Spark abruptly shuts down

Hi

I got a dgx spark. When i load qwen 3.5 122b on it and it gets to work, after a while, it different shuts down with no warning or anything.

Everything’s updated and Ive used only the original adaptor. And don’t remember this happening with only qwen 35b but it has also happened with both qwen 35b and 27b loaded. Only loading doesn’t make it shutdown but when i let them do a bunch of jobs, this happens. I also experienced the same issue running gemma 4 diffusion gemma 26b using unsloth studio.

Any ideas? At this point, my spark is no use to me. I got it for heavy work and now, it can’t do even simple stuff

Don’t write it off — we had this identical symptom on our 2× DGX Sparks (hard death under sustained load, fine at idle, model-agnostic, no warning, sometimes needing a physical power-cycle) and it turned out to be fixable in software + firmware. The tell is in your own report: it’s model-agnostic and only dies once they’re doing real work, never just loading — and it got worse with two models loaded at once (your 35b+27b). That’s the fingerprint of the GB10’s 128GB unified-memory cliff, not a bad model.

Here’s what actually fixed it for us, in order:

1. Give the unified memory real headroom (this was the big one). On the GB10, weights + KV cache + CUDA workspace all share one 128GB pool. Under sustained jobs the KV cache grows, and if total allocation creeps past the pool you do not get a clean OOM — you get a UVM page-migration livelock that hard-locks the whole box with no warning and no log, and the OOM-killer never fires. Loading two big models (35b+27b) or the 122B leaves almost no headroom, so a busy run tips it over. Fix: cap how much the server grabs — in vLLM that’s the flag --gpu-memory-utilization set to 0.85–0.92 (not 0.94+), and don’t co-load multiple large models. Leave ~10–15GB free. This alone stopped ours from dying.

2. Update the platform firmware — BIOS/BMC, not just the OS. “Everything’s updated” almost always means OS packages + driver. The Spark’s system firmware is a separate update and it materially improved our stability under sustained load. Do that update specifically.

3. Cap the GPU’s max power draw. Enable persistence mode and pull the power limit a touch under max so sustained inference can’t spike past the envelope — enable it with sudo nvidia-smi -pm 1, then set the cap with sudo nvidia-smi -pl followed by a wattage a few watts under the reported max.

4. Lock the clocks. Pinning the clocks instead of letting them boost and drop kills the power transients that compound everything above — do it with sudo nvidia-smi -lgc followed by your min,max clock values.

Do #1 and #2 first — between capping memory utilization and updating the platform firmware, ours went from dying every heavy run to rock-solid. #3 and #4 are the belt-and-suspenders for the power/thermal side.

And keep the physical basics honest too: dedicated wall circuit (ideally a UPS), real airflow clearance — a browning circuit or heat-soak will still trip it no matter how clean the config. But start with the memory cap; that’s the one that gets described as “dies under load for no reason” the most.

Thank you very much. I feel blessed that someone took this much time to help me. I’ll try out everything you suggested and i hope it works out. Thanks a lot 🌷💐

Please run DGX Spark Field Diag and share the results Get the Right Support for Your DGX Spark — DGX Spark User Guide

I had this happen on two occassions in a room sitting at 32 degrees C. The computer (msi EdgeXpert) kept it’s cool but I have the impression that the power supply overheated. The PSU was laying flat on a carpeted floor and it’s underside was extremely hot. The solution for me was to stand the PSU up on it’s edge, and it hasn’t failed since. I tried a cooling rack from the kitchen but that’s when it failed a second time. While the machine has great cooling the PSU does not.

Thanks for all the help you all gave me. limiting the clock helped. i used this command and after that, i havent encountered the issue yet and hopefully i wont again:
sudo nvidia-smi -lgc 300,2800

Also, i couldnt get the dgx spark field diag to get working (my internet connection is extremely laggy and also, im currently in a country where NVIDIA doesnt support it and blocks this region and i cant get out due to issues in the region. Also (and most important), im not an expert and perhaps this is why i couldnt run it.

However, these passed weeks were extremely frustrating and i thought ive wasted my money. Now im hopeful and thats because you wonderful people helped me.

These instructions don’t work for me, any ideas?

danny@toad:~$ sudo apt install dgx-spark-fieldiag
Reading package lists... Done
Building dependency tree... Done
Reading state information... Done
Some packages could not be installed. This may mean that you have
requested an impossible situation or if you are using the unstable
distribution that some required packages have not yet been created
or been moved out of Incoming.
The following information may help to resolve the situation:

The following packages have unmet dependencies:
 dgx-spark-fieldiag : Depends: ofed-scripts but it is not installable
E: Unable to correct problems, you have held broken packages.

