Ollama
Local LLM inference server exposing an OpenAI-compatible REST API at localhost:11434 for running open-weight models entirely on your own hardware.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
No auth and no TLS by default — safe only on localhost. Exposing OLLAMA_HOST to a network without a reverse proxy is a significant risk. Model weights are stored locally in ~/.ollama/models.
⚡ Reliability
Best When
You need zero-cost, private, offline LLM inference for development or on-premise deployment and your target models are available as GGUF/GGML-compatible open weights.
Avoid When
Your agent requires state-of-the-art frontier model performance, or you need to run more than a handful of concurrent requests without GPU memory headroom.
Use Cases
- • Run agent inference loops entirely offline and air-gapped with no data leaving the local machine
- • Use the OpenAI-compatible /api/chat endpoint so agents written for OpenAI can switch to local models by changing base_url only
- • Pull and manage multiple quantized models (llama3, mistral, codestral) and route different agent tasks to the most cost-effective model size
- • Create custom Modelfile personas with baked-in SYSTEM prompts and PARAMETER settings for specialized agent roles
- • Stream token-by-token output from long agent reasoning chains without timeout risk from remote provider APIs
Not For
- • Cloud-deployed agents that need SLA-backed uptime — Ollama is a local daemon with no managed availability
- • Agents requiring the latest frontier models (GPT-4o, Claude 3.5) — only open-weight models are available
- • High-concurrency production workloads where many agents share a single Ollama instance — request queuing is basic
Interface
Authentication
No authentication by default; the server binds to localhost only. To expose over a network, set OLLAMA_HOST and consider adding a reverse proxy with auth. No built-in API key support.
Pricing
Completely free and open source. Compute costs are your own hardware.
Agent Metadata
Known Gotchas
- ⚠ Model must be pulled before first use with `ollama pull <model>`; agents calling an un-pulled model get a 404 error, not an automatic download
- ⚠ Context window defaults vary by Modelfile and may be shorter than advertised model capacity; explicitly set num_ctx in options or the model may silently truncate long prompts
- ⚠ The OpenAI-compatibility layer (/v1/chat/completions) does not support all OpenAI parameters; unsupported fields are silently ignored rather than rejected
- ⚠ Concurrent requests queue behind each other on a single GPU — a long-running agent request will block all other agent calls until it completes
- ⚠ Model unloading from VRAM happens after a keep_alive timeout (default 5 minutes); the next request incurs a cold-load penalty that can exceed 10 seconds for large models
Alternatives
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Scores are editorial opinions as of 2026-03-06.