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Public story · 2026-09-20 · high
His March 2025 arXiv paper gets 32.8ms per response and a calibration error of 0.081, against Jev's 236-276ms and 0.246.
Why now: As of September 20, no counter-benchmark from TypeSafe is public, so Mukkunnoth's numbers are the only public comparison between Jev and Laya.
Nandakishor Mukkunnoth says TypeSafe's Jev repackages the non-autoregressive RL decision architecture he published in March 2025. The claim reached 1,231 points on Hacker News.
The dispute matters most for anyone routing decisions on confidence scores. Mukkunnoth's model scores a calibration error of 0.081, against the 0.246 he attributes to Jev, and a miscalibrated router escalates the wrong cases.
His arXiv paper, 2503.23303, shipped Apache 2.0 weights for two checkpoints: a 421M ModernBERT-large model and a 322M mmBERT-base model. He runs Laya on those weights and clocks 32.8ms per response on a single GPU, against the 236-276ms he measured for Jev. On accuracy, he reports 0.950 on AG News and 0.766 on typed-decision tasks.
TypeSafe sells Jev through a metered API. It hasn't published weights or datasets, so nobody outside the company can test his numbers against Jev directly. Mukkunnoth's checkpoints are public, so anyone can rerun his side of the comparison.
Each link below shares sources, entities, or timing with this story.
NandhaKishorM published it September 18 under Apache 2.0, a non-autoregressive decision engine evaluating typed questions (choice, score, noul) over text, email, tickets or JSON in a single forward pass, at 33ms for one question and 7.2ms per question batched, trained with RL...
Published September 19 on a ModernBERT backbone, using a logit shift, per-token top-12 vocabulary expansion, and case folding of byte-level BPE variants, reaching over 97% recall in about 380 microseconds per query with a Seismic index. Hugging Face The useful part for RAG bui...
laya-mlx, created September 19 at 549 stars, is a native Apple Silicon runtime skipping PyTorch and Transformers entirely (GitHub). It reports 13.4ms median end-to-end for short English questions and 7.4ms on the multilingual checkpoint, 146.8 and 395.0 q/s batched on an M3 Ma...
IFM's lineup showed up on the Artificial Analysis Intelligence Index with the 7B slotting between two much larger Qwen models (r/LocalLLaMA). Two corrections from the thread and the model card: the HF config reports about 8.999B parameters in BF16 for a dense model, and the RE...
Paritok-4B (arXiv 2608.24188) is a LoRA on Qwen3-4B distilled from a gpt-4.1-mini teacher over 67,074 real OpenHands trajectories. It's extractive rather than paraphrasing, with 96.0% of emitted identifiers, paths and numbers already present in its input, and intent-conditione...
Somebody diffed the configs. Zero architectural changes. Same 64 layers, same 5,120 hidden dimension, same hybrid Gated DeltaNet → FFN / Gated Attention → FFN block structure as Qwen3.6-27B. The r/LocalLLaMA post showing this hit 945 upvotes and 157 comments, and Hugging Face...
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