DeepSeek V4 Flash 0731 (Reasoning, Max Effort) Intelligence, Performance & Price Analysis
[](https://artificialanalysis.ai/login)K
•
Proprietary model
•
Released July 2026
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) Intelligence, Performance & Price Analysis
CompareAPI Provider Benchmarks
Model summary
#### Intelligence
#2 / 162
50
Artificial Analysis Intelligence Index
4 out of 4 units for Intelligence.
#### Speed
N/A
Output tokens per second
Unknown out of 4 units for Speed.
#### Price
#1 / 162
Input
$0.14
per 1M tokens
Output
$0.28
per 1M tokens
1 out of 4 units for Price.
#### Cache Hit Price
#1 / 162
$0.003(-98%)
USD per 1M tokens
1 out of 4 units for Cache Hit Price.
#### Verbosity
#58 / 162
210M
Output tokens from Intelligence Index
4 out of 4 units for Verbosity.
Comparison Summary
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) is amongst the leading models in intelligence and well priced when comparing to other models of similar price. The model supports text input, outputs text, and has a 1M tokens context window.
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) scores 50 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 17). When evaluating the Intelligence Index, it generated 210M tokens, which is very verbose in comparison to the median of 62M.
Pricing for DeepSeek V4 Flash 0731 (Reasoning, Max Effort) is $0.14 per 1M input tokens (competitively priced, median: $0.25) and $0.28 per 1M output tokens (competitively priced, median: $0.88). In total, it cost $72.02 to evaluate DeepSeek V4 Flash 0731 (Reasoning, Max Effort) on the Intelligence Index.
Technical specifications
| Reasoning | YesThis page shows the reasoning version of this model.A non-reasoning variant may also exist. | | --------------- | ---------------------------------------------------------------------------------------------- | | Input modality | Supports: text | | Output modality | Supports: text | | Context window | 1M\~1500 A4 pages of size 12 Arial font |
162 models in this class
Metrics are compared against models of the same class:
- Non-reasoning models → compared only with other non-reasoning models
- Reasoning models → compared across both reasoning and non-reasoning
- Open weights models → compared only with other open weights models of the same size class: * Tiny: ≤4B parameters * Small: 4B–40B parameters * Medium: 40B–150B parameters * Large: >150B parameters
- Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:
Highlights
Intelligence
Artificial Analysis Intelligence Index · Higher is better
Speed
Output tokens per second · Higher is better
Cost per Task
Weighted average cost (USD) per Intelligence Index task · Lower is better
Prompt Options
Intelligence
Artificial Analysis Intelligence IndexCoding IndexAgentic Index
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR
26 of 590 models
NEW
Add model from specific provider
Reasoning models are indicated by a lightbulb icon
###
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Open Weights / ProprietaryReasoning / Non-ReasoningText Only / Multimodal Inputs
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR
26 of 590 models
NEW
Add model from specific provider
ProprietaryOpen Weights (Commercial Use Restricted)Open Weights
Reasoning models are indicated by a lightbulb icon
###
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
1 more note
Benchmarks
Intelligence Evaluations
Intelligence evaluations measured independently by Artificial Analysis · Higher is better
18 of 22 evaluations
26 of 590 models
NEW
Add model from specific provider
Agentic real-world work tasks, (Elo-500)/2000
Agentic tool use
Agentic coding & terminal use
Coding
Reasoning & knowledge
Scientific reasoning
Physics reasoning
Knowledge
AA-Omniscience Non-Hallucination Rate
1 - hallucination rate
Long context reasoning
Agentic knowledge work, Elo
Agentic SaaS workflows
Legal agentic work, criterion pass rate
Agentic business operations
Instruction following
Long-horizon agentic tasks
Kubernetes incident root-cause analysis
Visual reasoning
Reasoning models are indicated by a lightbulb icon
###
Intelligence Evaluation Relevance
While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.
1 more note
AA-Omniscience
AA-Omniscience IndexAA-Omniscience AccuracyAA-Omniscience Hallucination Rate
AA-Omniscience Index
AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.
26 of 460 models
NEW
Add model from specific provider
Reasoning models are indicated by a lightbulb icon
###
AA-Omniscience Index
AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.
Intelligence Index Comparisons
Intelligence Index vs. Cost per TaskIntelligence Index vs. Time per TaskIntelligence Index vs. Output SpeedIntelligence Index vs. End-to-End Response Time
Intelligence Index vs. Cost per Intelligence Index Task
Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task
26 of 590 models
NEW
Most attractive quadrant
DeepSeekGoogleAnthropicZ AIOpenAISpaceXAIKimiNVIDIAMiniMaxMetaXiaomiTencentThinking MachinesAlibaba
Reasoning models are indicated by a lightbulb icon
###
Cost per Intelligence Index Task
Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight.
