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DeepSeek V4 Flash 0731 (Reasoning, Max Effort)

DeepSeekDeepSeek開源權重MIT · 商用許可

描述

DeepSeek-V4-Flash-Max is the maximum reasoning effort mode of DeepSeek-V4-Flash, a 284B-parameter MoE model with 13B activated parameters and a 1M-token context window. Sharing the V4 series' hybrid attention architecture (Compressed Sparse Attention combined with Heavily Compressed Attention), Manifold-Constrained Hyper-Connections, and Muon optimizer, V4-Flash-Max delivers reasoning performance comparable to V4-Pro when given a larger thinking budget while operating at a fraction of the parameter scale. It is pre-trained on more than 32T tokens and post-trained with a two-stage paradigm of domain-specific expert cultivation followed by on-policy distillation.

發布日期
2026-07-31
參數規模
284.0B
上下文長度
1.0M
支援模態
text

能力雷達圖

49
general
66
coding
91
reasoning
66
science
60
agents
0
multimodal

排行榜排名

領域#排名分數來源
智慧體能力模型榜74
45.0
LS
程式碼能力榜35
88.0
AA
通用能力榜34
82.0
AA
科學能力47
82.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Agents

Terminal-Bench 2.182.7%自報
CyberGym76.7%自報
BrowseCompOpenAI (2025)73.2%自報
MCP Atlas69.0%自報
DSBench-FullStack68.7%自報
DSBench-Hard59.6%自報
Terminal-Bench 2.0Stanford × Laude Institute (2026)56.9%自報
DeepSWE54.4%自報
NL2Repo54.2%自報
SWE-Bench ProPrinceton NLP (2024)52.6%自報
Toolathlon47.8%自報
Agents' Last Exam25.2%自報
AutomationBench25.1%自報

Biology

GPQANYU + Cohere + Anthropic (2023)88.1%自報

Code

LiveCodeBench91.6%自報
SWE-Bench Verified79.0%自報
SWE-bench Multilingual73.3%自報

Factuality

SimpleQA34.1%自報

Finance

MMLU-Pro86.2%自報

General

CSimpleQA78.9%自報
MRCR 1M78.7%自報
CorpusQA 1M60.5%自報

Math

CodeForces1.00 / 3000自報
HMMT Feb 2694.8%自報
IMO-AnswerBench88.4%自報
MathArena Apex85.7%自報
Humanity's Last Exam45.1%自報

AA 評測指數

(Artificial Analysis)
Coding Index(Artificial Analysis)
69.1
Intelligence Index(Artificial Analysis)
51.8
Gpqa(NYU + Cohere + Anthropic (2023))
0.9
Terminalbench V2 1
0.8
Lcr(Artificial Analysis)
0.7
Scicode(UIUC + Argonne National Lab (2024))
0.5
Tau Banking
0.4
Hle(Center for AI Safety + Scale AI (2025))
0.4

LLM Stats 分類評分

(LLM Stats (zeroeval))
Legal
90
Physics
90
Finance
90
Healthcare
90
Biology
90
Chemistry
90
Math
80
Language
80
Frontend Development
80
Long Context
70
Reasoning
70
Search
70
General
70
Code
70
Agents
60
Tool Calling
60
Vision
50
Factuality
30

定價

輸入價格$0.14 / 1M tokens
輸出價格$0.28 / 1M tokens
混合價格(3:1)$0.175 / 1M tokens
快取讀取價格$0.0028 / 1M tokens

速度

Tokens/秒109.1
首Token延遲0.96s
首回答延遲19.29s

供應商價格排行

供應商價格排行

8 個供應商

最便宜: DeepSeek最貴: TensorX
供應商輸入輸出
1DeepSeek最便宜
$0
$0
2OpenRouter
$0.08
$0.18
3NanoGPT
$0.14
$0.28
4Kilo Gateway
$0.14
$0.28
5Ambient
$0.14
$0.28
6Merge Gateway
$0.14
$0.28
7Vercel AI Gateway
$0.2
$0.4
8TensorX
$0.25
$0.3

比較該模型在不同 API 供應商之間的定價。

外部連結