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Model profile

DeepSeek V4 Flash Base

DeepSeekCurrentReleased Apr 24, 2026
Data verified
Overall Score
Unranked
Arena Elo
Not listed
Eligible category ranks
1of 8
Price (1M tokens)
Not listedAPI pricing
Speed
Not listed
Context
1M

Evidence coverage

24 of 323 tracked benchmarks are published. 24 are verified and 0 provisional. 5 of 8 categories are measured.

Updated July 23, 2026Methodology
Published / tracked
24 / 323
Verified
24
Provisional
0
Categories with evidence
5 / 8

Evidence by category

  • Agentic0 benchmarks
    Not measured
  • Coding2 benchmarks
    Verified
  • Reasoning6 benchmarks
    Verified
  • Knowledge12 benchmarks
    Verified
  • Math3 benchmarks
    Verified
  • Multilingual1 benchmark
    Verified
  • Multimodal0 benchmarks
    Not measured
  • Inst. Following0 benchmarks
    Not measured
Open WeightSelf-hostNon-Reasoning
Confidence:
Low
base

BenchLM is tracking DeepSeek V4 Flash Base, but this profile is currently excluded from the public leaderboard because it still lacks enough non-generated benchmark coverage to rank safely. Only non-generated public benchmark rows appear below.

DeepSeek V4 Flash Base is a open weight model with a 1M token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.

DeepSeek V4 Flash Base sits inside the DeepSeek V4 family alongside DeepSeek V4 Pro (Max), DeepSeek V4 Pro (High), DeepSeek V4 Flash (Max), DeepSeek V4 Flash (High), DeepSeek V4 Pro, DeepSeek V4 Pro Base, DeepSeek V4 Flash. This profile currently has 24 of 323 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.

Its strongest category is Knowledge (#48). This performance profile makes it particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.

Peer position

Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.

Range 77.4483.93

  1. Claude Mythos 5
    Anthropic
    #183.93
    Claude Mythos 5 is #1 with a score of 83.93.
    Compare
  2. Claude Fable 5
    Anthropic
    #283.68
    Claude Fable 5 is #2 with a score of 83.68.
    Compare
  3. GPT-5.6 Sol
    OpenAI
    #381.96
    GPT-5.6 Sol is #3 with a score of 81.96.
    Compare
  4. Kimi K3
    Moonshot AI
    #480.96
    Kimi K3 is #4 with a score of 80.96.
    Compare
  5. Claude Opus 4.8
    Anthropic
    #578.34
    Claude Opus 4.8 is #5 with a score of 78.34.
    Compare
  6. Muse Spark 1.1
    Meta
    #677.44
    Muse Spark 1.1 is #6 with a score of 77.44.
    Compare
  7. DeepSeek V4 Flash BaseCurrent model
    DeepSeek
    UnrankedNot measured
    DeepSeek V4 Flash Base is Unranked with a score of Not measured.

Category percentile

More

Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.

  1. Knowledge8%
    Eligible cohort rank #48 of 52Category score 53.8

Category evidence

Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticWeight 22%0 benchmarksNot measuredNot measured
CodingWeight 20%2 benchmarksVerifiedScore pending
ReasoningRank Not rankedWeight 17%6 benchmarksVerified22.0
KnowledgeRank #48 of 52Percentile 8thWeight 12%12 benchmarksVerified53.8
MathWeight 5%3 benchmarksVerifiedScore pending
MultilingualWeight 7%1 benchmarkVerifiedScore pending
MultimodalWeight 12%0 benchmarksNot measuredNot measured
Inst. FollowingWeight 5%0 benchmarksNot measuredNot measured

Benchmark Details

Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.

