GPT-5.6 Launches — OpenAI Ships Three Models (Sol, Terra, Luna) with ChatGPT Work

Spec and pricing figures here come from OpenAI's announcement and AI-media reporting (sources at the end). We stick to disclosed facts and avoid unverified benchmark numbers.

1. What GPT-5.6 is + the three models

GPT-5.6 differs from earlier updates in that OpenAI split it into three clearly named models by use case, instead of one model with an effort dial — similar in spirit to the Claude class split (Opus/Sonnet/Haiku):

2. Specs and pricing

All three share the same core specs, differing in capability and price (USD per 1M tokens, standard API):

OpenAI's headline: Sol holds the same price as GPT-5.5 did at its April launch — a smarter flagship with no price increase — while Terra effectively gives GPT-5.5-class performance at about half the cost, pushing value down much like Claude did with Sonnet 5.

3. Cerebras — 750 tokens/sec

OpenAI partnered with Cerebras to serve Sol at up to ~750 tokens/sec, much faster than typical GPU serving. That speed matters for agents that reason over many steps and for real-time user-facing work.

4. ChatGPT Work — the agent alongside it

Alongside GPT-5.6, OpenAI announced ChatGPT Work — an agent designed to carry out multi-hour projects rather than answer single prompts, the same direction the whole industry is moving: AI that "gets real work done" continuously, not just chats.

Zooming out, rivals are moving in parallel: Anthropic just brought Cowork to web and mobile so it can run in the cloud. We compared the concept in ChatGPT Work vs Claude Cowork — the competition now isn't only "whose model is smarter" but "whose agent runs long tasks more reliably."

5. Vs Claude Opus 5 / Sonnet 5

With GPT-5.6 and the Claude 5 family both out in the same window, here's a rough price-tier line-up (USD per 1M tokens, input/output) to see market positioning:

The picture: both camps arrive with similar structures — flagship/mid/budget tiers, 1M context, and a focus on long-running agents. The choice comes down to your real workload, existing ecosystem and data governance, more than benchmark numbers alone. See our deep comparison at ChatGPT vs Claude vs Gemini.

6. From a Thai ERP organization's view

For organizations running an ERP at the core, having many vendors and price tiers is good — it lowers and diversifies the cost of adopting AI. But the selection principle stays the same:

• Choose by task and ecosystem, not hype — if you already use Microsoft/Google or Claude, fit with your existing tools matters more than a benchmark score.
• Mind the data — whichever vendor, these models process on overseas clouds; sensitive data needs a clear policy on what can and can't be sent. See our guide on AI tooling and cost.
• The ERP remains the source of truth — every vendor's AI is an assistant; accounting/inventory/finance numbers must come from a system with controlled permissions and an audit trail.

Saeree ERP stays neutral on AI assistants — the system holds the real data and controls permissions, while which AI assistant it connects to depends on your organization's fit and data policy (see more on AI in accounting).

7. Conclusion

GPT-5.6 reflects the whole industry's direction — tiered models to pick by task (Sol/Terra/Luna), pushing value down, adding speed via Cerebras, and moving into the "long-running agent" era with ChatGPT Work. Lined up against Claude Opus 5/Sonnet 5, the structures are strikingly similar, so each organization's decision should hinge on real workload, existing ecosystem and data policy — not on any single vendor's numbers.

When every vendor has flagship, mid and budget tiers, the question isn't "who's strongest" but "which one fits our work and our data best."

- The Saeree ERP Team

References

• Simon Willison — The new GPT-5.6 family: Luna, Terra, Sol (accessed 25 Jul 2026)
• OpenAI — GPT-5.6 and ChatGPT Work announcement
• AI Pricing Guru — OpenAI Pricing (Sol/Terra/Luna pricing source)