What DeepSeek V3.1 is
DeepSeek V3.1 (V3.1-Terminus) is a large hybrid model from DeepSeek for reasoning, coding, search-agent workflows, and tool-assisted tasks. One model supports both thinking and non-thinking modes by changing the chat template — useful when teams want direct answers for routine work and deeper reasoning for difficult analysis. Ollama lists 160K context, text input, tool support, and thinking support on the cloud tag.
On Ollama today, the Terminal Glass cloud tag is
deepseek-v3.1:671b-cloud (high usage tier).
A local deepseek-v3.1:671b build is also
available (~404 GB) for teams with the infrastructure to host it on
NoCloudGPT Private Instances.
Deploy cloud access with clear rules about what documents and code 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 multi-GPU servers sized for a 671B-class model to start evaluating hybrid reasoning and agent workflows.
Honest reality: Prompts, code snippets, RAG passages, tool outputs, and conversation context 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. DeepSeek V3.1 cloud is rated high usage on Ollama — expect higher per-token cost than smaller models, especially with long 160K contexts and thinking-enabled prompts. You also accept network-dependent latency and less control over strict reproducibility. When sensitive or regulated material must never leave your network, choose a NoCloudGPT Air Gapped deployment instead.
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 technical users who want help with complex questions, code explanation, research planning, or long-document synthesis without building a local high-end inference box. Every prompt and any documents you include are sent to Ollama Cloud — avoid private journals, financial records, credentials, or sensitive personal documents. Choose NoCloudGPT Private Instances if keeping data fully private is your priority.
🏢 Business / Team Use
A strong fit for teams evaluating advanced assistants for internal documentation, policy Q&A, technical support, code review preparation, and structured research when your data policy permits cloud processing. Use NoCloudGPT Private Instances for regulated data, confidential client material, or source code that must remain inside your environment.
⚙️ Developer & Technical Use
Well suited for tool-calling prototypes, search agents, code agents, debugging workflows, architecture review, and longer technical prompts. Thinking mode can help with difficult analysis; non-thinking mode is better when you want direct answers and lower response overhead. Credentials, private keys, and proprietary algorithms leave your environment during inference unless cloud use has been approved.
🔬 Data Science & Research Use
Practical for public datasets, literature review, reasoning-heavy analysis, benchmark exploration, and multilingual research. 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
deepseek-v3.1:671b-cloud,
the request — including code excerpts 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. DeepSeek V3.1 is rated high usage on Ollama — budget accordingly for
long 160K contexts, thinking-mode prompts, and agentic tool loops.
ollama signin
ollama run deepseek-v3.1:671b-cloudWhat leaves your infrastructure: prompt text, code snippets, RAG-retrieved passages, and tool context. DeepSeek V3.1 is text-only on Ollama. Latency includes network round-trips. Cost is usage-based at the high-usage tier.
Honest Guidance: When to Choose a Different Path
- Regulated, confidential, or strict data-residency requirements — Choose NoCloudGPT Private Instances with a local DeepSeek deployment. Terminal Glass routes prompts and code to Ollama Cloud.
-
Steady daily team usage on capable hardware —
Local
deepseek-v3.1:671bon owned multi-GPU infrastructure may cost less over time than recurring high-usage cloud tokens. - Routine drafting or tighter budgets — A smaller model may be enough for basic Q&A and support workflows where a 671B-class model is more capacity than the task requires. For a newer DeepSeek cloud option, see DeepSeek V3.2 Cloud.
- Unreviewed agent automation — Search, code, and tool workflows still need permissions, logs, validation, and rollback practices 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 | |
|---|---|---|---|
| deepseek-v3.1:671b-cloud | Teams evaluating hybrid reasoning and agents | 671B-class model, 160K cloud context, text input, thinking and tools, high usage tier. Only verified DeepSeek V3.1 cloud tag on Ollama. Hybrid reasoning, tool use, code agents, search agents, and long technical analysis when content may leave your network. | Get quote → |
Local tag deepseek-v3.1:671b (~404 GB)
is also available on Ollama for fully local deployment when you have the hardware. Confirm availability at
ollama.com/library/deepseek-v3.1
before deployment.
Licensing & Access
DeepSeek V3.1 model weights are released under the MIT license per the Ollama model card — which permits commercial use subject to standard MIT 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/deepseek-v3.1
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.