Albatross (@albatrosscode) header
Albatross (@albatrosscode) profile picture

Open source agentic coding harness where local and frontier models live in harmony.

Joined January 2009
Photo by Albatross (@albatrosscode)Photo by Albatross (@albatrosscode)Photo by Albatross (@albatrosscode)Photo by Albatross (@albatrosscode)Photo by Albatross (@albatrosscode)Photo by Albatross (@albatrosscode)Photo by Albatross (@albatrosscode)Photo by Albatross (@albatrosscode)Photo by Albatross (@albatrosscode)Photo by Albatross (@albatrosscode)
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Albatross retweeted
I am going to start to share the leaderboard at VulcanBench more regularly. VulcanBench is the only benchmark I know that benchmarks across effort levels, on an eval suite of 100% real engineering tasks. Getting ready to sunset eval suite 3 and eval suite 4 is almost ready to go. Here's the current leaderboard for Eval Suite 3, Grok 4.5 High is the highest scoring model still with Fable 5 Low, yes Low, right behind it. What I've been able to uncover with VulcanBench is that way too many people are running models at Max effort, thinking that buys them more accuracy, when really it just costs more and uses more tokens so takes more time. If you're still in the mode of, tell my agent to do something then go get coffee, you're probably still living in the past. You can move faster, with higher accuracy, the key is not thinking you need Max effort all the time.
Time to share the leaderboard for VulcanBench, Eval Suite 3. As a reminder, these are 100% real engineering tasks, from real repos. No puzzles, no math problems, no exotic architecture. Our leaderboard takes the data we have from our full effort sweeps, every effort level, and reports the effort level that gave the highest accuracy. Right now, so many engineering teams just run a model on High or Max, assuming that's what they need to get the best accuracy. But for most regular, routine, engineering tasks, the stuff we do day in and day out, that's overkill. And it means the company you work for is paying a LOT more money for tokens, all to get the same accuracy, just a lot slower. Currently Grok 4.5 High still tops the chart at 90, with Fable 5 Low right behind it at 89 and DeepSeek V4-Flash Max right behind that at 88. If you're using Grok 4.6, Medium is actually the sweet spot for effort, and Opus 5, which everyone seems to be complaining about these days...well you're probably using it on High, which actually doesn't perform as well as low. Effort matters. Live long and benchmark 馃枛
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Replying to @EXM7777 @orca_build
Super interesting, thanks for sharing.
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Replying to @kimmonismus
Yeah, was very bummed to see this 馃槥
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Replying to @bindureddy
How do you know that 5.6 is cheaper, faster, and more pragmatic? Did you get early access?
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Super interesting to see how strong the adoption curve has been with GLM 5.2
GLM 5.2 vs DeepSeek V4: share of tokens on OpenRouter GLM 5.2 has had a very fast uptake relative to most open-weight launches
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Replying to @OpenRouter
Very interesting to see, and not surprised given how well GLM 5.2 is benchmarking.
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Replying to @daniel_mac8
Ohhh, this is neat.
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Replying to @ollama
Yes! 馃檶
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Replying to @nicdunz
Totally wild.
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Hearing really good things about GLM 5.2
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Replying to @ThePrimeagen
Great minds think alike!
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Replying to @dabit3
Yes! 馃檶
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One of the best small models out now.
Gemma 4 is a very good small model that punches above it's weight class Gemma is a 31B model that is as good as other very large MoE models It's the best in the world for it's size 馃憦馃憦
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