GPT-5.6 Sol matches Claude Fable 5 intelligence at one third the cost

OpenAI released GPT-5.6 Sol, which scores 59 on the Artificial Analysis Intelligence Index, one point below Claude Fable 5, at approximately one third the cost. The model family includes Sol, Terra, and Luna, with Sol leading the Coding Agent Index and offering cost savings for coding tasks. New cache-write pricing mirrors Anthropic's model, increasing costs for long cached contexts.

OpenAI's GPT-5.6 family dropped this week, and Artificial Analysis has the benchmarks. The headline: GPT-5.6 Sol max scores 59 on the Artificial Analysis Intelligence Index — one point below Claude Fable 5 — at approximately one third of the cost. "GPT-5.6 Sol costs $1.04 per task in the Artificial Analysis Intelligence Index — offering a similar level of intelligence to Claude Fable 5 at approximately one third of the cost." That's not a minor efficiency bump. It's a meaningful shift in the cost/intelligence curve. What actually changed - Three-tier family: Sol, Terra, and Luna. Sol is the flagship; Terra ~50% cheaper than Sol and Luna ~80% cheaper trade down on intelligence but stay on the Pareto frontier ahead of GPT-5.5 at every effort level. - Coding agent leader: GPT-5.6 Sol max in OpenAI's Codex harness scores 80 on the new Artificial Analysis Coding Agent Index — first across all three evaluations DeepSWE, Terminal-Bench v2, SWE-Atlas-QnA . It's also ~40% cheaper per task than Claude Fable 5 in Claude Code for comparable coding work. - Low token use: Sol max uses ~15k output tokens per Intelligence Index task vs 16k for GPT-5.5 — and fewer than Claude Opus 4.8 and Gemini 3.5 Flash at similar intelligence levels. - Best presentation outputs: Sol max takes the top Presentation Elo in the AA-Briefcase benchmark — its PowerPoint and Excel outputs rated most visually polished of any model tested. The cache-write pricing wrinkle GPT-5.6 introduces something new for OpenAI: cache-write pricing . Sol, Terra, and Luna are priced at $5/$30, $2.5/$15, and $1/$6 per million input/output tokens respectively. Cache reads stay at 90% discount — but cache writes now cost 1.25× the base input price. This mirrors Anthropic's model. The logic: cached tokens occupy memory whether or not they're reused, so the write cost reflects real infrastructure cost. Fair enough — but if you're building agents with long shared contexts, this will show up in your bills. Worth a line item in your cost model. What to do - Evaluating frontier models for production? GPT-5.6 Sol is now the clearest cost challenger to Claude Fable 5 for general intelligence tasks. Run your own evals on your actual workloads — benchmark scores are a starting point, not a decision. - Running coding agents? Sol in the Codex harness leads the field right now. If you've been on Claude Code for agentic coding, the cost delta is worth testing. - Cost-sensitive use cases? Luna at $1/$6 per million tokens is on the Pareto frontier — more intelligent per dollar than GPT-5.5, GLM-5.2, and Gemini 3.5 Flash. - Building with long cached contexts? Account for the new cache-write premium in your cost projections. 1.25× on writes is not free. The full benchmark breakdown — including per-model effort-level comparisons — is at artificialanalysis.ai https://artificialanalysis.ai/articles/gpt-5-6-has-landed . ✏️ Drafted with KewBot AI , edited and approved by Drew.