Nemotron 3.5 Bolt on GB10: intermittent "prepared model reported device error 6" mid-stream at concurrency 1

Abierto
  • ¿Algo no está bien?
#52 0 comentarios 0 reacciones 0 asignados Ver en GitHub

Los mantenedores suelen responder en 1 día

Nadie ha tomado este issue todavía.

Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
48/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
python
Área
backend, performance

Línea de trabajo

Start by tracing where streaming decode reports prepared model reported device error 6, then compare that path with the intermittent KV page reuse issue in #14. Reproduce with the supplied GB10 setup and sequential streaming requests at --max-concurrency 1, using the offered debug build or request bodies to capture more detail. Done when the cause is identified and the supplied workload no longer produces mid-stream errors.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

bug model:nemotron-3.5-bolt priority:P2 triage:investigate

Summary

Streaming chat completions intermittently fail mid-stream with prepared model reported device error 6 on a single DGX Spark (GB10) serving Nemotron 3.5 Bolt at --max-concurrency 1. The first token is streamed, then the stream ends with a server_error. 4 of the first 11 requests to this server process failed, all from one agent session.

Environment

  • NVIDIA DGX Spark, GB10 (SM121), driver 580.178.04, CUDA 13.0, kernel 7.0.0-1019-nvidia
  • Flare 47581cc (2026-10-20), release build
  • Package: nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB, exported for concurrency 4
  • Command: flare run bolt-lilicorr-c4.safetensors --gpus 0 --host 0.0.0.0 --port 8000 --served-model-name nemotron-3.5-bolt --kv-cache-limit concurrency --max-concurrency 1
  • Startup: Prepare execution. concurrency 1, Plan cache. per GPU: 27.73 GiB loaded · 69.30 GiB cache budget · reserve 4GiB · KV capped at 1 contexts

Workload

One OpenCode agent session (OpenAI-compatible /v1/chat/completions, stream: true, tools defined, chat_template_kwargs.enable_thinking: false). Requests are sequential; there is never more than one in flight. Prompt sizes at the failures were about 28K–53K tokens, mostly a reused prefix.

Server log

[Fri, 23 Oct 2026 10:16:08 GMT] request_id=chatcmpl-1307976-6 stage=stream code=server_error message="prepared model reported device error 6"
[Fri, 23 Oct 2026 10:16:46 GMT] request_id=chatcmpl-1307976-7 stage=stream code=server_error message="prepared model reported device error 6"
[Fri, 23 Oct 2026 10:16:50 GMT] request_id=chatcmpl-1307976-8 stage=stream code=server_error message="prepared model reported device error 6"
[Fri, 23 Oct 2026 10:22:57 GMT] request_id=chatcmpl-1307976-11 stage=stream code=server_error message="prepared model reported device error 6"

Client-side error

{"type":"server_error","message":"prepared model reported device error 6","param":null,"code":"server_error"}

The HTTP status is 200; the error arrives in the stream after the first content token.

Notes

  • The server stays up after each error, and the next request succeeds.
  • The same error appeared on 2026-10-21 with the same package under concurrent requests.
  • Possibly related: #14 (intermittent mid-decode errors from reused KV pages on SM120). The error code here is 6, not 1.

I can provide the full request bodies or run a debug build if that helps.

Lenguaje dominante
Rust
Estrellas
800
Forks
106
Merge medio
1 d 3 h
PR fusionados (30 d)
100

Preparar el entorno

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

Más de NVIDIA/hyperflare-inference

Todos los issues de NVIDIA/hyperflare-inference

Issues similares

Más issues de Rust

Recibe los nuevos issues en tu correo

Un resumen breve de issues de GitHub para principiantes.