DeepSeek-V4 Flash
Cheap, fast open MoE — near-frontier value at a fraction of Pro's cost and size.
- Context window
- 1Mtokens
- Max output
- 384Ktokens
- Input price
- $0.14/ 1M tokens
- Output price
- $0.28/ 1M tokens
- Cached input
- $0.01/ 1M tokens
- Modalities
- Text, Image
- Knowledge cutoff
- Jan 2026
- Released
- Apr 2026
- Parameters
- 284B
- License
- MIT
- Approx. speed
- —
What this model is
DeepSeek-V4 Flash is the lightweight sibling of V4 Pro (284B-parameter MoE, 13B active, MIT), built for high-volume, latency-sensitive work. It keeps the V4 generation's 1M-token context, native image input, and DeepSeek Sparse Attention while cutting price to roughly a third of Pro's and running noticeably faster. It is one of the cheapest capable multimodal long-context models available, ideal as a router target for the bulk of everyday traffic, stepping up to Pro or a frontier model only for the hardest jobs.
Strengths
- Extremely cheap — among the lowest prices anywhere
- Fast, low-latency decoding for high-volume work
- 1M-token context and native image input
- MIT open weights, self-hostable
Trade-offs
- Well below the frontier on hard reasoning and coding
- Not for long-horizon autonomous agentic work
- Vision quality is basic
- Smaller active-parameter budget caps peak quality
Best for
- High-volume classification, extraction, and routing
- Cheap long-context document processing
- Low-latency chat and simple coding
- Batch multimodal (image + text) workloads
Not ideal for
- Complex autonomous coding
- Deep multi-step frontier reasoning
Capability profile
Normalized 0–100 scores, comparable across the whole catalog.
- Reasoning
- 74
- Coding
- 62
- Math
- 82
- Writing
- 74
- Knowledge
- 76
- Speed
- 82
- Agentic
- 58
- Vision
- 58
- Multilingual
- 78
- Long Context
- 84
How it scores
Public benchmark results, with independent third-party results where available. Bars normalize percentages to 100 and Elo ratings to a 1500 ceiling.