Augure vs Ollama: self-host open models or Canadian hosting

Ollama is open-source software that downloads open-weight models and runs them on your own Mac, Windows or Linux machine, with an OpenAI-compatible local API. Augure is a Canadian AI platform that hosts models for you: its own Ossington, Rosedale and Tofino tiers plus two open-weight models under Augure Open, all behind an OpenAI-compatible API, with customer data stored in Canada. The biggest difference is who runs the hardware. With Ollama nothing leaves your machine, and you own the capacity, the upgrades and the on-call. With Augure you get larger models, long context, document reading and a finished chat product, under Canadian jurisdiction. Read this if you are a Canadian developer or IT lead choosing between the two, or planning to use both.

At a glance

	Augure	Ollama (self-hosted)
Company and jurisdiction	Canadian company, no US parent or investors.	MIT-licensed software from Ollama Inc. The software runs wherever you install it; Ollama's privacy policy says account data may be processed in the United States.
Where customer data is stored	Canada.	On your own hardware. "Ollama runs locally. We don't see your prompts or data when you run locally," per its docs.
Where inference runs	Canadian infrastructure (Ontario) and vetted EU partners under zero-data-retention; never US providers.	Your CPU or GPU. Optional Ollama Cloud models are hosted "primarily in the United States" with routing to Europe for capacity, per the pricing page.
Your data used for training	Never.	Local: nothing is sent. Ollama Cloud: "Prompt or response data is never logged or trained on," per the pricing page.
Canadian residency option	Storage always in Canada. Accounts can be set Canada-only: requests then stay in Canada or fail with 503 residency_unavailable, never served elsewhere. tofino-3 and the Augure Open models never leave Canada.	Inherent when you run on premises in Canada. Ollama Cloud publishes no Canadian region as of October 2026.
API	OpenAI-compatible, https://api.augureai.ca/v1	OpenAI-compatible, http://localhost:11434/v1, API key "required but ignored."
Models	ossington-5 (256K), rosedale-1 (up to 1M), tofino-3, Augure Open (GLM-5.3, Qwen3.8-Flash-Next, text only, Canada only)	Any model in the Ollama library: Llama 3.1 (8B to 405B), DeepSeek-R1 (1.5B to 671B), Qwen3 (0.6B to 235B), Gemma, Mistral and more, each under its own licence.
Context window	256K on every model; rosedale-1 up to 1M.	4,096 tokens by default, raised with num_ctx or OLLAMA_CONTEXT_LENGTH, limited by your memory.
Images and PDFs	Images on any model via auto; PDFs as file parts, up to 25 MB and 200 pages.	Base64 images on vision models; PDF input is not listed in its OpenAI-compatible docs.
Hardware	None.	Roughly 6 to 7 GB VRAM for a 7B to 8B model and 47 to 52 GB for a 70B model at 4-bit, per a third-party guide; CPU-only works but is slower.
Languages	English and Quebec French natively.	Model-dependent.
Price and currency	Per token in CAD: tofino-3 $0.60/$2.00, ossington-5 $1.50/$3.00, GLM-5.3 $3.00/$7.00, Qwen3.8-Flash-Next $2.00/$4.00 per million.	Software is free. Ollama Cloud: pay as you go, Pro $20/mo, Max $100/mo, Team $500/mo (currency not named on the page).
Best fit	Teams that want hosted models, long context and a chat product under Canadian jurisdiction without running GPUs.	Teams with hardware and ops capacity whose data must never leave the premises, or who need offline use.

Where Ollama wins

• Residency without a contract. Prompts and answers stay on the machine that runs the model. Ollama binds to 127.0.0.1 by default, and cloud features can be switched off with OLLAMA_NO_CLOUD=1. No provider, Canadian or otherwise, is in the loop.
• Licence cost is zero. Ollama is MIT-licensed, and the library has models released under Apache 2.0 and MIT terms. Your only costs are hardware, power and people.
• Model choice and control. You pick the exact model and size, pin the version, and nothing changes under you. Augure Open serves two open models and marks them preview with no SLA.
• Offline and air-gapped use. A laptop or a server with no internet connection still answers.
• Breadth of the local API. Ollama's OpenAI layer covers chat, completions, embeddings, speech and transcription endpoints as of its current docs; Augure's API is chat completions, search, link reading and memories.

Where Augure wins

• Model size without hardware. ossington-5 and rosedale-1 are hosted reasoning tiers with 256K context, and rosedale-1 accepts up to 1M tokens. Ollama's default context is 4,096 tokens and larger models need tens of gigabytes of VRAM.
• Canadian jurisdiction for a hosted service. Customer data is stored in Canada. Customer conversations, documents and AI inference are never handled by US-jurisdiction providers, so the CLOUD Act's reach over US-controlled providers does not extend to customer content. Limited US processing exists for payment card networks and email delivery only, documented in the privacy policy.
• Hosted open weights in Canada. Augure Open serves GLM-5.3 and Qwen3.8-Flash-Next under their published names, hosted in Canada, with no gateway-added system prompt, and returns 503 or 429 rather than failing over when Canadian capacity is full.
• Documents, tools and agents. PDFs are read on the gateway with OCR fallback, images route to a vision engine in Canada, and rosedale-1 is positioned for tool calling and agent loops.
• A finished product. Augure Chat, the desktop app, Knowledge and Oshan run on the same models, in English and Quebec French, from C$0 to C$80 per month.

