First - credits where credits due to post by @tonyd615 and @11_p who pointed me to a right direction: DeepSeek-V4-Flash (official FP8) running across 2x DGX Spark — TP=2, MTP, 200K ctx, recipe + numbers - #174 by 11_p as more so to original creator of recipe @aidendle94 and reddit post Reddit - Plea…

Qwen 3.5 .8 MLX is like 1-2gb I think it does great captioning of photos

@aidendle94 Tried production-hybrid-1.0; I’m not getting past 1600PP and 30TG. Not sure but I do get a cuteDSL error with b12x moe in the vllm logs. I’ll copy paste when I am home is this something anybody else seeing?

That’s for GLM. Please refer to 3.7 or 3.75. Currently working on GLM sorry

I am running production-hybrid-1.1, it looks good to me on ds4-dspark ( I am using @0rand ’s starting script). So are you going to support different models in your image instead of one model per image strategy?

Separate image series for each model probably.

@aidendle94 What’s the difference between 3.7 vs 3.75? Do you think there are more increase in performance to be had for DS4F + DSpark? Thank you for your amazing work on this!

Setup worked fine with @0rand Github. But when running it for some time I got a Triton Error in the B12X MoE kernel. Could not load the compiled kernel (Production 3.7). I will do a benchmark later and post it here.

I have noticed there might be some parameter leakage in the nested shells implementing recipe in yaml. It could technically lead to improper values set to vllm like temperature. It should ignore and use default (you can see reports during the boot) but who knows. Just extra quotes wrapping. Easy fix…

Are those number expected for your Github? I am not sure if this is working correctly. This is the 3.7 production version. ======================================== c1 | d1024 ======================================== ============ Serving Benchmark Result ============ Successful requests: …

I suggest to measure using llama-benchy or tool-eval-bench for consistency to make sure you get similar results. The way different benches gather and interpret metrics can make results look very different. Especially for concurrents. PS however it this case something is definitely not right - it ap…

DeepSeek v4 Flash (Aiden Recipe from Reddit) - 1M token session operational, Cuda 12.1 tailored for DGX Spark GB10

Accelerated Computing DGX Spark / GB10 User Forum DGX Spark / GB10

aidendle94 July 23, 2026, 6:13am 405

There was some optimizations to shard more parts of the model to reduce overhead.

I’ll work more on this once 4.1 comes out

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DeepSeek v4 Flash (Aiden Recipe from Reddit) - 1M token session operational, Cuda 12.1 tailored for DGX Spark GB10

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