what a task needs, deeper reasoning versus faster responses, rather than managing cost trade-offs the way you might with a direct API integration.
It depends on the agent’s complexity. Use Sol for agents that need to reason across multiple steps, adapt to unexpected results, or handle genuinely difficult tasks, like research or code review agents. Use Terra for scoped, well-defined agents that run frequently, like ticket triage or status summaries, where consistent performance at faster speed matters more than maximum reasoning depth. A practical approach is to start new agents on Terra by default, then move a specific agent to Sol only if it needs deeper reasoning.
No. Terra is a different tier built for a different purpose, not a limited version of Sol. OpenAI reports Terra performs competitively with the prior generation’s flagship model while being smaller and faster, making it a strong default for everyday work rather than a compromise. In GoSearch, this efficiency doesn’t translate into a cost difference for you, since pricing isn’t tied to which model you use. Sol exists for tasks that specifically benefit from deeper reasoning, not as the “correct” choice for every use case.
Yes. Model selection in GoSearch happens at the query, agent, and workflow level, not the workspace level, so you can run some agents on Sol and others on Terra within the same organization. A complex research agent might run on Sol while a high-volume ticket triage agent runs on Terra, side by side. This lets teams optimize cost and performance individually for each use case, instead of making a single model choice that has to work for every agent across the organization.
