Combined results (Claude Mythos / Claude Opus 4.6 / GPT-5.4 / Gemini 3.1 Pro)
SWE-bench Verified: 93.9% / 80.8% / — / 80.6%
SWE-bench Pro: 77.8% / 53.4% / 57.7% / 54.2%
SWE-bench Multilingual: 87.3% / 77.8% / — / —
SWE-bench Multimodal: 59.0% / 27.1% / — / —
Terminal-Bench 2.0: 82.0% / 65.4% / 75.1% / 68.5%
GPQA Diamond: 94.5% / 91.3% / 92.8% / 94.3%
MMMLU: 92.7% / 91.1% / — / 92.6–93.6%
USAMO: 97.6% / 42.3% / 95.2% / 74.4%
GraphWalks BFS 256K–1M: 80.0% / 38.7% / 21.4% / —
HLE (no tools): 56.8% / 40.0% / 39.8% / 44.4%
HLE (with tools): 64.7% / 53.1% / 52.1% / 51.4%
CharXiv (no tools): 86.1% / 61.5% / — / —
CharXiv (with tools): 93.2% / 78.9% / — / —
OSWorld: 79.6% / 72.7% / 75.0% / —Haven't seen a jump this large since I don't even know, years? Too bad they are not releasing it anytime soon (there is no need as they are still currently the leader).
Are these fair comparisons? It seems like mythos is going to be like a 5.4 ultra or Gemini Deepthink tier model, where access is limited and token usage per query is totally off the charts.
We're gonna need some new benchmarks...
ARC-AGI-3 might be the only remaining benchmark below 50%
but how does it perform on pelican riding a bicycle bench? why are they hiding the truth?!
(edit: I hope this is an obvious joke. less facetiously these are pretty jaw dropping numbers)
Honestly we are all sleeping on GPT-5.4. Particularly with the influx of Claude users recently (and increasingly unstable platform) Codex has been added to my rotation and it's surprising me.
The real part is SWE-bench Verified since there is no way to overfit. That's the only one we can believe.
> Combined results (Claude Mythos / Claude Opus 4.6 / GPT-5.4 / Gemini 3.1 Pro)
> Terminal-Bench 2.0: 82.0% / 65.4% / 75.1% / 68.5%
> GPQA Diamond: 94.5% / 91.3% / 92.8% / 94.3%
> MMMLU: 92.7% / 91.1% / — / 92.6–93.6%
> USAMO: 97.6% / 42.3% / 95.2% / 74.4%
> OSWorld: 79.6% / 72.7% / 75.0% / —
Given that for a number of these benchmarks, it seems to be barely competitive with the previous gen, I don't know what to make of the significant jumps on some benchmarks within these same categories. Training to the test? Better training?
And the decision to withhold general release (of a 'preview' no less!) seems to be well, odd. And the decision to release a 'preview' version to specific companies? You know any production teams at these massive companies that would work with a 'preview' anything? R&D teams, sure, but production? Part of me wants to LoL.
What are they trying to do? Induce FOMO and stop subscriber bleed-out stemming from the recent negative headlines around problems with using?