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[GH-ISSUE #14207] Crash in Vulkan backend on Intel Arc when using Ollama through VS Code Continue (Exception 0xe06d7363 during llama_decode) #35016
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opened 2026-04-22 19:07:54 -05:00 by GiteaMirror
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Reference: github-starred/ollama#35016
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Originally created by @Josejsi on GitHub (Feb 11, 2026).
Original GitHub issue: https://github.com/ollama/ollama/issues/14207
What is the issue?
Summary
Ollama crashes when running Qwen2.5‑7B (Q4_K) on an Intel Arc GPU only when the model is invoked through the VS Code Continue extension.
Running the model directly via:
ollama run qwen2.5:7b
works normally and does NOT crash.
However, when Continue sends requests to Ollama (streaming, incremental decoding, multiple small batches), the runner crashes during
llama_decodewith:Exception 0xe06d7363 … signal arrived during external code execution wsarecv: An existing connection was forcibly closed by the remote host
This terminates the runner process and Ollama returns a 500 error.
Why this matters
The crash appears only when Continue triggers Ollama’s decoding pipeline.
This suggests a bug in:
The model loads perfectly, all 29 layers offload to GPU, Flash Attention is enabled, and inference begins normally.
The crash happens only during decoding, not during loading.
Hardware
Ollama Version
Ollama 0.15.6
Model
Qwen2.5-7B
Steps to Reproduce
Running the same prompt directly in the terminal does not crash.
Relevant Log Snippet
Exception 0xe06d7363 0x19930520 0x1de98f9550 0x7ffa3647a80a signal arrived during external code execution llama_decode → crash wsarecv: An existing connection was forcibly closed by the remote host
Full log (including Vulkan memory reports, layer offloading, and crash stack trace) is available here:
Intel GPU Community Issue Tracker report:
https://github.com/IGCIT/Intel-GPU-Community-Issue-Tracker-IGCIT/issues/1356#issuecomment-3879936651
Additional Notes
Expected Behavior
Model should run inference through Continue without crashing the runner.
Actual Behavior
Runner process crashes during
llama_decode, causing Ollama to return a 500 error.Additional Context
Other users with Intel Arc GPUs have reported similar Vulkan crashes under high‑frequency decode workloads in GGML-based projects.
Please let me know if you need additional logs, environment variables, or a reproducible test environment.
@rick-github commented on GitHub (Feb 11, 2026):
Server logs will aid in debugging.
@Josejsi commented on GitHub (Feb 11, 2026):
Click to view full Ollama Server Log
@Josejsi commented on GitHub (Feb 12, 2026):
Update: Tested on v0.16.1 - Issue Persists
The issue remains even after updating to version 0.16.1. Ollama correctly detects the Intel Arc 140V and loads the model into VRAM (approx. 5GB for Qwen2.5 7B), but crashes during inference.
Key Technical Details from Logs:
+2
Full debug logs show that ggml_vulkan is properly initialized but fails during the actual compute execution.
Click to view full Ollama Debug Log
@Josejsi commented on GitHub (Feb 15, 2026):
Update: Migrated to LM Studio for better hardware acceleration
I've decided to move away from Ollama for running LLMs and switched to LM Studio, as it handles my hardware much more efficiently.
Current Setup & Performance:
Hardware: Running on an Intel Arc 140V.
Model: DeepSeek-R1 14B (Distill) with a full 48-layer GPU offload.
Stability: Unlike my previous experience, VRAM management is now rock solid (~13GB/16GB usage), allowing for a lag-free experience in VS Code.
Architecture: I'm now using LM Studio as the primary local server for Chat and Edit roles, while keeping Ollama strictly for embeddings (nomic-embed-text) to handle codebase indexing.