alt Hacker NewsGPT-6.1 Terra
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I'm very confused about their model market position/naming schema.
First we had:
> Luna (Small), Terra (Medium), Sol (Big).
Which was fairly smooth after you got used to their planets.
But then they added Astra as the "Bigger," which was mostly still self-coherent:
> Luna (Small), Terra (Medium), Sol (Big), Astra (Bigger)
But then things go confusing, they released Sol-6.1 which sometimes is superior to Astra, and discontinued Terra which made it look like this:
> Luna (Small), Sol-6.1 == Astra
But with Sol-6.1 costing the old Terra-6.0 price, while, as I said performing as good as the old "Bigger" model in many non-3D/UI situations.
Now they're re-introduced Terra, as a 6.1 release, making this even more confusing.
Did Microsoft's chief branding officer move over to OpenAI?
I rather enjoy OpenAI's focus on cost-per-task.
I'm optimistic about them tackling frontier intelligence next. Astra 6.1 please?
GPT-6 Astra
Input:$10.00 / 1M tokens Cached input:$1.00 / 1M tokens Output:$50.00 / 1M tokens
GPT-6.1 Sol
Input:$2.00 / 1M tokens Cached input:$0.10 / 1M tokens Output:$10.00 / 1M tokens
GPT-6.1 Terra
Input:$1.00 / 1M tokens Cache read:$0.05 / 1M tokens Output:$5.00 / 1M tokens
GPT-6 Luna
Input:$0.10 / 1M tokens Cached input:$0.01 / 1M tokens Output:$0.50 / 1M tokens
(For some reason they say "Cache read" instead of "Cached input" for 6.1 Terra)
6.1 Astra and 6.1 Luna must be coming up soon. Will they reduce their prices further?
Pelicans for GPT-6.1 Terra: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
Interesting that both "none" and "low" reasoning levels appeared not to spend any reasoning tokens at all, and in fact low ended up using less tokens and costing less than none here.
"medium" did use 496 reasoning tokens, but that's apparently not enough here to return a visible reasoning trace.
OpenAI's current frontier model lineup is gpt-6-astra, gpt-6.1-sol, gpt-6.1-terra, gpt-6-luna, so here's a comparison grid of all of their pelicans at different reasoning levels: https://static.simonwillison.net/static/2026/openai-pelicans...
In my tests [1], GPT-6.1 Terra joins the Pareto Frontier in between GPT-6 Luna and GPT-6.1 Sol. So, exactly as advertised!
It's also a very fast model, of all 33 models we've tested so far, only Haiku 5.5 and Nemotron 3.5 Super VL have passed the exam faster but both scored lower. It also wrote the _least_ output in its responses.
[1] Benchmarks for data analytics tasks: https://plotly.com/blog/gpt-6-1-terra-plotly-data-analytics-...
I don't understand, in my tests, on max effort, it's worse than 6.1 sol and 2x more expensive[0].
Used on medium seems to be the best use-case[1] and cheaper than 6.1 Sol.
[0]: https://aibenchy.com/compare/openai-gpt-6-1-sol-max/openai-g...
[1]: https://aibenchy.com/compare/openai-gpt-6-1-sol-medium/opena...
PacBench results.
GPT-6.1 Terra scored 84, one point over Grok 4.7 (83), in 5.4 min for $0.19 vs Grok’s 36.5 min and $1.69. The cheap models keep getting better.
GPT-6.1 Terra: https://jonclegg.github.io/pacman-bakeoff/#gpt-6.1-terra
Closest competitor (Grok 4.7): https://jonclegg.github.io/pacman-bakeoff/#grok-4.7
Why do Anthropic and OpenAI think it necessary to split their model into 4 versions (Opus, Sonnet, Fable, Haiku, Astra, Sol, Luna, Terra) vs. Google's 2 (Argon, Flash)?
Wow. If those charts are true, this effectively matches GPT-6-Astra at a fraction of the cost, and is neck-and-neck with 6.1-Sol.
OpenAI repeatedly keeps hurting user workflows by altering the model generations family for each new version in unpredictable ways. As such, it is not a sane ecosystem to develop in.
Too many models and too many knobs. There are like 5 models and 5 thinking levels, that is 25 different combinations.
Can anyone give me the compelling reason for Terra and Sonnet to exist?
Virtually every task I give to either is better served by going up a tier and down a reasoning level, or down a tier and up a reasoning level. I simply don't understand their use case. No testing I've done has shown them to have a niche where there isn't a cheaper-with-equal-results or more-performant-at-same-cost option.
cool update. Like super cool.
Just one thing about the advert, how can I be the only person here thinking the ad is weird - like for the marketing dep, its a bit weird the ad features the same tram that broke and tragically like ended some people - happened for like the first time ever in 100 years, like a year ago ( 14 months ago) just a bit weird.
