Quick Facts
| Developer | Moonshot AI |
| License | Not specified on the Ollama listing -- verify current terms at the official model card before commercial use |
| Size | Not specified -- confirm parameter count at the official Ollama listing |
| Context Window | Not specified -- confirm current context length at the official Ollama listing |
| Cloud Variant | kimi-k2.7-code:cloud |
| Modality | Code and text input; image input supported for multimodal agent workflows |
| Local Hardware | Accessible via cloud tag on Ollama -- confirm whether local weights are available at the official listing |
| Best For | Long-horizon coding, repository understanding, multimodal agent and design-to-code workflows |
Why Choose This Model
Kimi K2.7 Code is built for coding tasks that extend across large amounts of code, documents, and visual context over long, multi-step interactions rather than isolated single-turn prompts. It performs well on repository-scale understanding and multimodal agent workflows where reasoning needs to persist across an extended session. Because it is accessed as a cloud tag on Ollama, Terminal.Glass makes it possible to evaluate its long-horizon coding and agentic capabilities without provisioning frontier-scale local hardware to match.
Terminal.Glass Deployment
Your interface, chat history, and RAG index stay on your Terminal.Glass host. When you submit a
prompt -- including code context and any images -- to
kimi-k2.7-code:cloud, the
request is forwarded to Ollama Cloud, where the model runs, and the response streams back. Cloud
access requires an Ollama account signed in on the Terminal.Glass machine
(ollama signin). Usage is
metered by Ollama Cloud and scales with token volume. No local GPU is required to use the cloud tag.
Recommended Uses
- Long-horizon coding across large codebases
- Repository understanding and multi-file reasoning
- Design-to-code and multimodal agent workflows
- Tool-calling agents for complex, multi-step development tasks
- Code-related research and agentic workflow tooling
Not appropriate for proprietary code, images, or data under strict data-residency requirements -- every prompt, code snippet, image, and retrieved context leaves your infrastructure and is processed on Ollama Cloud. Cloud inference does not provide the same version pinning and reproducibility as a local deployment, which matters for audit-grade or citable research work.
Hardware Guidance
The kimi-k2.7-code:cloud tag
runs entirely on Ollama Cloud, so the Terminal.Glass host only needs to run Open WebUI, the Ollama
client, and your document index -- a small VM, NUC, or office mini-PC is usually sufficient. Confirm
whether a local weight variant exists, along with current parameter count and context window, at
the official Ollama listing
before sizing any local deployment.
Honest Guidance
- Proprietary code, images, or strict data policies: route this to a self-hosted deployment instead -- Terminal Glass's cloud routing sends prompts, code, and images to Ollama Cloud.
- High, predictable volume: owned inference hardware often becomes more economical than sustained cloud usage over time.
- Maximum long-horizon coding or multimodal agent performance: evaluate the latest specialized models when these workloads dominate your use case, since capability rankings shift quickly.
- Model-version pinning or audit-grade reproducibility: a pinned local deployment provides more control than a cloud-only tag that may change behavior without notice.
Learn More
Full technical reference, licensing detail, and local deployment options for this model family are documented on NoCloudGPT. Confirm current tags, parameter count, context window, and availability at ollama.com/library/kimi-k2.7-code.