Ollama / Ollama

Ollama GGML_ASSERT(buffer) Failed: CUDA OOM When Loading Multimodal Models like gemma4:26b

Fix Ollama GGML_ASSERT(buffer) failed crash when loading multimodal models with CUDA Includes evidence for Ollama troubleshooting demand.

Source-backed Last updated May 15, 2026 1 source Needs local verification

Category: Ollama
Error signature: GGML_ASSERT(buffer) failed during loading of multimodal model
Quick fix: Compare the failing environment with a known working setup, then change one configuration value at a time.
Updated: May 15, 2026
Verification status: Source-backed
Evidence: 1 public source URL

Before you change production

This page includes public source URLs in the imported troubleshooting record. Compare those references with your version and environment before applying changes.

Reproduce the smallest failing action and save non-secret logs before changing configuration.
Check versions for Ollama, related SDKs, package managers, CI runners, and hosting providers.
Change one setting or dependency at a time, then rerun the same failing command or request.
Avoid destructive commands, credential rotation, billing changes, or security relaxations without a rollback plan.

What this error means

GGML_ASSERT(buffer) failed during loading of multimodal model is a Ollama failure pattern reported for developers trying to fix ollama ggml_assert(buffer) failed crash when loading multimodal models with cuda. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

On Ollama 0.30.0-RC15, loading gemma4:26b crashes with GGML_ASSERT(buffer) failed. Main LLM layers (31/31) offload to GPU successfully, but crash occurs during vision component initialization.

Common causes

Ollama crashes with GGML_ASSERT when loading large multimodal models (gemma4:26b) even when GPU layers appear to load successfully. The crash happens during vision component initialization, not main model loading. Users with adequate VRAM still hit this.
On Ollama 0.30.0-RC15, loading gemma4:26b crashes with GGML_ASSERT(buffer) failed. Main LLM layers (31/31) offload to GPU successfully, but crash occurs during vision component initialization.

Quick fixes

Confirm the exact error signature matches GGML_ASSERT(buffer) failed during loading of multimodal model.
Check the Ollama account, local tool state, and provider configuration involved in the failing workflow.
Compare the failing environment with a known working setup, then change one configuration value at a time.

Platform/tool-specific checks

Verify the command, editor, extension, or API client that produced the error.
Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
Avoid deleting credentials, local model data, or project settings until the failing scope is clear.

Step-by-step troubleshooting

Capture the exact error message and the command, editor action, or request that triggered it.
Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
Review the source evidence below and compare it with your environment.
Apply one change at a time and rerun the smallest failing action.
Keep the working fix documented for the team or deployment environment.

How to prevent it

Keep provider/tool configuration documented.
Record non-secret diagnostics such as tool version, provider name, model name, and command path.
Add a lightweight check before CI or production workflows depend on the tool.

Diagnostic flow for this page

Match GGML_ASSERT(buffer) failed during loading of multimodal model exactly before applying the quick fix.
Compare the failing environment with Ollama versions, account scope, provider settings, and deployment context.
Check the listed common causes in order, starting with the cause that best matches your logs.
Use the evidence status below to decide whether to confirm against public sources or official documentation.
Apply one reversible change, rerun the smallest failing action, and keep rollback notes.

FAQ

What does GGML_ASSERT(buffer) failed during loading of multimodal model mean in Ollama?

GGML_ASSERT(buffer) failed during loading of multimodal model indicates the workflow described by "Ollama GGML_ASSERT(buffer) Failed: CUDA OOM When Loading Multimodal Models like gemma4:26b" failed in a Ollama context. Start by confirming the exact signature and the component that emitted it.

What should I check first for GGML_ASSERT(buffer) failed during loading of multimodal model?

Check whether this cause matches your environment: Ollama crashes with GGML_ASSERT when loading large multimodal models (gemma4:26b) even when GPU layers appear to load successfully. The crash happens during vision component initialization, not main model loading. Users with adequate VRAM still hit this.

Is the GGML_ASSERT(buffer) failed during loading of multimodal model guidance source-backed?

The "Ollama GGML_ASSERT(buffer) Failed: CUDA OOM When Loading Multimodal Models like gemma4:26b" page is labeled source-backed. It has 1 public source URL from github.com, so use that evidence status when deciding how much additional verification you need.

When should I avoid the quick fix for GGML_ASSERT(buffer) failed during loading of multimodal model?

For "Ollama GGML_ASSERT(buffer) Failed: CUDA OOM When Loading Multimodal Models like gemma4:26b", avoid applying "Compare the failing environment with a known working setup, then change one configuration value at a time." when the error text differs, the affected version or provider is different, or the change would touch credentials, billing, DNS, production deploy settings, or irreversible data.

What should I collect before debugging GGML_ASSERT(buffer) failed during loading of multimodal model?

For "Ollama GGML_ASSERT(buffer) Failed: CUDA OOM When Loading Multimodal Models like gemma4:26b", collect the failing Ollama command or request, non-secret configuration, versions, timestamps, request IDs when available, and the smallest reproduction that still triggers the signature.