Im honestly not trying to be negative, but its kinda weird I kinda feel I should mention it because noone else has?
Im sure literally anyone from southern europe must have thought this the second they saw the ad. It was big news last year.
Am I mad? Just a heads up for PR to always check things like this first when releasing a video? Maybe its just me? Just trying to help
How would it compare to Claude models in terms of performance?
the only things we've got to actually make a judgement on are vibes and token anxiety. vibes generally indicate that more expensive == better, but more expensive == more token anxiety. so you end up using the most expensive model x effort that keeps your anxiety in check. yeah, maybe terra is great at technical documents. i'm not going to use it because i'd need to spend a couple of days writing technical documents to work out if it was better than sol and then what if it isn't?
is opus 5.5 better than sol 6.1? hmm, i really can't tell. maybe claude is a bit more diligent and identifies more issues up front. but sol has this can do attitude and the codex harness just gets on and does it's job done.
The results for factual error rate on "difficult" prompts is staggering to me. Particularly the difference between 5.6-Terra and 6.1-Terra. These are wildly different Pareto fronts. Our custom enterprise agent is currently running on 5.6-Terra and it's already very good. I look forward to updating the configuration.
I'll wait for the runebench results!
On AA intelligence index, this fills in the cost per task frontier nicely between 6 Luna and 6.1 sol. So when 6.1 Luna inevitably releases...
The OAI model tango seems to not have an end in sight, for better or worse. Give me more API toys!
These "Pareto frontier" performance vs price graphs have become very popular and I find them mostly uninformative. Pricing is subjective. You chose the position on the X axis, and which measures to use on the Y Axis.
6.0 re branded as terra?
Am I reading the Agents’ Last Exam v1 graph correctly where it's saying GPT Luna Medium performs better than High, but XHigh is better than Medium?
This tier is what I'd actually point opencode at for PR reviews. The top models are too slow and expensive to run on every diff.
Does it suitable for finance choice?
I am wondering if there is a site with a perf/efficiency chart of the models over time? I am wondering is the pace still speeding up?
These benchmarks made me want to try sonnet 5.5
is it eligible for data sharing incentive free token quota?
Still can't really forgive any of them for essentially stealing most of this knowledge regardless...
Unfortunately it suffers from the same problem as Luna: it will stop at an earliest excuse and no amount of prompting not to stop until X is done will convince it otherwise.
If you are confused, that is how this company was always been, remember GPT 4, then they did some weird versioning.
I personally like Terra, it kind of does what I would ask Sol or Astra, but dont have to count tokens as much. And Luna has been amazing tbh, it takes designs from prototype and in record time is implementing it, so that was a huge win.
But yeah, they always had confusing way of naming products and if you are not following news, you will be confused about what it is.
https://artificialanalysis.ai/#intelligence-efficiency-tabs
According to this, Sol 6.1 x-high is both cheaper and smarter than Terra 6.1 max.
not gonna lie they did really bad and this drained my usage SO FAST. that model used lots of unnecessary skills and read through way more memory files needed.
It literally burned through 2 subs.
Is it stronger and cheaper than DeepSeek V4.1 Flash 1017?
If not, yawn...
The benchmarks are already saturated and the curves for Terra stick to the axes.
Underwhelming
That terminal bench 4.0 result is... bad? Terra XHigh more expensive than Sol Low and still does worse.
It's very likely this is a next checkpoint of GPT-6 "Sol", over-optimised for the web chat and offered to Codex subscribers as a "please go away" offering.
If this was half the price, I'd be very interested, but at 1/5/0.05? Feels like another panic release because they can't get Astra 6.1 out of the door...
Really hate how they only show it vs Opus @ Max and not Low/Medium/High.
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People keep asking OpenAI for a mode that's as good as Opus 5.5, and they release this instead. Interesting strategy. Let's see how it works out for them.
"better writing"
let's see if it can pass the Pangram test. Many services purport to fool it, but fail.
If they had any courage, they would release 6.1 Astra, but they don't.
Update: Look at the OpenAI employees downvoting me.
i'm not sure anyone cares about Terra though.
Previous Terra model was so good it was discontinued.
OpenAi needs a model to compete with Opus 5.5, and that's not Terra 6.1.
GPT-6 only just came out! The AI landscape is always on the move!
Similar 75% price cut trajectory as GPT-5.6 Sol -> GPT-6.1 Sol. Overall, Terra is still half the price of Sol.
But like the original release of Terra, it's still a weird middle child between the small-model-that-got-substantially-better (Luna) and the large-model-that-got-significiantly-cheaper (Sol). The TerminalBench 4.0 cost-per-task results are a bit confusing and I'm not sure why you would pick Terra over Sol in that case. Overall this release seems like a flex on Sonnet 5.5: a model which is having its own middle child problems between the godly Opus 5.5 and the surprisingly capable Haiku 5.5.