LOCAL AI. FULL VISIBILITY.

See what your Ollama models are really doing.

Monitor requests, logs, latency, token usage, model performance, and errors across your Ollama instances — locally or in the cloud.

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cloud_done Local or cloud
terminal Built for developers
hub Open ecosystem
WHY OLLAMA MONITOR

Everything happening inside Ollama. Visible.

Turn raw logs into meaningful insights. Understand your models, optimize performance, and troubleshoot faster.

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Live Request Monitoring

See incoming Ollama requests and model activity in real time with minimal resource overhead.

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Token Analytics

Track prompt tokens, generated tokens, context usage, and total consumption across every session.

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Performance

Measure latency, generation speed, tokens per second, and request duration across local weights.

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Model Analytics

Compare how different local models perform under parallel load, quantization, and context scales.

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Error Tracking

Quickly identify failed requests, CUDA out-of-memory states, and runtime backend faults.

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Multi-Instance

Monitor Ollama across multiple developer machines, local edge clusters, and cloud inference environments.

HOW IT WORKS

From raw Ollama logs to useful insights.

A simple setup. Powerful insights. Works locally or in the cloud without modifying your application stack.

1

Connect

Run a lightweight monitoring agent next to Ollama via CLI, Docker sidecar, or native binary.

2

Collect

Capture logs, request metadata, model activity, token statistics, and hardware inference metrics.

3

Analyze

Explore the data locally or securely send telemetry to the cloud for centralized monitoring.

Your Environment
laptop_mac Mac / Linux / Server
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neurology Ollama
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developer_board Monitoring Agent
laptop
Local Analytics

Keep your data 100% local.

or
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Cloud Analytics

Access from anywhere securely.

Same insights. Wherever you run. turn_slight_right
PERFORMANCE INSIGHTS

Know which models actually perform best on your hardware.

Compare models, track inference performance, and make data-driven decisions for your local pipelines.

Model Tokens / sec Latency Total Tokens Requests Throughput
Qwen3.8 27B 31.8 1.4s 18.4K 428
DeepSeek R1 32B 21.3 2.8s 24.1K 312
GLM 5 Flash 38.7 1.1s 12.8K 521
Llama 3.2 3B 28.4 1.9s 8.4K 274
Mistral 7B 26.1 2.4s 14.2K 308
Request Volume
1,428
Token Usage
284K
Latency (avg)
2.31s
Model Usage
■ Qwen 27%
■ DeepSeek 22%
■ GLM 19%
BUILT FOR DEVELOPERS

Stop reading endless terminal logs.

Transform noisy text streams into structured, actionable JSON-native insights.

Raw Ollama Logs
22:14:32 INFO request started model=qwen3.8:27b
22:14:34 INFO prompt_eval_count=428
22:14:35 INFO eval_count=1842
22:14:35 INFO request completed duration=2.84s
22:14:37 INFO request started model=deepseek-r1:32b
...
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Structured Event Completed
Model qwen3.8:27b
Endpoint /api/chat
Prompt Tokens 428
Generated Tokens 1,842
Duration 2.84 sec
Generation Speed 23.4 tok/s
$ ollama-monitor start
check Ollama detected
check Connected to localhost:11434
check Monitoring started
Watching Ollama requests...
Start Monitoring arrow_forward Get up and running in seconds. No cloud account required.

Your local AI shouldn't be a black box.

See every request, every model, and every performance metric in high fidelity.

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