Coding2 benchmarks
BigCodeBenchProvider exact
56.8%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
HumanEvalProvider exact

Evaluating Large Language Models Trained on Code

69.5%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
Reasoning6 benchmarks
LongBench v2Provider exact
44.7%Weighted 38%
Source: DeepSeek-V4 technical reportProvenance: Provider exact
BBHProvider exact

BIG-Bench Hard

86.9%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
DROPProvider exact

Discrete Reasoning Over Paragraphs

88.6%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
HellaSwagProvider exact
85.7%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
WinoGrandeProvider exact
79.5%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
CLUEWSCProvider exact
82.2%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
Knowledge12 benchmarks
MMLU-ProProvider exact

Massive Multitask Language Understanding Professional

68.3%Weighted 30%
Source: DeepSeek-V4 technical reportProvenance: Provider exact
SimpleQAProvider exact

Measuring Short-Form Factuality in Large Language Models

30.1%Weighted 11%
Source: DeepSeek-V4 technical reportProvenance: Provider exact
SuperGPQAProvider exact

SuperGPQA: Scaling LLM Evaluation Across 285 Graduate Disciplines

46.5%Weighted 7%
Source: DeepSeek-V4 technical reportProvenance: Provider exact
AGIEvalProvider exact
82.6%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
MMLUProvider exact

Massive Multitask Language Understanding

88.7%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
MMLU-ReduxProvider exact
89.4%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
MMMLUProvider exact
88.8%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
C-EvalProvider exact
92.1%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
CMMLUProvider exact

Chinese Massive Multitask Language Understanding

90.4%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
MultiLoKoProvider exact
42.2%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
FACTS ParametricProvider exact
33.9%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
TriviaQAProvider exact
82.8%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
Math3 benchmarks
GSM8KProvider exact

Grade School Math 8K

90.8%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
MATHProvider exact
57.4%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
CMathProvider exact
93.6%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact
Multilingual1 benchmark
MGSMProvider exact

Multilingual Grade School Math

85.7%Display only
Source: DeepSeek-V4 technical reportProvenance: Provider exact

Frequently Asked Questions

How does DeepSeek V4 Flash Base perform overall in AI benchmarks?

DeepSeek V4 Flash Base has 24 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.

Is DeepSeek V4 Flash Base good for knowledge and understanding?

DeepSeek V4 Flash Base ranks #48 out of 52 models in knowledge and understanding benchmarks with an average score of 53.8. There are stronger options in this category.

Is DeepSeek V4 Flash Base good for coding and programming?

DeepSeek V4 Flash Base has visible benchmark coverage in coding and programming, but BenchLM does not currently assign it a global category rank there.

Is DeepSeek V4 Flash Base good for mathematics?

DeepSeek V4 Flash Base has visible benchmark coverage in mathematics, but BenchLM does not currently assign it a global category rank there.

Is DeepSeek V4 Flash Base good for reasoning and logic?

DeepSeek V4 Flash Base has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.

Is DeepSeek V4 Flash Base good for multilingual tasks?

DeepSeek V4 Flash Base has visible benchmark coverage in multilingual tasks, but BenchLM does not currently assign it a global category rank there.

Is DeepSeek V4 Flash Base open source?

Yes, DeepSeek V4 Flash Base is an open weight model created by DeepSeek, meaning it can be downloaded and run locally or fine-tuned for specific use cases.

Which sibling models are related to DeepSeek V4 Flash Base?

DeepSeek V4 Flash Base belongs to the DeepSeek V4 family. Related variants on BenchLM include DeepSeek V4 Pro (Max), DeepSeek V4 Pro (High), DeepSeek V4 Flash (Max), DeepSeek V4 Flash (High), DeepSeek V4 Pro, DeepSeek V4 Pro Base, DeepSeek V4 Flash.

Does DeepSeek V4 Flash Base have full benchmark coverage on BenchLM?

Not yet. DeepSeek V4 Flash Base currently has 24 published benchmark scores out of the 323 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.

What is the context window size of DeepSeek V4 Flash Base?

DeepSeek V4 Flash Base has a published context window of 1M, which determines how much text it can process in a single interaction.

Last updated: July 23, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

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