Ollama / Ollama

Ollama OOM crash during GGUF metadata parsing in v0.24.0

Fix Ollama server crashing with OOM during GGUF metadata parsing after upgrading to v0.24.0 Includes evidence for Ollama troubleshooting demand.

Source-backed Last updated May 16, 2026 1 source Needs local verification

Category: Ollama
Error signature: runtime: out of memory during GGUF metadata parsing (readString/n_kv allocation) in Ollama v0.24.0
Quick fix: Compare the failing environment with a known working setup, then change one configuration value at a time.
Updated: May 16, 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

runtime: out of memory during GGUF metadata parsing (readString/n_kv allocation) in Ollama v0.24.0 is a Ollama failure pattern reported for developers trying to fix ollama server crashing with oom during gguf metadata parsing after upgrading to v0.24.0. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub issue #16175 filed 2026-05-15 against ollama/ollama, labeled bug. Ollama v0.24.0 crashes on startup with fatal OOM error during GGUF metadata parsing on RTX 5060 Ti 16GB + 32GB RAM system. Category mapped to Ollama per approved category list.

Common causes

GitHub issue #16175 filed 2026-05-15 against ollama/ollama, labeled bug. Ollama v0.24.0 crashes on startup with fatal OOM error during GGUF metadata parsing on RTX 5060 Ti 16GB + 32GB RAM system. Category mapped to Ollama per approved category list.

Quick fixes

Confirm the exact error signature matches runtime: out of memory during GGUF metadata parsing (readString/n_kv allocation) in Ollama v0.24.0.
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 runtime: out of memory during GGUF metadata parsing (readString/n_kv allocation) in Ollama v0.24.0 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 runtime: out of memory during GGUF metadata parsing (readString/n_kv allocation) in Ollama v0.24.0 mean in Ollama?

runtime: out of memory during GGUF metadata parsing (readString/n_kv allocation) in Ollama v0.24.0 indicates the workflow described by "Ollama OOM crash during GGUF metadata parsing in v0.24.0" failed in a Ollama context. Start by confirming the exact signature and the component that emitted it.

What should I check first for runtime: out of memory during GGUF metadata parsing (readString/n_kv allocation) in Ollama v0.24.0?

Check whether this cause matches your environment: GitHub issue #16175 filed 2026-05-15 against ollama/ollama, labeled bug. Ollama v0.24.0 crashes on startup with fatal OOM error during GGUF metadata parsing on RTX 5060 Ti 16GB + 32GB RAM system. Category mapped to Ollama per approved category list.

Is the runtime: out of memory during GGUF metadata parsing (readString/n_kv allocation) in Ollama v0.24.0 guidance source-backed?

The "Ollama OOM crash during GGUF metadata parsing in v0.24.0" 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 runtime: out of memory during GGUF metadata parsing (readString/n_kv allocation) in Ollama v0.24.0?

For "Ollama OOM crash during GGUF metadata parsing in v0.24.0", 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 runtime: out of memory during GGUF metadata parsing (readString/n_kv allocation) in Ollama v0.24.0?

For "Ollama OOM crash during GGUF metadata parsing in v0.24.0", 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.