I shrank DeepSeek V4 Flash to 57GB and it wrote a compiler on my Mac
I built a specialized package of DeepSeek V4 Flash 0731 (originally 284B total parameters, 13B active), preserving reasoning, tool calling and coding capabilities: https://huggingface.co/steadfastgaze/DeepSeek-V4-Flash-0731-... I let it write a minimal C compiler targeting ARM64, then test the result with Fibonacci and FizzBuzz programs, and it succeeded in less than 1 hour, with the full recording at: https://youtu.be/XiwSilmV8B0 You can run it on Silicon Macs with my engine https://github.com/steadfastgaze/MoEspresso, while one of the…
I shrank DeepSeek V4 Flash to 57GB and it wrote a compiler on my Mac launched on August 16, 2026 with 21 votes, #737 of 23,274 launches that month and more than 90% of that year's launches.
In plain words
DeepSeek-V4-Flash-0731-Coder is a specialized 57GB model package optimized for coding tasks, built by reducing the original 284B parameter model while preserving reasoning and tool-calling capabilities. It runs on Silicon Macs using the MoEspresso engine and can generate functional code, including compilers. The package is designed for developers and AI agents working on coding tasks, with support for context windows up to 128K tokens and inference speeds around 5 tokens per second on machines with 32GB memory.
written from the facts on this page · September 2026
From the sources
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
This is a 56.869 GB coding-specialized MoEspresso package derived from DeepSeek-V4-Flash-0731 . Its model safetensors occupy 56.831 GB, 32.63% less than the 84.355 GB MoEspresso 2.37 bpw package . The package removes about 80B parameters, leaving 204B total, with about 13B active per token. The package requires MoEspresso 2.1 or newer. MoEspresso is the only engine that serves it. llama.cpp, transformers, and mlx-lm will not load these files. This package is intended for coding and coding-agent workloads. It is not a smaller general-purpose replacement for the 2.37 bpw package. The measurements below show both the coding retention and the general-text regression. Lower NLL and perplexity…from huggingface.co
In the maker’s words, at launch
I built a specialized package of DeepSeek V4 Flash 0731 (originally 284B total parameters, 13B active), preserving reasoning, tool calling and coding capabilities: https://huggingface.co/steadfastgaze/DeepSeek-V4-Flash-0731-... I let it write a minimal C compiler targeting ARM64, then test the…
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Distilling DeepSeek into GPT-OSS doesn't transfer censorship. Try itJul 2026 · ctgt.ai · ▲170We recently used DeepSeek V4 Flash as a teacher for finance tasks with GPT-OSS-120B. Distillation works well on this problem. At a constrained 8k token budget, our self-distilled 120B scores 83.61% on FinanceReasoning, above Kimi K3 (81.93%) and Inkling (65.13%). We released the 20B open weights. With V4 as the teacher though, we realized it would be timely to measure if the censorship characteristic of it transferred to the distilled version of the base model. tl;dr it didn't, the teacher answered politically sensitive questions 7 SDs differently than expected, but the distilled model's…
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