DeepSeek V4.1 Flash — VRAM, szybkość i lokalna konfiguracja
Autor: Jakub Rusinowski · Ostatnia aktualizacja:
A 552B-backbone Mixture-of-Experts with a causal encoder-decoder: 8B parameters active per input token, 16B per output token, plus a 196B-parameter Engram memory table and native image input. 1M-token context, MIT licence. The released checkpoint is about 510 GB and DeepSeek's reference code serves it across eight GPUs; mainline local runtimes do not load it yet. Revision 2026-10-17: DeepSeek published DeepSeek-V4.1-Flash-1017, a minor update of these weights (same 763B-parameter checkpoint, 510 GB, MIT, 1M context) that improves reasoning, coding, agentic and visual benchmarks and shortens outputs; every memory figure on this page applies to both.
DeepSeek V4.1 Flash potrzebuje około 462 GB VRAM przy Q4_K_M — skwantyzowane wagi plus narzut frameworka, bez pamięci podręcznej KV. Na Apple Silicon ta wartość pochodzi z pamięci zunifikowanej.
VRAM i szybkość według kwantyzacji
Liczone dla NVIDIA RTX 4090 (24 GB). Tylko wagi i narzut: architektura tego modelu nie jest opublikowana, więc nie doliczamy pamięci KV.
| Kwant. | Pamięć | VRAM | Szybkość (szac.) | Dopasowanie |
|---|---|---|---|---|
| Q2_K 2.63 bpw | 251.7 GB | — | Za duży | |
| Q3_K_M 3.41 bpw | 326.1 GB | — | Za duży | |
| Q4_K_M 4.83 bpw | 461.6 GB | — | Za duży | |
| Q5_K_M 5.67 bpw | 541.7 GB | — | Za duży | |
| Q6_K 6.56 bpw | 626.6 GB | — | Za duży | |
| Q8_0 8.50 bpw | 811.7 GB | — | Za duży | |
| F16 16.00 bpw | 1527.2 GB | — | Za duży |
Czarny znacznik = dostępna pamięć na NVIDIA RTX 4090 (24 GB). Szacunki z modelu przepustowości pamięci opisanego na stronie metodologii. Kalkulator VRAM dla DeepSeek V4.1 Flash →
Uruchom DeepSeek V4.1 Flash
DeepSeek V4.1 Flash is not practical on a single consumer GPU: it needs about 461.6 GB at Q4_K_M, more than any single device in our catalogue holds with headroom. How multi-GPU inference works, or rent a multi-GPU server by the hour:
Jako partner Amazon zarabiamy na kwalifikujących się zakupach. Linki do chmurowych GPU są linkami polecającymi — możemy otrzymać prowizję bez dodatkowych kosztów dla Ciebie.
Jak uruchomić DeepSeek V4.1 Flash
No local Ollama tag. Ollama lists deepseek-v4.1-flash only as a cloud-hosted ':cloud' tag, which runs on Ollama's servers, not your machine.
Specyfikacja
Verified — Checked against the primary source — the model card or the vendor spec page — and corroborated by a second independent source.
- Parametry
- 552 Billion backbone (16B active) + 196B Engram memory
- Active parameters
- 16B per output token (decode) · 8B per input token (prefill)
- Okno kontekstu
- 1,000,000
- Architektura
- Mixture-of-Experts, causal encoder-decoder (20 + 20 layers), 384 routed experts + 1 shared, 6 active; vision encoder
- Dostawca
- DeepSeek
- Licencja
- MIT
- Availability
- Weights downloadable
- Practical deployment
- Multi-GPU server
- Określono przy
- Q4_K_M
- RAM systemowy
- 512 GB
- Rekord zaktualizowany
- 2026-11-11
Commercial use permitted. No usage restrictions beyond attribution.
Ograniczenia i zastrzeżenia
- The memory figure includes the 196B-parameter Engram table, which DeepSeek's released inference code keeps in GPU memory. A runtime that served Engram from system RAM would need much less GPU memory; none does yet.
- The KV-cache figure is an estimate: the model's compressed sparse attention (890 bytes per token, per the model card) is not modelled exactly here, so the cache is over-stated, which is negligible next to the weights.
Jakość i zastosowania
Wyniki opublikowane przez autorów modelu lub niezależnego oceniającego — jakość, nie przepustowość, i nie mierzone przez nas.
Independent evaluation — not vendor-claimed and not measured by us
| Benchmark | Wynik | Źródło |
|---|---|---|
| AA Intelligence Index v4.3.2 (Max) | 39 | independent · Artificial Analysis · snapshot 2026-10-13 |
Czy uruchomię DeepSeek V4.1 Flash na moim GPU?
- DeepSeek V4.1 Flash na AMD Ryzen AI Max+ 395
- DeepSeek V4.1 Flash na Apple M1 Ultra
- DeepSeek V4.1 Flash na Apple M2 Max
- DeepSeek V4.1 Flash na Apple M2 Ultra
- DeepSeek V4.1 Flash na Apple M4 Max
- DeepSeek V4.1 Flash na Apple M5 Max
- DeepSeek V4.1 Flash na NVIDIA A100 80GB (PCIe)
- DeepSeek V4.1 Flash na NVIDIA DGX Spark
- DeepSeek V4.1 Flash na NVIDIA H100 80GB (PCIe)
- DeepSeek V4.1 Flash na NVIDIA RTX PRO 6000 Blackwell
DeepSeek V4.1 Flash — najczęściej zadawane pytania
How much VRAM does DeepSeek V4.1 Flash need?
About 462 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.
Does DeepSeek V4.1 Flash run on an RTX 4090 (24 GB)?
No. DeepSeek V4.1 Flash needs about 462 GB at Q4_K_M, more than a single RTX 4090's 24 GB. It needs a larger card, several GPUs, or Apple Silicon with enough unified memory — or it runs with part of the weights offloaded to system RAM, which is much slower.
How do I run DeepSeek V4.1 Flash locally?
No local Ollama tag. Ollama lists deepseek-v4.1-flash only as a cloud-hosted ':cloud' tag, which runs on Ollama's servers, not your machine. Running the published tag would send your prompts to a hosted GPU rather than your own machine.
What other sizes does DeepSeek V4.1 come in?
DeepSeek V4.1 Flash (462 GB), DeepSeek V4.1 (967 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.