@DannyTup use the previous version. The 2.0 was pushed to the repos about a month ago (that’s when I observed it) but with unmet dependencies, i.e. ofed-scripts. It hasn’t been fixed yet.

sudo apt install dgx-spark-fieldiag=1.0.9-1

Changelog between 1.0.9 and 2.0.4:

  20 │   Prerequisite tools that must be installed before running the diagnostic
  21 │   --------------------------------------------------------------------
  22 │   1) stress-ng: Required to run CPU stress test.
  23 │   2) fio: Required to run SSD stress test.
  24 │   3) memtester: Required to run memory stress test.

  20 │   Prerequisite tools/packages that must be installed before running the diagnostic
  21 │   --------------------------------------------------------------------
  22 │   1) stress-ng: Required to run CPU stress test.
  23 │   2) fio: Required to run SSD stress test.
  24 │   3) memtester: Required to run memory stress test.
  25 │   4) infiniband-diags, mft, opensm, ofed-scripts: Required to run CX7 Stress test.

Please reference the Fieldiag User Guide to install the requisite dependencies. They are needed to test the CX7 module

I’m not trying to test the CX7 module, I’m just trying to install the field diagnostics initially, that’s what’s failing.

If the CX7 dependencies are required to be installed before installing the field diagnostics, I think this doc should be updated. Currently it tells you to install field diagnostics first, and later says:

The CX7Stress test requires additional tools that are not installed when you install the dgx-spark-fieldiag .deb package. Before you run field diagnostics, install DOCA Host and the related packages on your system

It would be convenient if the docs gave the correct commands to install to run the field diagnostics in the correct order. I’d prefer not to install additional things that aren’t necessary, but it’s unclear to me exactly what is/isn’t required. The steps in the doc do not work in the order they are given.

Thank you for the feedback. I will pass it along to improve the documentation.
Installing the networking modules is necessary to install the latest fieldiag version. There are also instructions to remove them if you do not want them to stay installed after running the fieldiag test.

Oh, something else to note - the sigining key and repo it asked me to install also caused issues - after running those commands, apt get reported that there were two signing keys for the same repository. I had to undo some of those commands.

I think it would be worth someone going through the docs on a clean install (with all updates).

Thanks, I will try again when I get some time.

dgx-spark-fieldiag 2.0 adds the CX7 test. That needs the DOCA packages. It also requires two kernel modules to be build and loaded, the mst_cpi and mst_pciconf complicating the setup. If networking is okay the previous dgx-spark-fieldiag package provides the stress-ng, fio and memtester. These are the test that matter!

unforunately it abruptly shut down again today. the clock speed was at around 2420 so ii changed the command to sudo nvidia-smi -lgc 300,2400
it wasnt shut down again after that.

If you continue to have issues after, I would run the field diagnostic like people said. I had to get mine RMA’ed and waiting for a new unit. Had sensor problems that was just straight shutting down my spark.

the abrupt shut downs occurred yesterday again so i gave ran the dgx spark field diag with the help of codex and gpt 5.6 sol ultra. this is the report given to me by codex. there are so many things it said. i asked it to summarize. this is its response:

I ran the DGX Spark field diagnostics on August 1, 2026.

My system abruptly powers off under GPU load. Before the last shutdown,
nvidia-smi reported about 77 C, but the hidden package sensor reached 96.6 C.

Results:

  • GpuStress: passed on retry
  • CpuStress1: passed
  • CpuStress2: passed
  • C2CStress: passed
  • MemStress: passed
  • PowerStress: FAILED
    MODS-020000600139
    “Acceptable temperature limits exceeded or the thermal sensor is broken or
    miscalibrated”
  • ThermalStress: FAILED
    MODS-020000281445
    “Thermal resistance is too high”
  • CX7Stress: failed (“Infiniband: Failed”)

ThermalStress measured filtered thermal resistance of 0.484 C/W, maximum
0.562 C/W, with a 16.8 C hidden-hotspot offset.

I added a temporary 2000 MHz thermal-guard cap. A guarded 10-minute load
validation then completed with 16/16 requests, zero failures, and a maximum
hidden temperature of 82.7 C. The underlying ThermalStress failure remains."

Well, perhaps unsurprisingly, mine failed the test:

Can you confirm what the next steps are? How long does the replacement process take? The retailer I bought it from (Scan UK) advertised a 48hr-turnaround if it needed to be replaced, so if nvidia would take longer than that, I think I might prefer to send it to them?

Thanks

Shutdown issues reported by some DGX Spark/GB10 users are being investigated.

We’ll provide an update as soon as we have more information. Thank you for your patience and help by reporting details!

Hi @DannyTup Please contact NVIDIA Consumer Support requesting an RMA, and you can cite this thread for approval. (Explicitly, this is approved due to field diagnostic failures)

You’re, of course, free to pursue other replacement options such as by your retailer. I cannot confirm RMA turn around times, so if you have a guaranteed time via other channel you might pursue that option as an alternative.

Since your device failed field diagnostics, you can contact NVIDIA Customer Support Resources for a replacement (RMA).