DeepSeek V4 Flash runs with one million tokens in llama.cpp
A user has demonstrated DeepSeek V4 Flash with a context length of one million tokens using llama.cpp on consumer hardware, indicating progress in local LLM inference.
What happened?
DeepSeek V4 Flash has been demonstrated running with a context length of one million tokens. This was achieved using llama.cpp on an Nvidia RTX 5090 graphics card, according to a post on Reddit. This demonstration showcases technical progress for large language models on consumer-grade hardware.
Key facts
| Modell | DeepSeek V4 Flash |
|---|---|
| Kontextlängd | 1 miljon tokens |
| Ramverk | llama.cpp |
| Hårdvara | Nvidia RTX 5090 |
”DeepSeek v4 Flash on 5090 in llama.cpp with 1 Million context”
Why it matters
The ability to handle a million-token context locally is significant. It facilitates the development of applications requiring extensive text analysis and processing without relying on cloud services. This lowers the barrier for local implementation of advanced AI models.
Who is affected?
Developers and researchers working with large language models (LLMs) for local inference are directly affected. Companies wishing to run AI models internally can also benefit from this type of progress. End users of applications based on locally run LLMs will indirectly see improvements in performance and functionality.
What else you should know
The demonstration used an Nvidia RTX 5090 graphics card, which has not yet been released to the consumer market. This provides an early indication of what future hardware can achieve.
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