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DeepSeek released on Jul 31, 2026 Open weights (unrestricted)

DeepSeek V4 Flash 0731

DeepSeek V4 Flash 0731 (DeepSeek) was released on Jul 31, 2026. In the Epoch AI capability ranking (ECI), it ranks #36 out of 267 models, with 154.49. On LiveBench, the overall average is 74.2, #34 out of 58 scored models. Against models of the same generation, its best result is on ALE-Bench: 1,306, #22 of 64.

#36 of 267 in the ECI ranking
154.49 ECI, the Epoch AI capability index
no match Arena ELO, human preference
74.2 LiveBench, overall average from 0 to 100 · #34
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What the tests say

Where DeepSeek V4 Flash 0731 stands out and where it falls behind, by the numbers

DeepSeek V4 Flash 0731 has published results on 18 tests compiled by Epoch AI. The yardstick here is its generation: its position among the models released between Nov 3, 2025 and Oct 29, 2026 that took the same test. Against the whole archive, which includes 2023 models, a recent release lands near the top of almost everything, and that says nothing.

Where it stands out

Tests where it sits in the top third of its own generation.

ALE-Bench1,306
#22 of 64 in its generation · #22 of 82 overall

Where it falls behind

Tests where it sits in the bottom half of its own generation.

FrontierCode18.8%
#37 of 43 in its generation · record: 54.6% (Claude Opus 5.5)
SimpleQA Verified33.6%
#52 of 64 in its generation · record: 76.0% (Gemini 4 Argon)
Frontiermath Tier 4 V224.4%
#41 of 58 in its generation, tied with 1 · record: 100.0% (GPT-6.1 Sol)
Chess puzzles32.0%
#42 of 64 in its generation · record: 76.0% (GPT-6 Astra)
SciCode49.9%
#49 of 76 in its generation · record: 66.9% (Claude Opus 5.5)
See all 18 tests, one by one
TestScoreIn its generationOverallTest record
GPQA Diamond 91.0% #28 / 81 (tied with 1) #28 / 173 96.4% Gemini 4 Argon
AIME 2024 and 2025 (OTIS) 94.4% #42 / 83 #42 / 168 100.0% GPT-5.5
Dtbench 90.9% #32 / 69 (tied with 2) #32 / 148 98.9% Claude Opus 5.5
Lmca 41.73 #42 / 69 #42 / 121 68.23 Claude Opus 5.5
CritPt 16.6% #35 / 79 #35 / 112 32.3% GPT-5.6 Sol
WeirdML 63.0% #25 / 54 #25 / 112 93.6% GPT-6 Astra
SciCode 49.9% #49 / 76 #49 / 104 66.9% Claude Opus 5.5
Frontiermath Tiers 1 3 V2 57.5% #42 / 68 #42 / 86 93.7% GPT-6 Astra
ARC-AGI 2 61.4% #25 / 50 (tied with 1) #25 / 83 95.0% GPT-6 Astra
ALE-Bench 1,306 #22 / 64 #22 / 82 2,951 GPT-6 Astra
ARC-AGI 89.0% #29 / 50 #29 / 81 98.5% Claude Fable 5
SimpleQA Verified 33.6% #52 / 64 #57 / 81 76.0% Gemini 4 Argon
Chess puzzles 32.0% #42 / 64 #45 / 80 76.0% GPT-6 Astra
Game puzzles 34.0% #22 / 62 (tied with 2) #22 / 77 84.0% GPT-6 Astra
ProofBench 56.0% #24 / 70 (tied with 1) #24 / 74 100.0% Claude Fable 5.1
SimpleBench 61.1% #19 / 38 (tied with 1) #21 / 74 81.9% Claude Fable 5
Frontiermath Tier 4 V2 24.4% #41 / 58 (tied with 1) #41 / 67 100.0% GPT-6.1 Sol
FrontierCode 18.8% #37 / 43 #37 / 43 54.6% Claude Opus 5.5

For each test, the model's best effort level counts, as in the ranking. Source of the scores: Epoch AI, under CC BY 4.0.

Comparison

What to compare DeepSeek V4 Flash 0731 with

The models from other labs closest in capability and released in the same period, at most two per lab. Click any of them to see its page.

ModelLabECIELOLiveBenchRelease
Muse Spark 1.2 Meta AI 154.90 1,509 78.0 Aug 5, 2026
Gemini 3.1 Pro Google DeepMind 154.67 1,528 77.0 Feb 19, 2026
DeepSeek V4 Flash 0731 DeepSeek 154.49 n/a 74.2 Jul 31, 2026
Gemini 3.5 Flash Google DeepMind 154.38 1,526 74.6 May 19, 2026
Grok 4.7 xAI 154.37 1,453 77.4 Sep 21, 2026
Muse Spark 1.1 Meta AI 154.00 1,516 75.3 Jul 9, 2026
GPT-5.2 Codex OpenAI no ECI n/a 74.0 Dec 18, 2025
Head to head

DeepSeek V4 Flash 0731 or Gemini 3.5 Flash?

