GraphCanon
Home/Compare/llama.cpp vs ollama

Comparison

llama.cpp vs ollama

Verdict

Ollama and llama.cpp are both open-source tools for deploying and performing inference with large language models, but they cater to different needs and preferences. Ollama is a Go-based framework that supports a wide range of models and is suitable for developers who prefer Go and need flexibility across various deployment platforms. llama.cpp, on the other hand, is a C++ tool.

Markdown twin · llama.cpp alternatives · ollama alternatives

GraphCanon updated Sep 30, 2026

48views this month

llama.cpp logo

llama.cpp

ggml-org/llama.cpp

★ 129kpushed Sep 18, 2026
vs
ollama logo

ollama

ollama/ollama

★ 181kpushed Sep 17, 2026

Trust & integrity

Signalllama.cppollama
Maintenance
Very active (0d since push)
As of Sep 18, 2026 · github_public_v1
Very active (0d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
No published findings from this source as of 2026-09-18
As of Sep 18, 2026 · osv@v1
Published findings
As of Sep 18, 2026 · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Published findings
As of Aug 9, 2026 · deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
No public record from this source
As of Aug 2, 2026 · openssf-scorecard@v1
llama.cpp trust reportollama trust reportTrust methodology

Tagline

llama.cpp
LLM inference in C/C++
ollama
Get up and running with Kimi, GLM, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.

Stars

llama.cpp
129k
ollama
181k

Forks

llama.cpp
23k
ollama
18k

Open issues

llama.cpp
2.5k
ollama
4.0k

Language

llama.cpp
C++
ollama
Go

Adopt for

llama.cpp
llama.cpp is a C++ tool for performing inference with large language models, offering a lightweight and efficient alternative to Python-based solutions.
ollama
Ollama is a Go-based framework for deploying and running various large language models, including Kimi, GLM, MiniMax, DeepSeek, gpt-oss, Qwen, and Gemma.

Persona

llama.cpp
-
ollama
-

Runtime

llama.cpp
-
ollama
-

License

llama.cpp
MIT
ollama
MIT

Last pushed

llama.cpp
Sep 18, 2026
ollama
Sep 17, 2026

Categories

llama.cpp
Inference & Serving
ollama
Inference & Serving, LLM Frameworks

Trust and health

Open issues (now)

llama.cpp
2.5k
ollama
4.0k

Stars delta

llama.cpp
+5.7k (30d)
ollama
+3.7k (30d)

Open issues delta

llama.cpp
+522 (30d)
ollama
+451 (30d)

OSV dependency advisories

llama.cpp
No published findings from this source as of 2026-09-18
ollama
Published findings

deps.dev advisories

llama.cpp
Not queried
ollama
Published findings

OpenSSF Scorecard

llama.cpp
Not queried
ollama
No public record from this source

Full report

llama.cpp
Trust report
ollama
Trust report

Typed relationship

llama.cpp related ollamaBoth Ollama and llama.cpp are related to LLM inference, but while Ollama seems to provide a broader ecosystem (models + infrastructure), llama.cpp is specific to C/C++ inference.

Choose llama.cpp if…

  • llama.cpp is primarily C++; ollama is Go.
  • Both Ollama and llama.cpp are related to LLM inference, but while Ollama seems to provide a broader ecosystem (models + infrastructure), llama.cpp is specific to C/C++ inference.
  • Tags unique to llama.cpp: c++, ggml, llm-inference.
  • When you need a fast and lightweight solution for LLM inference that can be integrated into C++ projects.

When NOT to use llama.cpp

  • If your project is already heavily invested in Python and you do not want to introduce another language for inference.
  • When you need extensive model training capabilities, as llama.cpp focuses solely on inference.
  • If you are looking for a tool with a large community and extensive documentation, as llama.cpp might have a smaller community and less comprehensive support compared to some Python-based alternatives.
GitHubDetails

Choose ollama if…

  • ollama is primarily Go; llama.cpp is C++.
  • Both Ollama and llama.cpp are related to LLM inference, but while Ollama seems to provide a broader ecosystem (models + infrastructure), llama.cpp is specific to C/C++ inference.
  • Tags unique to ollama: deepseek, gemma, glm, go.
  • Also covers LLM Frameworks.
  • ollama ships Docker support for self-hosted deployment.
  • When you need a framework that supports a wide range of large language models, including Qwen and Gemma, and you prefer using Go for development.

