
GPT-6 Sol and Luna: the price cut is the upgrade
GPT-6 Sol and Luna cut API prices while independent benchmarks show smaller gains. I compare the scores, ChatGPT access, and mixed first reports on Reddit.
Every article tagged benchmarks, newest first.

GPT-6 Sol and Luna cut API prices while independent benchmarks show smaller gains. I compare the scores, ChatGPT access, and mixed first reports on Reddit.

Opus 5.5 gains ground in independent coding tests and cuts token prices. I compare the task costs, effort settings, and first Reddit reports on daily use.

OpenAI's GPT-6 Astra is metered at 2.5 times Sol's rate and feels more human in conversation. I checked the limits, the benchmarks, and the first reactions.

Muse Spark 1.3 scored 62 on Artificial Analysis, above GPT-6 Astra, then fell to ninth in a rescore. I traced where the score came from and what it costs.

Fable 5.1 leads its predecessor on long agent tasks, but Opus 5 stays close at half the base token price. I checked the benchmarks and first reports.

V4 Flash costs $0.14 in and $0.28 out per million tokens. I checked whether its 97 to 99 percent discount makes DeepSeek's benchmark losses worth it.

DeepSWE puts Luna Max 2.2 points behind Sol High at roughly one-sixth the attempt cost. I explain why the models can still feel far apart in repository work.

I compared Sol, Terra, Opus 5 and Fable 5 across coding benchmarks. The winner changes with the task, effort setting, agent setup and budget.

Kimi K3 ties GPT-5.6 medium but takes 4.6 times as long. GLM-5.2 is cheap per token yet costly per task. I checked where both models still win.

Opus 5 matches Fable 5 on benchmarks at half the token price, yet it can be painful to supervise. Here is where Fable still earns its place.