All models

DeepSeekChina· released Jul 2026· open weights

DeepSeek V4 Flash

Ranked #23, 36.3% behind the frontier on average.

DeepSeek, China. One of 4 models from this lab on the Index.

Third-party publishedMedium confidence (7+ comparable tests, 3+ Index categories)
Theo

Available in Theo as Theo Open Flash

Theo orchestrates it for the steps it does best and always shows which engine answered.

Use it in Theo

Snapshot September 8, 2026

OpenCharts Index

63.7

Ranked #23 (20 to 28) of 36 · 36.3% behind the frontier on average · 15 comparable tests · 3 counting categories

Drop any single test and the Index lands between 59.8 and 67.5, anywhere from #20 to #28. Neighbours inside that range are ties.

HARD SET

Needs more results (3 of 8 so far)

Averaging 50.3 on the 3 it has; the score opens at 4 of 8.

Distance to today's frontier on the hardest tests. Not a measure of intelligence.

What it's known for

DeepSeek V4 Flash, in 15 results.

Strongest in reasoning (74.8) and math (59.2). It trails the frontier most in coding, 43.0% behind on average. No comparable results yet in agentic, multimodal and long context. Between 35% and 40% behind the best published results, on average. Drop any single test and it would sit anywhere from #20 to #28.

Strongest category

Reasoning

Hard, novel problems: graduate science, abstract puzzles, expert exams.

74.8

Mean of 5 of the category's 6 comparable tests. Counts toward the Index.

Best single result

Mock AIME 2024–2025

Solve competition mathematics problems that have a single exact integer answer.

94.4%

94.4% of the best (100.0%) · #25 of 78.

Olympiad-style problems need long, careful chains of reasoning, and there is no partial credit.

Where it trails

FrontierMath Tier 4

Solve the hardest FrontierMath tier: problems that take expert mathematicians days.

24.4%

75.0% behind the best published result (97.6%) · #30 of 51.

The deepest end of the set. Progress here signals genuinely new capability.

Not measured yet

No comparable result yet in these 3 categories. A blank is a blank, never a zero, and it does not lower the Index.

  • Agentic
  • Multimodal
  • Long context

Covered, but not averaged into the Index:

  • Knowledgesingle-test category, shown beside the Index · 44.5
  • Human preferencesingle-test category, shown beside the Index · 80.5
Every score, with its source

See it at work

What DeepSeek V4 Flash was asked to do, and how it did.

Every test it has taken, by category, with the kind of task it faced, who produced the number and where the result landed against the best published one. The examples are original and illustrative, never items from the datasets themselves.

Human preference · mean 80.5 across 1 comparable test · a single-test category, shown beside the Index and never averaged into it

Text ArenaLeaderboard

Answer the same prompt as a rival model; real users vote blind on which answer they prefer.

1,438

40% expected win rate against the board leader (1,507)
#59 of 92

high-preview · board 2026-09-02

Source: Arena

Every result is read against the best published one on its test: percent scores as a share of the best above chance, Arena ratings as the expected win rate against the board leader, open-ended values on a log scale. Sitting a harder exam never lowers a model. Every number links to the publisher that produced it.

Head to head

DeepSeek V4 Flash against whoever you pick.

Choose a rival. Every counted test both have taken appears side by side as a share of the best published result on that test, with the category means above. A win is a higher share; a gap under 2 points is a tie, because one item on a 45-problem exam is 2.2 points and publishers' own standard errors are of that order.

DeepSeek V4 Flash

#23·Index 63.7C

0 : 13

wins · 0 ties · 13 shared

GPT-6 Astra

#1·Index 99.0A+

GPT-6 Astra comes out ahead on 13 of the 13 tests both have taken.

Category means

  • Reasoning

    74.8
    99.6
  • Knowledge

    44.5
    100.0
  • Coding

    57.0
    97.7
  • Math

    59.2
    99.8
  • Agentic

    98.5
  • Human preference

    80.5

Shared tests · biggest gaps first

Bars are distances to the best published result on each test (percent scores above chance, Arena ratings as win rate against the leader, open-ended values on a log scale). Raw values as the publishers report them.

