What Devstral Small 2 is
Devstral Small 2 is Mistral's compact agentic coding model for software engineering workflows. It targets tool use, codebase exploration, multi-file editing, test generation, and software engineering agents that need to inspect and modify real projects. Ollama lists text and image input, tool support, and a 256K context window on the cloud tag.
On Ollama today, the Terminal Glass cloud tag is
devstral-small-2:24b-cloud (low usage tier).
A local devstral-small-2:24b build is also
available (~15 GB) with a longer 384K context window on local inference on
NoCloudGPT Private Instances.
Deploy cloud access with clear rules about what repositories and screenshots may leave your network.
The Terminal Glass trade-off
Terminal Glass gives you the same OpenWebUI chat experience and locally stored RAG index you would use on a private deployment — but routes each inference request to Ollama Cloud. Your server runs the Ollama client, OpenWebUI, and your document index; a small cloud VM, NUC, or mini-PC is usually enough. You do not need to size, buy, or maintain hardware for local 24B inference to start evaluating coding-agent workflows.
Honest reality: Prompts, source-code snippets, images, repository context, RAG passages, and tool outputs leave your infrastructure and are processed on Ollama Cloud. This is not air-gapped and is not equivalent to NoCloudGPT Private Instances, where inference stays on hardware you control. You also pay recurring, usage-based Ollama Cloud fees and accept network-dependent latency. When sensitive or regulated material must never leave your network, choose a NoCloudGPT Air Gapped deployment instead.
Source: Wikimedia Commons
What about the video card?
This is the question most buyers are actually trying to answer.
Running these models without a proper GPU usually means falling back to CPU only. This works for very light use, but it becomes extremely slow for normal workloads. Many people discover this the hard way after spinning up a cloud server that ends up being too expensive or too slow.
Some teams want to avoid dealing with GPUs altogether. For them, Terminal Glass Cloud is usually the simpler option — you get capable models through a familiar OpenWebUI interface without having to select, size, or manage video cards.
Other teams prefer to run on infrastructure they control. In that case, they typically choose a GPU-based instance (on AWS Lightsail, Digital Ocean, or their own servers) and install NoCloudGPT on it. Because these models are designed to run with local Ollama, you become responsible for selecting and managing the GPU.
Some organizations need everything to stay fully inside their own environment from day one. For those teams, a NoCloudGPT Air Gapped deployment on their own hardware is the right approach.
There isn’t a single right answer. The right answer depends on your constraints around cost, privacy, compliance, latency, and long-term ownership.
Who This Model Family is For
👤 Personal Use
Useful for solo developers who want help understanding unfamiliar code, planning refactors, writing tests, reviewing errors, or learning a new framework without hosting a 24B model locally. Every prompt and code excerpt you include is sent to Ollama Cloud — do not paste private keys, credentials, client code, or sensitive screenshots. Choose NoCloudGPT Private Instances if keeping data fully private is your priority.
🏢 Business / Team Use
A good fit for teams that want a shared coding assistant for internal tools, developer onboarding, ticket triage, code review preparation, and test planning when your data policy permits cloud processing. Use NoCloudGPT Private Instances when repositories contain confidential IP, regulated data, or customer-specific code.
⚙️ Developer & Technical Use
Strongest for agentic coding workflows: exploring file trees, reading related files, proposing multi-file edits, generating tests, and debugging tool output. It is smaller than full Devstral 2 — validate complex changes with tests and review before merging. Multi-file edits and generated patches still need rollback discipline regardless of model quality.
🔬 Data Science & Research Use
Practical for public-code analysis, notebook cleanup, data-pipeline review, and experiment automation. Cloud inference does not pin model versions the way a local checkpoint does. Confidential, unpublished, or regulated datasets should stay on fully local NoCloudGPT Private Instances.
How Terminal Glass Works with This Model
You interact through OpenWebUI on your Terminal Glass host
(or via the command line). Chat history, user accounts, and your locally built RAG document index
stay on hardware you control. When you submit a prompt to
devstral-small-2:24b-cloud,
the request — including code excerpts, images, and retrieved passages — is forwarded to Ollama Cloud;
the response streams back to your browser.
Cloud access requires an Ollama account (ollama signin)
on the Terminal Glass machine. Devstral Small 2 cloud is rated low usage on Ollama — generally lower
per-request cost than extra-high frontier families, though long 256K contexts and image inputs can
still accumulate spend with heavy agentic use.
ollama signin
ollama run devstral-small-2:24b-cloudWhat leaves your infrastructure: prompt text, code snippets, images, RAG-retrieved passages, and tool context. Latency includes network round-trips. Cost is usage-based.5 text-cyan-200">devstral-small-2:24b on NoCloudGPT Private Instances when private inference becomes the better fit.
Honest Guidance: When to Choose a Different Path
- Regulated, confidential, or strict data-residency requirements — Choose NoCloudGPT Private Instances with a local Devstral build. Terminal Glass routes prompts and code to Ollama Cloud.
-
Steady daily team usage on capable hardware —
Local
devstral-small-2:24bon owned hardware may cost less over time than recurring cloud tokens and removes data-movement risk. - Most demanding software-agent workloads — Full Devstral 2 or another larger coding model may fit better when quality matters more than compact size.
- Unreviewed automation — Multi-file edits, generated patches, and terminal-agent actions need human review, tests, and rollback plans regardless of which model you use.
- Model-version pinning or audit-grade reproducibility — A pinned local deployment on NoCloudGPT Private Instances provides more control than a cloud-only tag.
Recommended Terminal Glass Deployment
| Variant / Tag | Recommended For | Notes | |
|---|---|---|---|
| devstral-small-2:24b-cloud | Individuals and small teams | 24B model, 256K cloud context, text and image input, tools, low usage tier. Only verified Devstral Small 2 cloud tag on Ollama. Codebase exploration, multi-file editing, tool-assisted coding agents, and test generation when content may leave your network. | Get quote → |
Local tag devstral-small-2:24b (~15 GB)
is also available on Ollama with 384K context for fully local deployment. Confirm availability at
ollama.com/library/devstral-small-2
before deployment.
Licensing & Access
Devstral Small 2 is released under the Apache 2.0 license per the Ollama model card — which permits commercial use subject to standard Apache terms. Cloud access requires an Ollama Cloud account with usage-based pricing; rate limits and tiers apply and may change. Ollama Cloud usage is separately governed by Ollama's terms. Review both before production deployment.
Official catalog: ollama.com/library/devstral-small-2
What Terminal Glass adds
Terminal Glass packages a unified OpenWebUI interface, locally stored private RAG over your documentation, multi-user access controls, and guidance on monitoring cloud usage so spend stays predictable.
We help you size the local host and choose the right cloud variant for your team.