Switch from Ollama to Augure

Both expose the OpenAI chat completions shape, so most code moves with three changes. You can keep Ollama for local experiments and send heavier jobs to Augure from the same client.

1. Create a key at https://augureai.ca/developers (aug_sk_live_...).
2. Change the base URL from http://localhost:11434/v1 to https://api.augureai.ca/v1 and replace the placeholder key with your Augure key. Ollama ignores the key; Augure requires it.
3. Map model names.

Ollama model	Augure model	Why
qwen3:*	open-qwen-3.8-flash-next	Same family, open weights, hosted in Canada, reasoning_effort passed through unchanged.
GLM models	open-glm-5-3	Open weights, hosted in Canada, 49,152 output cap, thinks before every answer.
llama3.1:8b, gemma4:12b, mistral	tofino-3	Fast everyday tier, thinking off, served in Canada with no failover outside Canada.
deepseek-r1:*	ossington-5	Reasoning tier with reasoning_content returned separately.
llama3.1:70b and larger	rosedale-1	Premium reasoning on Canadian inference, up to 1M context.
Vision models with images	auto with image_url parts	Images route to Augure's vision engine in Canada.

4. Before and after in Python:

import os
from openai import OpenAI

# Before: Ollama on your machine
client = OpenAI(base_url="http://localhost:11434/v1", api_key="ollama")  # key required but ignored
resp = client.chat.completions.create(
    model="qwen3:8b",
    messages=[{"role": "user", "content": "Summarise this contract in two lines."}],
)
print(resp.choices[0].message.content)

# After: Augure, hosted in Canada
client = OpenAI(base_url="https://api.augureai.ca/v1", api_key=os.environ["AUGURE_API_KEY"])
resp = client.chat.completions.create(
    model="open-qwen-3.8-flash-next",
    messages=[{"role": "user", "content": "Summarise this contract in two lines."}],
)
print(resp.choices[0].message.content)
print(resp.model_extra["_augure"]["inference_region"])

5. Re-check:
   • Context: drop any num_ctx workaround. Every Augure model accepts 256K tokens; rosedale-1 up to 1M.
   • max_tokens: omit it on reasoning models, and on the Augure Open models omit it or set at least 1,024, or you can get reasoning_cutoff. Caps are 32,768 (tofino-3: 16,384; GLM-5.3: 49,152).
   • tool_choice and n: Ollama's docs list them as unsupported; Augure accepts tool_choice, and Qwen3.8-Flash-Next takes n: 1 only.
   • Images: both take base64 data URLs. Augure Open models are text only and return 400 unsupported_content for image or file parts; use auto or another tier.
   • response_format: on Augure Open it goes to the model's own structured decoding, so validate the JSON.
   • Rate limits and spend: 60 requests per minute and 20 in flight per key by default, with a daily spend cap of CAD 100 (CAD 25 until your first successful charge).
   • Residency: Augure Open and tofino-3 return 503 or 429 when Canadian capacity is full instead of failing over, so retry with backoff.
6. Run both for a week on the same prompts, compare quality and latency, then cut over the workloads that need the larger models.

Keep Ollama if

• Your policy is that prompts never leave the premises, or the environment is air-gapped.
• You already own the GPUs and the people to run them, and the small-to-mid models meet your quality bar.
• You need a specific open model, quantisation or fine-tune that Augure does not serve.
• You are prototyping and a local 8B model is enough.

Sources

• https://github.com/ollama/ollama/blob/main/LICENSE (checked 2026-10-27): MIT License.
• https://github.com/ollama/ollama (checked 2026-10-27): macOS, Windows, Linux and Docker; model families supported.
• https://docs.ollama.com/openai (checked 2026-10-27): base URL http://localhost:11434/v1, key "required but ignored", supported endpoints and features, unsupported tool_choice, n, logit_bias; images base64 only; cloud base URL https://ollama.com/v1.
• https://docs.ollama.com/faq (checked 2026-10-27): "Ollama runs locally. We don't see your prompts or data when you run locally"; binds 127.0.0.1:11434; default context 4,096 tokens; OLLAMA_NO_CLOUD=1.
• https://ollama.com/library (checked 2026-10-27): model families and parameter sizes; Apache 2.0 and MIT licences on some models.
• https://docs.ollama.com/gpu (checked 2026-10-27): NVIDIA compute capability 5.0+, AMD ROCm v7, Apple Metal, Vulkan.
• https://hostinger.com/tutorials/ollama-gpu-requirements/ (checked 2026-10-27, updated 23 October 2026): third-party VRAM guidance per model size at Q4; CPU-only operation.
• https://ollama.com/pricing (checked 2026-10-27): Ollama Cloud plans; hosted "primarily in the United States" with routing to Europe; never logged or trained on.
• https://ollama.com/privacy (checked 2026-10-27): Ollama Inc. as controller; data may be transferred to and processed in the United States; no training on inputs or outputs; last updated March 2026.
• https://docs.ollama.com/cloud (checked 2026-10-27): cloud models and model naming; no training.
• https://augureai.ca/docs/api (checked 2026-10-27): Augure base URL, residency, limits, images and PDFs, tool use.
• https://augureai.ca/docs/models (checked 2026-10-27): Augure Open conditions, model ids, caps and CAD prices.
• https://augureai.ca/llms.txt (checked 2026-10-27): company, storage, inference, ownership, plans and languages.