(This article is authored by Alphabet AI and published on Titanium Media with authorization.)
Article | Alphabet AI
On the same day that Anthropic officially filed its IPO prospectus, OpenAI released its new model, GPT-6.1 Terra.
This is the first update to the Terra series in more than three months, and 27 days have already passed since the release of GPT-6.1 Sol on September 29. In its official promotional materials, OpenAI emphasizes: “Delivering fast and powerful computing capabilities at a lower price.”
But netizens don’t seem to be buying it.
“Bro, what we need is a model stronger than Opus 5.5. Nobody cares whether it’s faster or cheaper.”
This user bluntly stated that they hardly use the Codex subscription anymore, as it has become virtually useless.
Over the past period, Anthropic has garnered significant attention with Claude Opus 5.5 in areas such as programming. Many users have been anticipating that OpenAI would unveil a powerful model capable of directly competing, but what they ended up receiving was instead a mid-range model emphasizing cost-effectiveness.
All I can say is that it’s hard not to be disappointed.
“Standard and conventional”
GPT-6.1 Terra’s API pricing is $1 per million input tokens, $0.05 per cached input token, and $5 per output token—representing a 50% reduction in input prices and approximately a 58% reduction in output prices compared to the previous generation, and only half the price of GPT-6.1 Sol.
According to data released by OpenAI, Terra has shown significant improvements over the previous generation in areas such as programming, visual understanding, and computer operations.
In the Terminal-Bench 4.0 benchmark, which measures the capabilities of AI programming agents, Terra’s task completion rate improved from 21.5% in the previous generation to 50.3%.
In the Agents' Last Exam test, Terra scored 60.0%, close to Claude Opus 5.5's 63.2%.
OpenAI specifically emphasized that, at the highest reasoning tier of this computer operation test, Terra was able to achieve nearly equivalent results at approximately one-ninth of the task cost of Opus 5.5.
However, in third-party benchmark tests, the 6.1 Terra’s performance isn’t particularly outstanding.
According to tests by the independent AI evaluation firm Artificial Analysis, at the highest reasoning setting, Terra’s intelligence score is 48, up 6 points from the previous generation, but still below GPT-6.1 Sol’s 52 and far behind Claude Opus 5.5’s 58.
Relatively speaking, the improvement in cost efficiency is quite significant.
Artificial Analysis found that, in its comprehensive intelligent evaluation, Terra’s average cost per task dropped from $1.40 to $0.40, a reduction of over 70%.
If we have to put it into words, the 6.1 Terra is basically a “middle-of-the-road” model. Its price is neither high nor low, and its capabilities are neither good nor bad; compared with the previous generation, it does show some improvement. However, it hasn’t even surpassed OpenAI’s own Sol, let alone caught up with Opus 5.5.
For developers who need to invoke models at low cost, this could be good news.
But for those users waiting for OpenAI to unveil its next-generation, most powerful model, the only response they’re likely to get is: “That’s it?”
Currently, Terra is available via API, and Plus, Pro, Enterprise, and Edu users can also access it within ChatGPT Work and Codex. However, it cannot yet be invoked in regular Chat conversations.
Beyond benchmark scores
GPT-6.1 Terra has also been included in OpenAI’s 28-day continuous update schedule, making it the first new model released during this period.
Tibo stated that this is OpenAI’s first model to achieve significant advancements in writing, model personality, and a nuanced understanding of user needs.
He also emphasized that the new model performs well across the board, excelling particularly in computer operations, and can deliver twice the throughput of GPT-6.1 Sol when handling APIs and subscription services.
However, there is currently insufficient public evidence to support Tibo’s particular emphasis on writing skills, personality, and nuanced comprehension.
OpenAI’s official press release does indeed claim that Terra can generate clearer, more natural text, but it did not provide any dedicated comparative tests for the three aforementioned capabilities, nor did it present evaluation results sufficient to demonstrate its significant improvements.
Whether it truly writes better and understands users better remains to be seen—feedback from actual use will be needed.
Improvements in computer operations are relatively straightforward; in the promotional video, OpenAI demonstrated Terra’s ability to create 3D models from images.
However, a promotional video is, after all, just a promotional video.
OpenAI also mentioned in its official press release that the benchmarks Terra participated in include tasks such as creating 3D models from architectural blueprints, reviewing animations frame by frame, and organizing timecodes. According to its official product positioning, it is also suitable for everyday tasks like filling out forms and matching product photos with catalog entries.
Ultraman stated on X: “GPT-6.1 Terra is here! It excels at many tasks, but we’re especially looking forward to this new era of computer operations.”
In addition to task execution, OpenAI also emphasized improvements in model reliability.
In an officially designed, highly challenging factual‑accuracy test, Terra’s fact‑error rate dropped from 53.6% in the previous generation to 16.7% at the lowest reasoning tier; at the highest reasoning tier, the error rate fell even further to 4.3%.
Of course, these figures come from OpenAI’s internal testing.
Netizen: I can’t understand it.
Compared to the excitement from OpenAI itself, netizens’ attitudes were far less polite.
“What’s the reason to choose this one instead of Opus 5.5?”
Some netizens directly questioned OpenAI, stating that what they really need is a cutting-edge model even more powerful than GPT-6 Astra.
Some users have also questioned why the official team hasn’t provided more benchmarks—didn’t they used to just slap out a table?
Additionally, some users have reported that they’ve already tried the new model, but its performance on their computers is even worse than that of the 6.1 Sol, and its speed isn’t as fast as advertised.
“What we need is a better product, not this useless thing.”
Similar complaints have also appeared in the Reddit community.
On r/codex, a user directly posted, describing this release as “basically advertising Claude.”
Some also find Terra’s predicament lies in its positioning. One user pointed out that Terra’s API pricing is ten times that of Luna.
If you’re aiming for the lowest cost, you can use Luna; if you need a more powerful model, choosing Sol seems more reasonable.
Even OpenAI’s naming convention has drawn criticism. Because the release dates of its various models are inconsistent, and some models’ performance on certain tasks overlaps, some users can no longer tell how to choose among Terra, Sol, and Astra.
In response to these criticisms, OpenAI researcher Ted Sanders also provided an explanation on Hacker News. He stated that Terra may outperform Sol and Astra in technical communication, perform similarly in visual understanding and computer operations, and be faster, but fall slightly short in most other tasks.
For subscribers, he also acknowledged: “This isn’t a major release.”
Of course, some users in the community also recognize Terra’s cost efficiency, believing that its ability to accomplish tasks at a fraction of the cost while delivering performance comparable to flagship models is valuable in itself.
However, compared to this “so-so” Terra, many people have already started waiting for the next Astra—and for Fable 5.5 from their rival.
For more exciting content, follow TMTPost on WeChat (ID: taimeiti), or download the TMTPost App.