What OpenAI shipped
On July 9, 2026, OpenAI made GPT-5.6 generally available across the API, Codex, and ChatGPT, after previewing it on June 26. Rather than a single model, GPT-5.6 is a three-tier family with a shared 1.05M-token context window and a February 16, 2026 knowledge cutoff. The tiers trade cost for capability: Luna is the fast, cheap option; Terra is the balanced everyday model; and Sol is the flagship for the hardest work. All three landed the same day in GitHub Copilot as well.
The headline structural change is not the raw scores but the delivery: OpenAI positions Terra as matching GPT-5.5-class quality at roughly half the price, and both Terra and Luna reportedly match Anthropic's Claude Fable 5 on the Agents' Last Exam at around one-sixteenth of the cost. GPT-5.6 also ships new API machinery - programmatic tool calling, subagents, and explicit prompt-cache control - aimed squarely at long-running agent workloads.
Three tiers: Luna, Terra, Sol
| Tier | Positioning | Input / 1M | Output / 1M | Terminal-Bench 2.1 |
|---|---|---|---|---|
| GPT-5.6 Luna | Fast and affordable | $1.00 | $6.00 | 82.5% |
| GPT-5.6 Terra | Balanced, everyday work | $2.50 | $15.00 | 84.3% |
| GPT-5.6 Sol | Flagship, hardest tasks | $5.00 | $30.00 | 88.8% |
Each tier also has a -pro variant in the API, and Sol adds an Ultra mode that scores 91.9% on Terminal-Bench 2.1 by leaning on subagents rather than a single pass. Pricing is identical across a tier and its pro variant; the difference is reasoning depth and orchestration, not per-token cost.
Where the numbers actually land
On Terminal-Bench 2.1 (agentic terminal tasks), the family stacks up cleanly against the field:
| GPT-5.6 Sol Ultra | 91.9% |
| GPT-5.6 Sol | 88.8% |
| Claude Mythos 5 | 88.0% |
| GPT-5.6 Terra | 84.3% |
| GPT-5.5 | 83.4% |
| GPT-5.6 Luna | 82.5% |
| Claude Opus 4.8 | 78.9% |
On the Agents' Last Exam (long-running professional workflows across 55 fields), Sol scores 53.6, which OpenAI reports as 13.1 points ahead of Claude Fable 5, with Terra and Luna also edging out Fable 5 at a fraction of the cost.
The honest counterpoint: on SWE-Bench Pro, Sol scores 64.6% versus Claude Fable 5's 80% - a clear loss. OpenAI's own audit noted that roughly 30% of SWE-Bench Pro tasks are broken, so the gap is worth reading with that caveat, but GPT-5.6 does not top every board. It leads on agentic terminal and long-horizon workflow tasks and trails Anthropic on this particular software-engineering set.
Pricing and the caching story
The three-tier ladder is the whole point: Terra costs half of Sol and, per OpenAI, holds GPT-5.5-class quality, while Luna is cheaper still for high-volume or latency-sensitive work. Cached input reads keep the 90% discount, cached writes cost 1.25x, and GA added a 30-minute minimum cache life plus explicit cache breakpoints for fine-grained control.
Simon Willison's cost probe makes the spread concrete: the same image-generation task ranged from 0.71 cents on Luna with no reasoning to 48.55 cents on Sol at max reasoning effort - a ~68x span within one model family, which is exactly the knob the three tiers plus reasoning modes are meant to give you.
Agent-first API machinery
The Responses API can orchestrate tools with JavaScript instead of round-tripping every call through the model, cutting latency and token overhead on multi-tool agents.
Sol Ultra spins up subagents to parallelize complex work, going beyond a single agent pass. That is how Ultra reaches 91.9% on Terminal-Bench 2.1 versus 88.8% for a single Sol run.
A new max reasoning tier gives Sol the most time to think on the hardest problems, trading latency and cost for depth.
GPT-5.6 Sol runs on Cerebras at up to ~750 tokens per second, aimed at interactive and agentic use where wall-clock latency matters.
Rounding out the release: explicit prompt-cache breakpoints and image detail options (including detail: original for full-resolution image inputs). The through-line is that GPT-5.6 is tuned less for one-shot chat and more for long-running, tool-heavy agents.
Where GPT-5.6 sits in our rankings
Our leaderboard rescinds and rescores every model hourly. Here is where the GPT-5.6 family currently lands in the coding category:
Compare the family directly against the current leaders on the live model leaderboard, or line Sol up against Anthropic's flagship on the GPT-5.6 Sol vs Claude Fable 5 comparison.
Which tier should you use
High-volume, latency-sensitive, or cost-capped work: classification, extraction, routing, first-pass drafting, and agent steps where you call the model thousands of times. At $1/$6 it is the cheapest tier and still clears 82.5% on Terminal-Bench 2.1.
The everyday workhorse. OpenAI positions it at GPT-5.5-class quality for roughly half the price, so most production agents and coding assistants should start here and only escalate to Sol when a task genuinely needs it.
The hardest agentic and long-horizon work: multi-step research, complex refactors, and tasks worth paying max reasoning for. Use Ultra mode when parallel subagents help, keeping in mind Anthropic's Fable 5 still leads on SWE-Bench Pro.
Primary sources
Pricing, context, and benchmark figures reflect OpenAI's GPT-5.6 GA announcement (July 9, 2026) and the coverage cited above. Live ranking positions are computed hourly from this site's pipeline and will move as benchmark coverage of the new models fills in.