Gemini 3.5 Flash is the model from another lab closest to DeepSeek V4 Flash 0731 in capability. Across the 17 tests both took, this is the score:

DeepSeek V4 Flash 0731 ahead on 5 Gemini 3.5 Flash ahead on 12
Largest differences first
TestDeepSeek V4 Flash 0731Gemini 3.5 Flash
SimpleQA Verified 33.6% 66.2%
ProofBench 56.0% 31.0%
ALE-Bench 1,306 911
Chess puzzles 32.0% 45.0%
CritPt 16.6% 13.1%
SimpleBench 61.1% 76.7%
ARC-AGI 2 61.4% 72.1%
Lmca 41.73 47.15
Frontiermath Tier 4 V2 24.4% 26.8%
Frontiermath Tiers 1 3 V2 57.5% 62.8%

Unweighted score: each test counts one point, whether math or coding. The dot marks who did better on each row.

Family

Other models from DeepSeek

The models from the same lab closest in time, newest first.

ModelReleaseECIELOLiveBenchAccess
DeepSeek V4.1 Flash Sep 9, 2026 155.57 n/a 81.1 Open weights (unrestricted)
DeepSeek V4 Pro 0813 Aug 13, 2026 155.29 n/a 77.4 Open weights (unrestricted)
DeepSeek V4 Flash 0731 Jul 31, 2026 154.49 n/a 74.2 Open weights (unrestricted)
DeepSeek-V4-Pro Apr 24, 2026 149.19 1,486 71.6 Open weights (unrestricted)
DeepSeek v4 (unknown) Apr 24, 2026 146.26 n/a n/a Open weights (unrestricted)
DeepSeek-V4-Flash Apr 24, 2026 146.05 1,468 65.5 Open weights (unrestricted)
DeepSeek-V3.2 Dec 1, 2025 146.11 1,455 n/a Open weights (unrestricted)
DeepSeek-V3.2-Exp Sep 29, 2025 144.97 1,461 n/a Open weights (unrestricted)
DeepSeek-V3.1 Aug 21, 2025 139.91 1,469 n/a Open weights (unrestricted)
Your rating

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Frequently asked questions

What people ask about DeepSeek V4 Flash 0731

Where does DeepSeek V4 Flash 0731 rank among AI models?

In the ROO3 AI Benchmark, ordered by the Epoch AI ECI, DeepSeek V4 Flash 0731 ranks #36 out of 267 models, with an ECI of 154.49. The ECI is a composite index that combines several hard benchmarks into a single scale. The position changes when a new model comes out, and the page is refreshed six times a day.

Is DeepSeek V4 Flash 0731 better than Gemini 3.5 Flash?

Across the 17 tests both models took and Epoch AI compiled, DeepSeek V4 Flash 0731 comes out ahead on 5, behind on 12 and tied on 0. It is a test-by-test count with no weighting: a win in math counts the same as a win in coding. To choose between the two, look at the tests that resemble your own use.

What is DeepSeek V4 Flash 0731 best at?

Against models of the same generation (released up to 9 months before and up to 3 months after it), the best relative results of DeepSeek V4 Flash 0731 are: ALE-Bench (#22 of 64). The yardstick is its position among the models of that period that took the same test.

Where do the numbers on this page come from?

From the same three sources as the ranking, all openly licensed: Epoch AI (ECI and individual tests, CC BY 4.0), Arena (human-preference ELO, CC BY 4.0) and LiveBench (overall average, CC BY-SA 4.0). ROO3 does not measure any model. When the page shows a figure published by the maker itself, it appears in the written analysis, labeled as the maker's, and never enters the ranking.

Sources

Where each number comes from

Epoch AI, "AI Benchmarking Hub". Published at epoch.ai. Data under the CC BY 4.0 licence, reordered by roo3.co.

The Arena (LMArena) leaderboard, from the public lmarena-ai/leaderboard-dataset on Hugging Face, under the CC BY 4.0 licence. We are not affiliated with the Arena.

LiveBench, by the LiveBench team, published at livebench.ai under the CC BY-SA 4.0 license. The overall average is recomputed by roo3.co with the same formula as the website (average of the categories), and those numbers stay under CC BY-SA 4.0. We are not affiliated with LiveBench.

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