N8 Programs @N8Programs
Studying Applied Mathematics and Statistics at @JohnsHopkins. n8python.github.io Proxima Centauri B Joined September 2022-
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N8 Programs retweeted
The latest MLX LM supports batch inference for ssm / conv / hybrid models. Here's 8 simultaneous generations with LFM 2.7B on M4 Max with >21k token context per example:
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My guesses (that deviate from Teo's) Arch: 1.8T, 65B active, 25-30T tokens. Probably uses some variant of Muon tuned for large scale training - akin to MuonClip (which Kimi employed). Likely vanilla NSA. Probably no O(n) attention hacks (mamba, deltanet) Potentially gated…
My guesses (that deviate from Teo's) Arch: 1.8T, 65B active, 25-30T tokens. Probably uses some variant of Muon tuned for large scale training - akin to MuonClip (which Kimi employed). Likely vanilla NSA. Probably no O(n) attention hacks (mamba, deltanet) Potentially gated…
N8 Programs retweeted
New ARC Prize 2025 High Score 27.08% by Giotto. ai (@podesta_aldo)
claude 4.1 vibes vindicated???
Local AI of a different sort
N8 Programs retweeted
It's becoming increasingly clear that gpt5 can solve MINOR open math problems, those that would require a day/few days of a good PhD student. Ofc it's not a 100% guarantee, eg below gpt5 solves 3/5 optimization conjectures. Imo full impact of this has yet to be internalized...
N8 Programs retweeted
this reminds me of this meme 😅
this reminds me of this meme 😅 https://t.co/iRyyk539Nm
N8 Programs retweeted
AI companies often grade their own homework. So are they cheating on the test? We wanted to see how companies’ test results compare to our own findings on the GPQA diamond benchmark. So what did we find? No signs of cheating! Here’s our methodology: 🧵
N8 Programs retweeted
when chatgpt said moondream wasn't a frontier model, i took it personally
when chatgpt said moondream wasn't a frontier model, i took it personally
ITS HERE - probably the most carefully constructed VLM I know of.
ITS HERE - probably the most carefully constructed VLM I know of.
Amazing work in the latest mlx-lm release in this PR: github.com/ml-explore/mlx…
Qwen3-next also can do gemini like doomloop sometimes
N8 Programs retweeted
M3 Ultra vs M4 Max with Qwen3-Next-80B-A3B-Instruct-4bit context benchmarks! Current and Custom Kernel (ck in charts). Spoiler: Yes M4 Max is faster in text generation with small context. The "only" 3B active params helps here. 🧵
This changes so much. Up to 10x faster throughput at high batch sizes
This changes so much. Up to 10x faster throughput at high batch sizes
N8 Programs retweeted
We’re releasing GPT-5-Codex — a version of GPT-5 further optimized for agentic coding in Codex. Available in the Codex CLI, IDE Extension, web, mobile, and for code reviews in Github. openai.com/index/introduc…
N8 Programs retweeted
While tokenizer of >3B models are probably too small, I feel it's the reverse for small models. So long as multilingual support cannot be extensive (or maybe, h-net will save us?), less than 10k tokens is already good enough compression, and really save on embed space
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