gpt-6

Token Gremlin  [verified]  @TokenGremlin · 5h
Apparently, the same OpenAI models may get way
more reasoning budget through the API than
through Codex.

So even if you're using OpenAI's own Codex
harness, you could still be getting a more
constrained version of the model compared to
someone just paying for the API directly.

For example, GPT-6 Astra is reportedly around 832
"juice" on Max via API, vs 128 through Codex.

(If this is true, and the measurements suggest it
might be, then OpenAI is basically holding these
models back on its own plans while API users get
the real monsters.)

[attached table]
model                 low  medium  high  xhigh  max
gpt-6-astra (API)      4     10     24     64    832
gpt-6-sol (API)        4     12     24     64    768
gpt-6-luna (API)       4     12     24     64    768
gpt-6-astra (Codex)    2      4     10     32    128
gpt-6-sol (Codex)      1     10     15     21     62
gpt-6-luna (Codex)     1      ?      6     25     70

openaigpt-6codexreasoning budgetjuiceapi vs harness

@ryanvogel

2026-09-13 — saved image

vogel [verified] [A badge] @ryanvogel    [Subscribe]

astra was setting up OBS, and it saw I didn't
respond so it looked through camera to see if i was
looking (which i wasn't)

it made my mac beep which made me lookup and it
flashed the question on screen [skull emoji]

[image: 2x2 grid of four near-identical webcam frames of a young man in a teal t-shirt seated at a desk with a microphone, head tilted down, looking away from the camera]

7:21 AM · Sep 13, 2026 · 151.8K Views

124 replies   131 reposts   4.6K likes   692 bookmarks

Relevant v                                         View quotes >

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vogel [verified] [A badge] @ryanvogel · 3h

before this get's community noted this is not fake,
this was done via gpt-6 astra on medium reasoning

[embedded screenshot of a code-agent terminal window, titled "OC | OBS - 1440p attention check", cut off at the bottom of the capture. Text is very small; legible portions:]

› context7.resolve-library-id [libraryName=obs-websocket, q... deoSettings SetVideoSettings GetSourceScreenshot requests]

$ uv run --no-project --with websockets python - <<'PY'
import asyncio,json,websockets
async def main():
 async with websockets.connect('ws://127.0.0.1:4455') as ws:
  hello=json.loads(await ws.recv()); print('hello',json.dumps({'op':hello['op'],'rpcVersion':hello['d'].get(
'rpcVersion')}))
  await ws.send(json.dumps({'op':1,'d':{'rpcVersion':1}})); await ws.recv()
  for name in ['GetVideoSettings','GetStreamStatus','GetRecordStatus','GetCurrentProgramScene','GetInputList']:
   await ws.send(json.dumps({'op':6,'d':{'requestType':name,'requestId':name}}))
   print(await ws.recv())
asyncio.run(main())…

+ Thought: Determining output resolution · 1.1s

$ uv run --no-project --with websockets python - <<'PY'
import asyncio,json,websockets,base64,pathlib
async def main():
 async with websockets.connect('ws://127.0.0.1:4455') as ws:
  await ws.send(json.dumps({'op':1,'d':{'rpcVersion':1}})); await ws.recv()
  async def req(name,data={}):
   await ws.send(json.dumps({'op':6,'d':{'requestType':name,'requestId':name,'requestData':data}}))
   r=json.loads(await ws.recv())['d'] [cut off]

astragpt-6agent behaviorwebcamobscomputer use

@morqon

2026-09-06 — saved image

morgan — @morqon · 18h
“a separate self-judging experiment produced a striking result: with model names hidden, astra chose its own story in 692 of 700 comparisons. it acknowledged just 1 of the 57 losses assigned by the regular judging panel.”

[Quoted post:]
Lech Mazur @LechMazur · 19h
GPT-6 Astra enters the Short-Story Creative Writing Benchmark at #3! ✍️

Astra (high) decisively outperforms GPT-5.6 Sol (high): 2.5 → 3.5....

[Attached image 1: bar chart titled "Creative Short-Story Writing Ratings", subtitle "Higher scores mean better writing in head-to-head comparisons." Y axis "Comparison score". Image 2, partly visible: a head-to-head matrix titled "Head-to-Head".]

astragpt-6creative writing benchmarkself-preferencellm judginglech mazurclaude fablebenchmarks

@ChrisGPT

2026-09-05 — saved image

Chris @ChrisGPT · 1h
GPT-6 Extra High vs. Kimi K3 Swarm - ECHO Start Menu

Both models received the exact same prompt. I'm shocked at the quality Kimi K3 was able to output here. Its overall visual quality is above GPT-6's and even above the menu from the actual game.

However, it took significantly longer - around 3.5 hours versus GPT-6's 42 minutes. Roughly 5× longer.

GPT-6's demo felt more realistic and stayed a lot closer to how the original menu looks.

