---
title: "Ollama best practices"
answer: "Ollama identifies models as `name:tag`, and Coolhand treats each tag as a distinct model, so `llama3.1:8b` and `llama3.1:8b-instruct-q4_K_M` report separately. Standardize tags across your team or your cost and quality analytics will fragment across variants of the same underlying model."
category: "Provider guides"
tags: ["ollama","self-hosted","providers"]
published: 2026-08-30T13:57:52Z
updated: 2026-08-30T13:57:52Z
canonical_url: https://coolhandlabs.com/help/ollama-best-practices
index_url: https://coolhandlabs.com/help.md
---

# Ollama best practices

Ollama identifies models as `name:tag`, and Coolhand treats each tag as a distinct model, so `llama3.1:8b` and `llama3.1:8b-instruct-q4_K_M` report separately. Standardize tags across your team or your cost and quality analytics will fragment across variants of the same underlying model.

---

## Model naming

Ollama uses a `name:tag` format (e.g., `llama3.1:8b`, `deepseek-r1:14b`, `qwen2.5:32b`). Different tags for the same base model (e.g., `llama3.1:8b` vs `llama3.1:8b-instruct-q4_K_M`) appear as separate models in Coolhand. Standardize tags across your team to keep analytics meaningful.

---

## Structured outputs

Supported via the `format` parameter. Pass a JSON schema to enforce structured output.

Docs: https://ollama.com/blog/structured-outputs

---

## Caching

Not supported. Cached Input Tokens and Cache Creation Tokens will always be blank.

---

## Batch processing

No batch API. A single Ollama instance handles concurrent requests in parallel via the `OLLAMA_NUM_PARALLEL` environment variable (default: 1). Raise it to process multiple requests simultaneously. Requests beyond the parallel limit are queued server-side up to `OLLAMA_MAX_QUEUE` (default: 512); Ollama returns HTTP 503 only when that queue is full. For higher throughput, increase `OLLAMA_NUM_PARALLEL` or run multiple instances behind a load balancer.

---

## Latency

Reflects your local hardware and network, not a cloud provider's infrastructure. Expect more variability than hosted APIs, especially on consumer GPUs or CPU inference.

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## Reasoning tokens

Not supported. Reasoning Tokens will always be blank for Ollama logs, even for models that perform internal reasoning (e.g., DeepSeek-R1). Thinking content may appear in the **Thinking Response** field, but the token count is not broken out separately.

---

## Cost tracking

Ollama has no per-token pricing — costs are your own compute. Coolhand captures token counts, but there is no dollar-cost mapping for Ollama logs.


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Related:
- [Azure OpenAI best practices](https://coolhandlabs.com/help/azure-openai-best-practices.md)
- [OpenRouter best practices](https://coolhandlabs.com/help/openrouter-best-practices.md)
- [AWS Bedrock best practices](https://coolhandlabs.com/help/aws-bedrock-best-practices.md)
- [Google Gemini best practices](https://coolhandlabs.com/help/google-gemini-best-practices.md)

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