Model

DeepSeek-V4 Flash NO.29

Cheap, fast open MoE — near-frontier value at a fraction of Pro's cost and size.

DeepSeek · DeepSeek · Fast · Open weights

Specification

Fig.01DeepSeek — DeepSeek

CHINA

Context window
1Mtokens
Max output
384Ktokens
Input price
$0.14/ 1M
Output price
$0.28/ 1M
Cached input
$0.01/ 1M
Throughput
Class
Fast
Modalities
Text, Image
Weights
Open
Parameters
284B
License
MIT
Knowledge cutoff
Jan 2026
Released
Apr 2026

Overview

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

Fit

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

Capabilities

Ten axes, normalized 0–100 and scored the same way across the whole catalog — so a 78 here means what a 78 means anywhere else on the bench.

Fig.02Capability radar

0 — 100

Reasoning
74
Coding
62
Math
82
Writing
74
Knowledge
76
Speed
82
Agentic
58
Vision
58
Multilingual
78
Long Context
84

Benchmarks

Public results, with independent third-party runs marked. Bars normalize percentages against 100 and Elo ratings against a 1500 ceiling.

Independent index

Artificial Analysis Intelligence Index

Composite of ~9–10 independent evals · Artificial Analysis

40/ 100

BenchmarkResult
Artificial Analysis Intelligence IndexIndependentGeneral · Artificial Analysis
40%
SWE-bench VerifiedIndependentCoding · SWE-bench
66%
SWE-bench ProIndependentCoding · SWE-bench Pro
38%
GPQA DiamondIndependentReasoning · Independent aggregators
74%
AIME 2025Math · Vendor-reported
85%
LiveCodeBenchIndependentCoding · LiveCodeBench
66%

Alternatives

Models in roughly the same class — the ones worth weighing against this record.

Index

All models/EDUCATION