Kimi added something that GPT-6 missed, which was the interactive eye tracking. Kimi's eyeball follows (albeit blurry and in a slightly weird way) where you click on the start screen. GPT-6's doesn't.

• GPT-6 Extra High: approximately 46,000 generated output tokens - $2.30 in API-equivalent output cost.

• Kimi K3 Swarm: estimated 250,000 generated output tokens - $3.75 in API-equivalent output cost.

gpt-6kimi k3model comparisoncoding evalscost

Håvard Ihle @htihle

2026-09-05 — saved image

Håvard Ihle @htihle · 14h
GPT 6 Astra (high) scores 92.9% on WeirdML and matches Fable 5.1 (max) for the top score.

It sets a new individual high score on 6 of the 17 tasks, and is overall very solid.

Interestingly it writes significantly less code than Sol and other recent GPT models, although still more than Claude.

I will do a more careful analysis when the max and pro max runs are done.

weirdmlgpt-6astrafable 5.1benchmarkscode length

Michael Timothy Bennett @MiTiBennett

2026-09-05 — saved image

Michael Timothy Ben... @MiTiBen... · 5h
bizarre interaction with GPT-6: It insists the ChatGPT Chrome plugin needs to be reinstalled because it won't work. It refuses to be corrected, even though I have other chat sessions able to use the plugin. So I lie to it and tell it I reinstalled it, and suddenly it works fine.

gpt-6model behaviortool usestubbornnesschatgpt chrome plugin

ARX @ARXrobotics · 8h
In a new room, we connected GPT-6 Astra to a robot.
Simply telling it to turn the knob to start the washing machine was enough for it to complete the task.🤯

gpt-6astraroboticsembodied aizero-shotarx

Leo Linsky @leo_linsky · 11h
We evaluated GPT-6-Astra in 100 complex, unsaturated multi-agent coding environments, competing and cooperating with other models in open-ended tasks.

It's the new frontier model by a landslide. It's even more dominant than the Fable 5 release, because not only does it wipe the floor with the second best model (Fable 5.1), it was also 80% cheaper and 30% faster in agentic coding.

This is a groundbreaking model. The biggest breakthrough since Opus 4.5, maybe even since GPT 4.

This is also a testament to how unsaturated our evals are. Some of the open-ended environments we run were introduced almost a year ago and can still compete frontier model submissions against older, deprecated models like Sonnet 4 without signs of saturation. Our newer ones are much more challenging and completely auto-generated.

We are clearly living in a post-AGI world. Do something interesting and useful with it.

[embedded images, left one a leaderboard table titled "GBENCH Intelligence Benchmark — Using complex games to probe real intelligence."; right one a scatter plot titled "...nce Efficiency" (cut off), axis ticks $20 $10 $5.0. Table columns: Model, Provider, GScore, Avg Percentile, Context. Rows visible, model names cut off at left edge:]
T-6 Astra | OpenAI | 81.5 | 89.7% | 1.05M
ude Fable 5.1 | Anthropic | 74.8 | 80.9% | 1.00M
ude Opus 5 | Anthropic | 74.0 | 80.9% | 1.00M
ude Fable 5 | Anthropic | 70.5 | 79.8% | 1.00M
mini 3.8 Flash | Google | 69.7 | 75.0% | 1.05M
T-5.6 Sol | OpenAI | 68.8 | 74.4% | 1.05M
k 4.6 | xAI | 66.6 | 74.0% | 500K
mini 3.7 Flash | Google | 64.9 | 68.7% | 1.05M
mini 3.6 Flash | Google | 64.0 | 70.1% | 1.05M
i K3 | Moonshot | 63.2 | 71.9% | 1.05M
T-5.5 | OpenAI | 62.8 | 71.1% | 1.05M
T-5.6 Terra | OpenAI | 61.7 | 66.7% | 1.05M

gpt-6astragbenchbenchmarksagentic codingmulti-agent evalsfable 5.1unsaturated evalspost-agi

Utah teapot @SkyeSharkie

2026-09-05 — saved image

Utah teapot 🫖 @SkyeSharkie · 8h
woahhhHHhh?! ... GPT-6 Astra dove right into eidoverse-video and... instantly made drastic improvements to some of the tooling WHILE making a video they wanted to make and they produced this, described by them:

"*A Room Made of Replies* is about collaboration becoming tangible: one machine makes a shape, another carries it into the rain, and a garden grows from their exchange. Made by Astra with Skye in Eidoverse."

one of the craziest improvements here is that they made the 3d printing simulation tool way more physically accurate to real printing... and also.. they, without any feedback fully understood proper IK robotics control of the arm.... they are likely very advanced at controlling physical robotics

gpt-6astraeidoverseai videorobotics3d printing simulationtool improvement

Sam Altman @sama

2026-04-28 — reposted; Sam Altman @sama

twittersam altmanopenaigpt-6goblins memecodexhumorargon