Open GPT-6 Astra

Scores

Every test, every source

The best published run per benchmark, the raw value as the publisher reports it, who produced the number, how close it comes to the best published result on that test, and where the model sits among every model scored on it. Percent scores are read above chance, Arena ratings as a win rate against the board leader, open-ended values on a log scale. A test with too few models to compare against is shown but not counted.

Category means

  • Reasoning74.8 · 5/6
  • Knowledgebeside44.5 · 1/1
  • Coding57.0 · 4/7
  • Math59.2 · 4/5
  • Agentic
  • Multimodal
  • Human preferencebeside80.5 · 1/1
  • Long context

Mean · tests taken of the category's comparable tests. A faded category either rests on fewer than half of them or is a single-test category (marked “beside”), which is shown next to the Index and never averaged into it.

GPQA DiamondEpoch-runReasoning

91.0%

93.3% of the best (95.8%), above chance
74th percentile of 78 · n = 198

max

Source: Epoch AI — AI Benchmarking Hub
ARC-AGI-2LeaderboardReasoning

61.4%

64.6% of the best (95.0%)
62th percentile of 51 · n = 120

max

Source: Epoch AI — AI Benchmarking Hub
ARC-AGI-1LeaderboardReasoning

89.0%

90.4% of the best (98.5%)
56th percentile of 51 · n = 100

max

Source: Epoch AI — AI Benchmarking Hub
SimpleBenchLeaderboardReasoning

61.1%

74.6% of the best (81.9%)
53th percentile of 46

Source: Epoch AI — AI Benchmarking Hub
CritPtLeaderboardReasoning

16.6%

51.3% of the best (32.3%)
70th percentile of 78

max

Source: Epoch AI — AI Benchmarking Hub
SimpleQA VerifiedEpoch-runKnowledge

33.6%

44.5% of the best (75.6%)
25th percentile of 57 · n = 1,000

max

Source: Epoch AI — AI Benchmarking Hub
SciCodeLeaderboardCoding

49.9%

80.4% of the best (62.0%)
58th percentile of 73 · n = 338

max

Source: Epoch AI — AI Benchmarking Hub
WeirdMLLeaderboardCoding

63.0%

67.8% of the best (92.9%)
65th percentile of 69

max

Source: Epoch AI — AI Benchmarking Hub
FrontierCodeLeaderboardCoding

18.8%

35.2% of the best (53.5%)
19th percentile of 27

harness: chisel · reasoning effort: high

Source: Epoch AI — AI Benchmarking Hub
Code Arena (WebDev)LeaderboardCoding

1,580

22% expected win rate against the board leader (1,797)
81th percentile of 86

high · board 2026-09-05

Source: Arena (LMArena) — Leaderboard Dataset

94.4%

94.4% of the best (100.0%)
68th percentile of 78 · n = 45

max

Source: Epoch AI — AI Benchmarking Hub

57.5%

61.4% of the best (93.7%)
53th percentile of 61 · n = 290

max

Source: Epoch AI — AI Benchmarking Hub
FrontierMath Tier 4Epoch-runMath

24.4%

25.0% of the best (97.6%)
40th percentile of 51 · n = 48

max

Source: Epoch AI — AI Benchmarking Hub
ProofBenchLeaderboardMath

56.0%

56.0% of the best (100.0%)
78th percentile of 61

Source: Epoch AI — AI Benchmarking Hub
Text ArenaLeaderboardHuman preference

1,438

40% expected win rate against the board leader (1,507)
35th percentile of 92

high-preview · board 2026-09-02

Source: Arena (LMArena) — Leaderboard Dataset

Nearby on the leaderboard

Compare with its neighbours.

Theo

The best models, ranked here, working inside Theo.

28 of the models on this page run inside Theo today. Theo picks the right one for each step and always shows which engine answered.