James Walker 🇬🇧🇺🇦

1.1K posts

James Walker 🇬🇧🇺🇦 banner
James Walker 🇬🇧🇺🇦

James Walker 🇬🇧🇺🇦

@jxwalker

Independent Co. Husband/dad. Alpine hiker. ex Disney, JPM, Credit Suisse, Morgan Stanley, Bank of America and IBM. Work in tech. Own many GPUs and a DXG Spark.

Harpenden, UK Beigetreten Haziran 2009
3.7K Folgt752 Follower
Ivan Fioravanti ᯅ
Ivan Fioravanti ᯅ@ivanfioravanti·
Another video to show the speed of MLX Qwen3-Coder-Next-5bit running on M5 Max with pi and mlx-lm server. In the middle of the video I speed up to show at the end the speed with larger context. More videos to come using LMStudio and others!
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0xSero
0xSero@0xSero·
1 day, the kindness of people knows no bounds.
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Sudo su
Sudo su@sudoingX·
how much VRAM do you have right now
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James Walker 🇬🇧🇺🇦
GSD for the win - it’s like being interviewed by staff engineer who then goes off and doesn’t come back till the build is done. @gsd_foundation have reinvented to coding paradigm for me. I can’t believe how much of my life used to spend in VSC not understanding how any of that shit worked.
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0xSero
0xSero@0xSero·
I had to open this abomination today, holy fuck. How can anyone use this?????
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Alex Ellis
Alex Ellis@alexellisuk·
NVLink installed and showing 14 GB/s bandwidth Next job: getting Qwen3.5 27B running across both 3090s without OOM (Codex is plugging away at it)
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Oğuzhan Dilber
Oğuzhan Dilber@oguzhandilber3·
Far from my Mac but still I’m ‘getting shit done’ from my phone! Shoutout to @official_taches and all contributers for the GSD-2! Uzaktan mac terminalimden GSD ile projelerime devam ediyorum arkadaşlar. Bedava GSD ve 5 dolarlık Alibaba planı ile yapılamayacak iş yok 💯
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James Walker 🇬🇧🇺🇦
All kinds of craziness. A low latency proxy and router in rust with an in-memory low latency ML pipeline. I have never done anything serious in rust before. I now have 110k lines of shippable code that every LLM and security auditor tells me is ”enterprise quality”. It’s like a superpower. I have not touched Claude code or cursor since GSD2 shipped.
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James Walker 🇬🇧🇺🇦
@official_taches @oguzhandilber3 I have turned into a gsd junkie. Night and day. My gsd 2 is relentless. I am running tmux with two panes with tailscale and termius. GSD is building and I have a codex CLI window auditing and giving feedback and helping me keep GSD on a leash.
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Mass
Mass@MemoryReboot_·
Bought my first rtx 3090 Ready to dive into this local LLM rabbit hole Shoutout for @sudoingX for this inspiration See you on the other side
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James Walker 🇬🇧🇺🇦
@alexellisuk CUDA_VISIBLE_DEVICES=0,1 \ vllm serve Qwen/Qwen2.5-Coder-32B-Instruct-AWQ \ --tensor-parallel-size 2 \ --gpu-memory-utilization 0.93 \ --max-model-len 8192 \ --max-num-seqs 8 \ --dtype auto \ --port 8000
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Alex Ellis
Alex Ellis@alexellisuk·
@jxwalker I'm using llama.cpp which will split layers but won't parallelise inference like you're thinking of.. vLLM would be best for that. If/when I get an NVLink I'll be testing out vLLM for sure. How are you using yours?
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Alex Ellis
Alex Ellis@alexellisuk·
I realised that some of my issues with the 3090s may have been from running 1x and not 2x PCIe cables from the 1200W PSU What agentic tasks would you run with 48GB of VRAM?
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𝗭𝗲𝗻 𝗠𝗮𝗴𝗻𝗲𝘁𝘀
I take back my disparagement of @0xSero 's AI rig for the janky PVC trim holding his GPUs up. His GPUs are clearly living the good life. Sitting on nice hardwood floors, breathing fresh human air, eating wet food every day. My shit's in the basement gulag, chained by trip hazard wires, coils whimpering unheard. Ty @LLMJunky for helping my nubass build it.
𝗭𝗲𝗻 𝗠𝗮𝗴𝗻𝗲𝘁𝘀 tweet media𝗭𝗲𝗻 𝗠𝗮𝗴𝗻𝗲𝘁𝘀 tweet media
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Ivan Fioravanti ᯅ
Ivan Fioravanti ᯅ@ivanfioravanti·
What about M5 Max throttling... 👌 New 3nm process applied seems working well! 16" so far so good. I'm pushing it like crazy, it reached 200W of power consumption (how?), thermal state normal! High Power ~78º C as max Automatic ~91º C as max Curious about 14".
Ivan Fioravanti ᯅ tweet media
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James Walker 🇬🇧🇺🇦
@sudoingX I bought the nvlink. Can’t share memory so still hit ooms but will have to test impacting tensor parallelism over it.
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Sudo su
Sudo su@sudoingX·
@jxwalker 2x 3090 NVLink is the one. 48GB unified. run 70B Q4 with no offloading or 27B dense with 500K+ context. NVLink is the last consumer card that supports it and you have it. use vLLM for tensor parallelism across both. the DGX Spark handles anything at full precision. you're set.
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Sudo su
Sudo su@sudoingX·
drop your GPU below. i'll tell you exactly what model and config to run on it. here's what i've tested and verified on real hardware: RTX 3060 12GB - Qwen 3.5 9B Q4 - 50 tok/s - 128K context RTX 3090 24GB - Qwen 3.5 27B Q4 - 35 tok/s - 300K context RTX 3090 24GB - Qwen 3.5 35B MoE Q4 - 112 tok/s - 262K context 2x RTX 3090 - Qwen3-Coder 80B Q4 - 46 tok/s - full VRAM all running llama.cpp with flash attention. every number is real. every config is tested. if your card isn't on this list drop it below and i'll tell you what fits.
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James Walker 🇬🇧🇺🇦
@ivanfioravanti 16 inch. I was going for the 4 and thought I could spill to my NAS if I needed to but it was only an extra 1k for the extra 4t and the performance of the Mac nvme is insane. My NAS is spinners on a 2.5 gb network so no comparison
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Ivan Fioravanti ᯅ
Ivan Fioravanti ᯅ@ivanfioravanti·
I'll keep testing M5 Max and posting here some results. I will then create some articles to wrap up the various things I'm discovering.
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