Release Date: Apr 23, 2026

Developer DeepSeek 🇨🇳
Context Window 1M
Max Output Tokens 384k
Token Costs (in/out) $1.32/3.96
Weights Open
Input Modalities

Accuracy

42.89 % ± 1.19

Cost / Test (Vals Index)

$ 0.898

Latency

23 min 47 s

Vals Index
BenchmarksAccuracyRankings

0.0%

±1.19
33/55

0.0%

±4.04
28/57

0.0%

±5.84
14/24

0.0%

±3.05
36/55

0.0%

±0.65
38/58

0.0%

±2.93
36/58

0.0%

±2.12
51/90

0.0%

±2.00
66/92

0.0%

±3.67
24/29

0.0%

±0.88
69/145

0.0%

±4.77
38/93

0.0%

±1.65
30/138

0.0%

±7.14
15/62

0.0%

±0.95
14/143

0.0%

±0.47
82/142

0.0%

±0.34
32/138

0.0%

±0.00
36/45

0.0%

±4.60
20/33

0.0%

±1.87
36/88

0.0%

±1.50
51/63
Proprietary BenchmarksAcademic BenchmarksIndustry Partners
Vals
Default Provider : DeepSeek
Temperature: 1
Top P: Default
Top K: Default
Max Output Tokens: 384,000
Reasoning Effort: max

Updates

Apr 24, 2026

DeepSeek is back — DeepSeek V4 just landed #2 open-weight on the Vals Index, narrowly trailing Kimi K2.6 by 0.07%. All rankings below are among open-weight models.

The model has a 1M-token context window, and was run with temp=1, top_p = 0.95, 256k max output tokens, and max reasoning effort via the DeepSeek native API.