When NOT to use ollama

  • If your project is heavily reliant on Python or another language and you prefer not to introduce Go into your tech stack.
  • When you need a framework that is tightly integrated with a specific model or ecosystem that Ollama does not support, such as models that are only available through a different framework or language.
GitHubDetails

Explore

llama.cpp trust report →ollama trust report →Inference & Serving category →LLM Frameworks category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: llama.cpp 129k · ollama 181k (synced Sep 20, 2026).

Common questions

Which tool should I use if I prefer Go and need support for a wide range of models?
Ollama is the better choice if you prefer Go and need support for a variety of large language models.
What if my project is heavily reliant on Python?
Neither Ollama nor llama.cpp would be ideal if your project is heavily reliant on Python, as Ollama is Go-based and llama.cpp is C++-based.
Can I use these tools for model training?
No, both Ollama and llama.cpp are primarily for inference. If you need model training capabilities, you would need to look for other tools or frameworks.
Which tool is more suitable for resource-constrained devices?
llama.cpp is more suitable for resource-constrained devices as it is designed to be lightweight and efficient, making it a good choice for devices where Python-based alternatives might be too heavy.
What is the difference between llama.cpp and ollama?
llama.cpp: LLM inference in C/C++. ollama: Get up and running with Kimi, GLM, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.. See the comparison table for live GitHub stats and shared categories.
When should I choose llama.cpp over ollama?
Choose llama.cpp over ollama when llama.cpp is primarily C++; ollama is Go; Both Ollama and llama.cpp are related to LLM inference, but while Ollama seems to provide a broader ecosystem (models + infrastructure), llama.cpp is specific to C/C++ inference; Tags unique to llama.cpp: c++, ggml, llm-inference; When you need a fast and lightweight solution for LLM inference that can be integrated into C++ projects.
When should I choose ollama over llama.cpp?
Choose ollama over llama.cpp when ollama is primarily Go; llama.cpp is C++; Both Ollama and llama.cpp are related to LLM inference, but while Ollama seems to provide a broader ecosystem (models + infrastructure), llama.cpp is specific to C/C++ inference; Tags unique to ollama: deepseek, gemma, glm, go; Also covers LLM Frameworks; ollama ships Docker support for self-hosted deployment; When you need a framework that supports a wide range of large language models, including Qwen and Gemma, and you prefer using Go for development.
When should I avoid llama.cpp?
If your project is already heavily invested in Python and you do not want to introduce another language for inference. When you need extensive model training capabilities, as llama.cpp focuses solely on inference. If you are looking for a tool with a large community and extensive documentation, as llama.cpp might have a smaller community and less comprehensive support compared to some Python-based alternatives.
When should I avoid ollama?
If your project is heavily reliant on Python or another language and you prefer not to introduce Go into your tech stack. When you need a framework that is tightly integrated with a specific model or ecosystem that Ollama does not support, such as models that are only available through a different framework or language.
Is llama.cpp or ollama more popular on GitHub?
ollama has more GitHub stars (181,196 vs 128,639). Stars measure visibility, not whether either tool fits your constraints.
Are llama.cpp and ollama open source?
Yes - both are open-source projects on GitHub (llama.cpp: MIT, ollama: MIT).
Where can I find alternatives to llama.cpp or ollama?
GraphCanon lists graph-backed alternatives at llama.cpp alternatives and ollama alternatives (llama.cpp markdown twin, ollama markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, llama.cpp or ollama?
llama.cpp: Very active. ollama: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for llama.cpp and ollama?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llama.cpp trust report; ollama trust report.

Was this helpful?

Anonymous feedback helps us improve pages and translations.