DeepSeek V4.1 Flash 1017.
Minor update to DeepSeek-V4.1-Flash with improved reasoning, coding, agent and vision results and shorter outputs, open weights under the MIT licence.
8× Nvidia A100 SXM4 · $5.73/hr.
Most-aggressive quantisation we have a working recommendation for. Lower precision = less VRAM = cheaper hardware, at a small accuracy cost.
Cheapest hosted endpoints.
Variants in the DeepSeek family.
DeepSeek's flagship MoE — 671B total, 37B active, frontier-class.
DeepSeek's reasoning model — RL-trained, frontier-class, MIT-licensed.
70B Llama distilled from DeepSeek R1's reasoning traces.
32B Qwen base distilled from DeepSeek R1.
14B distilled R1 — laptop-friendly reasoning.
7B distilled R1 — runs on any modern GPU.
Tiny distilled R1 — phone / browser deployable.
Official release of DeepSeek-V4-Pro that supersedes the preview, adding a spe...
DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, wi...
DeepSeek-V3.1 is post-trained on the top of DeepSeek-V3.1-Base, which is buil...
DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iterat...
DeepSeek-V3.1 Terminus is an update to [DeepSeek V3.1](/deepseek/deepseek-cha...
DeepSeek-V3.2 is a large language model designed to harmonize high computatio...
DeepSeek-V3.2-Speciale is a high-compute variant of DeepSeek-V3.2 optimized f...
Open-weights 284B Mixture-of-Experts text model with 13B active parameters an...
Open-weights 1.6T Mixture-of-Experts text model with 49B active parameters an...
May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) Performa...
Open-weights multimodal 552B Mixture-of-Experts model that reads images and t...
DeepSeek-V4-Flash-Vision-Exp is an experimental MIT-licensed model adding ima...
DeepSeek-V3.2-Exp is an experimental large language model released by DeepSee...
Cheapest hardware per quantisation.
Each row is one quantisation tier (the same weights compressed differently). Lower precision → lower VRAM → cheaper hardware, at the cost of small accuracy loss. $/Std. ist der günstigste aktuelle Preis. Ein Setup mit mehreren Karten nutzt eine echte Instanz dieser Größe, wenn eine vermietet wird; sonst ist es der Einzelkartenpreis mal Anzahl.
| Quantisation | Cheapest GPU config | Total VRAM | Live $/hr | tokens/sec | |
|---|---|---|---|---|---|
|
FP16
FP16 — half precision (default)
|
2048 GB |
$24.57/hr
Cyfuture AI · On-Demand
|
— | Compare → | |
|
FP8
FP8 — 8-bit float (Hopper / Blackwell)
|
1024 GB |
$12.41/hr
Cyfuture AI · On-Demand
|
— | Compare → | |
|
INT4
INT4 — 4-bit integer (~4× VRAM saving)
|
640 GB |
$5.73/hr
geschätzt 8 × Einzelkartenpreis
Nosana · On-Demand
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— | Compare → |
What it costs per month across providers.
Estimate your monthly bill for DeepSeek V4.1 Flash 1017 across every host that publishes per-token pricing. Slide your token volumes; the chart + table re-rank cheapest-first.
Günstigster Anbieter links.
Gesamte Monatskosten — Eingabe- und Ausgabe-Tokens zusammen.
Rechnung im Detail.
| Anbieter | Monatssumme | |
|---|---|---|
| $2.7 | Registrieren ↗ | |
| $3.2 | Registrieren ↗ | |
| $5.4 | Registrieren ↗ |
GPU mieten statt pro Token zahlen.
Bei einem Open-Weights-Modell wie DeepSeek V4.1 Flash 1017 kannst du eine GPU mieten und die Inferenz selbst betreiben. Die Rechnung: günstigste GPU-Miete × 730 Stunden/Monat. Strom ist im Stundenpreis der Miete enthalten.
Angenommen wird, dass die GPU rund um die Uhr mit ca. 85 % Auslastung läuft. Bei schwankendem Traffic zahlst du für die API weniger und für die GPU wahrscheinlich mehr (Leerlaufstunden kosten trotzdem Miete). Die Break-even-Analyse findest du im Break-even-Tool Selbsthosting vs. API.
About DeepSeek V4.1 Flash 1017.
A minor update to DeepSeek-V4.1-Flash, the same multimodal model that reads images and text and writes text, with weights under the MIT licence and a one million token context. DeepSeek says the update improves reasoning, coding, agent tasks and visual understanding, and also shortens task execution time and output length. It keeps the base model's architecture and download format, so existing serving setups for V4.1-Flash apply.