DeepSeek V — the open model line at a glance
Where things stand
As of September 2026, DeepSeek V4-Pro is the flagship of the line, with the cheaper V4-Flash variant alongside it. This article covers the line as a whole — prices, context windows and benchmark figures for individual versions live in the linked glossary entries.
What DeepSeek V is and what the line stands for
DeepSeek runs two lines in parallel: V is the general all-purpose line for chat, coding and agents, R the separate line specialised in reasoning (such as R1) for maths and competition-style tasks. Since V3.1 and V3.2, reasoning capabilities increasingly move into the V line as a hybrid mode — the hard split between “all-purpose” and “thinking model” softens without V losing its breadth.
The second point up front, because it shapes the decision: DeepSeek V is open — with nuances. V3.2, V4, V4-Flash and V4-Pro are fully MIT-licensed. For V3 and V3.1 the code is MIT-licensed, while the model weights themselves sit under DeepSeek’s own but commercially usable licence. In practice: self-hosting is possible across the whole line, and you’re best off checking the exact licence terms per version.
The line’s strength profile
- Coding 4.5 / 5 · Claude Opus 5 u. a.
- Reasoning 4.5 / 5 · Claude Opus 5 u. a.
- Text 4 / 5 · Claude Fable 5.1
- Vision 3.5 / 5 · Gemini 3.1 Pro
- Speed 3.5 / 5 · Claude Haiku 4.5 u. a.
- Kosten-Eff. 4.5 / 5 · GPT Luna u. a.
Eignung 0–5 · redaktionelle Einordnung, kein Benchmark · gestrichelt = Feld-Bestwert je Achse
The flagship scores mainly on the ratio of performance to cost: solid coding and reasoning at very good cost efficiency. The axes are an editorial assessment, not a benchmark — they show the balance, but don’t replace a test on your own use case.
Where DeepSeek V sits in the field
Redaktionelle Einordnung, kein Benchmark
Next to the other big open lines — Kimi, GLM and Qwen — DeepSeek V lands in the strong all-rounder to frontier-adjacent band, with a clear pull to the right: high cost efficiency is the line’s hallmark. DeepSeek stands out here through especially large MoE capacity and early-integrated sparse attention for long contexts.
Use profile — open and cheap, built for volume
DeepSeek V plays to its strength where cost and openness matter:
- High-volume workloads on a tight budget — classification, summarisation, batch processing.
- Self-hosting on your own or third-party infrastructure when data can’t leave the building. The weights sit on Hugging Face.
- Agentic coding workflows and long contexts, thanks to sparse attention.
If you run reasoning-heavy special tasks, also check the R line; for broad all-purpose use, V is the right address. Details on running open models are under Running local LLMs.
Which DeepSeek V version fits
For most cases the current flagship DeepSeek V4-Pro is the right pick; for cost-sensitive workloads the cheaper V4-Flash variant. If you need stability and broad tool support, V3 remains a solid base:
- DeepSeek V4-Pro — current flagship (August 2026).
- DeepSeek V4-Flash — cheaper, faster variant.
- DeepSeek V4, V3.2, V3.1 and V3 — earlier generations.
Related terms
- AI model families at a glance — where DeepSeek sits next to the Western frontier lines.
- Running local LLMs — self-hosting options for open models.
- The Hugging Face ecosystem — where the weights live.
FAQ
- V is the general all-purpose line for chat, coding and agents. R is the separate line specialised in reasoning (such as R1) for maths and competition-style tasks. Since V3.1/V3.2, reasoning capabilities increasingly move into the V line as a hybrid mode.
- Yes, but with nuances: V3.2, V4, V4-Flash and V4-Pro are fully MIT-licensed. V3 and V3.1 have MIT-licensed code, while the model weights themselves sit under DeepSeek's own but commercially usable licence.
- For most cases the current flagship DeepSeek V4-Pro, or the cheaper V4-Flash variant, is the right pick. If you need stability and broad tool support, V3 remains a solid base.
- All four follow the same core principle — open weights, aggressive pricing. DeepSeek V stands out through especially large MoE capacity and early-integrated sparse attention for long contexts; the exact positioning shifts with each release cycle.
- This hub covers the line as a whole. Details on prices, context window or benchmark figures for individual versions live in the linked glossary entries, currently above all DeepSeek V4-Pro and DeepSeek V4-Flash.