DeepSeek V4 Pro 0813

DeepSeek V4 Pro 0813 is an open-weight model from DeepSeek, released August 13, 2026. It ranks #27 of 36 models on the Vals Index with 52.97%. Its best result is #27 of 127 on Vibe Code Bench v1.1.

Release Date: Aug 13, 2026

Developer DeepSeek ย ๐Ÿ‡จ๐Ÿ‡ณ
Context Window 1M
Max Output Tokens 384k
Token Costs (in/out) $1.32/3.96
Weights Open
Input Modalities

Accuracy

52.97 % ยฑ 1.04

Cost / Test (Vals Index)

$ 2.500

Latency

58 min 3 s

Vals Index
BenchmarksAccuracyRankings

52.97%

ยฑ1.04
27/36

52.94%

ยฑ1.41
33/39

69.01%

ยฑ1.77
21/37

51.99%

ยฑ2.23
15/30

72.86%

ยฑ5.50
14/48

65.13%

ยฑ2.35
34/41

57.12%

ยฑ2.08
31/39

61.66%

ยฑ1.68
24/26

40.87%

ยฑ3.42
35/93

42.47%

ยฑ2.16
50/107

80.17%

ยฑ2.00
59/109

50.00%

ยฑ5.03
32/53

1.91%

ยฑ0.85
26/37

26.76%

ยฑ3.09
41/84

73.06%

ยฑ0.87
55/145

17.53%

ยฑ3.41
16/26

82.30%

ยฑ3.15
27/127

10.83%

ยฑ2.72
21/37

92.42%

ยฑ2.02
17/138

51.61%

ยฑ2.40
26/46

87.53%

ยฑ0.96
13/143

82.36%

ยฑ0.44
73/151

86.97%

ยฑ0.34
36/138

0.00%

ยฑ0.00
35/66

53.83%

ยฑ4.49
16/35

96.40%

ยฑ0.83
2/88

14.14%

ยฑ2.02
41/63

4.29%

ยฑ2.44
32/45
Proprietary BenchmarksAcademic BenchmarksIndustry Partners
Vals
Default Provider : DeepSeek
Temperature: 1
Top P: Default
Top K: Default
Max Output Tokens: 384,000
Reasoning Effort: max

Compared with

Updates

Aug 12, 2026

We evaluated DeepSeekโ€™s DeepSeek V4 Pro 0813 across our benchmark suite.

  • It ranks #18 on the Vals Index (52.37%), up 9.48 points from DeepSeek V4 (42.89%).

  • Its standout result is SWE-bench Verified, where it places #2 of 82 models (96.40%) and is the highest-scoring open-weight model on the board, ahead of Kimi K3 (93.40%). It is also by far the cheapest model near the top: $0.02 per test, versus $1.29 for Claude Opus 5 at 97.00%.

  • Reasoning and legal results improve sharply over the previous release: 49.00% on ProofBench (up from 10.00%, #45 โ†’ #15) and 40.87% on Legal Research Bench (up from 23.08%, #27 โ†’ #11). It reaches 7.50% on Harveyโ€™s Legal Agent Benchmark with an 88.06% criteria pass rate, #10 of 43.

  • It struggles on terminal-driven coding and Excel tasks: it scores 54.68% across three full trials of Terminal-Bench 2.1 (#33 of 52, 28.89% on hard tasks) and 52.80% on EMB (#24 of 37).

The model has a 1M-token context window and supports up to 384k output tokens and tool calling. Evaluations were run at max reasoning effort; the model does not accept a temperature parameter.

Congrats to the DeepSeek team on the release!