1 more note
Token Use
Output Tokens per TaskIntelligence Index vs. Output Tokens per TaskIntelligence Index Token UseIntelligence Index vs. Token Use
Output Tokens per Intelligence Index Task
Weighted average number of output tokens used to run one task in the Artificial Analysis Intelligence Index
26 of 590 models
NEW
AnswerReasoning
Reasoning models are indicated by a lightbulb icon
###
Output Tokens per Intelligence Index Task
The number of tokens required per Intelligence Index task. This is calculated by multiplying the output tokens per eval by the relative weights of each benchmark in the Intelligence Index, then dividing by task count (excluding repeats).
Cost
Cost per TaskIntelligence Index vs. Cost per TaskEvaluation Breakdown
Cost per Intelligence Index Task
Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better
26 of 590 models
NEW
AnswerReasoningCache WriteCache HitInput
Reasoning models are indicated by a lightbulb icon
###
Cost per Intelligence Index Task
Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight.
Intelligence Index Total CostIntelligence Index vs. Total Cost
Cost to Run Artificial Analysis Intelligence Index
Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index
26 of 590 models
NEW
Add model from specific provider
OutputReasoningCache WriteCache ReadNon-Cache Input
Reasoning models are indicated by a lightbulb icon
###
Cost to Run Artificial Analysis Intelligence Index
The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input, cache hit, cache write, reasoning, and answer token prices and the number of tokens used across evaluations (excluding repeats).
Cache Hit, Input, and Output PricingBlended PriceBlended Price (Stacked)Cache DiscountIntelligence Index vs. PriceIntelligence Index vs. Price (Log, Inverted)Image Input Pricing
Pricing: Cache Hit, Input, and Output
Price (USD per M Tokens)
26 of 590 models
NEW
Add model from specific provider
Cache HitInputOutput
Reasoning models are indicated by a lightbulb icon
###
Cache Hit
Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.
4 more notes
Context Window
Context WindowIntelligence Index vs. Context Window
Context Window
Context window: tokens limit · Higher is better
26 of 590 models
NEW
Add model from specific provider
Reasoning models are indicated by a lightbulb icon
###
Context Window for RAG
Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.
1 more note
Frequently Asked Questions
Common questions about DeepSeek V4 Flash 0731 (Reasoning, Max Effort)
When was DeepSeek V4 Flash 0731 (Reasoning, Max Effort) released?
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) was released on July 31, 2026.
Who created DeepSeek V4 Flash 0731 (Reasoning, Max Effort)?
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) was created by DeepSeek.
How intelligent is DeepSeek V4 Flash 0731 (Reasoning, Max Effort)?
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) scores 50 on the Artificial Analysis Intelligence Index, placing it well above average among other reasoning models in a similar price tier (median: 17).
How much does DeepSeek V4 Flash 0731 (Reasoning, Max Effort) cost?
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) costs $0.14 per 1M input tokens (very competitive, median: $0.25) and $0.28 per 1M output tokens (very competitive, median: $0.88), based on DeepSeek's API.
What is DeepSeek V4 Flash 0731 (Reasoning, Max Effort) API pricing?
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) costs $0.14 per 1M input tokens and $0.28 per 1M output tokens (based on DeepSeek's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $0.06 per 1M tokens. Pricing may vary by provider. Compare provider pricing
How verbose is DeepSeek V4 Flash 0731 (Reasoning, Max Effort)?
When evaluated on the Intelligence Index, DeepSeek V4 Flash 0731 (Reasoning, Max Effort) generated 210M output tokens, which is at the higher end compared to other reasoning models in a similar price tier (median: 62M).
Is DeepSeek V4 Flash 0731 (Reasoning, Max Effort) a reasoning model?
Yes, DeepSeek V4 Flash 0731 (Reasoning, Max Effort) is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.
What input modalities does DeepSeek V4 Flash 0731 (Reasoning, Max Effort) support?
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) supports text input.
What output modalities does DeepSeek V4 Flash 0731 (Reasoning, Max Effort) support?
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) supports text output.
Can DeepSeek V4 Flash 0731 (Reasoning, Max Effort) process images?
No, DeepSeek V4 Flash 0731 (Reasoning, Max Effort) does not support image input. It can only process text.
Is DeepSeek V4 Flash 0731 (Reasoning, Max Effort) multimodal?
No, DeepSeek V4 Flash 0731 (Reasoning, Max Effort) is not multimodal. It only supports text input.
What is the context window of DeepSeek V4 Flash 0731 (Reasoning, Max Effort)?
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) has a context window of 1.0M tokens. This determines how much text and conversation history the model can process in a single request.
Is DeepSeek V4 Flash 0731 (Reasoning, Max Effort) open source?
No, DeepSeek V4 Flash 0731 (Reasoning, Max Effort) is proprietary. The model weights are not publicly available.
How many parameters does DeepSeek V4 Flash 0731 (Reasoning, Max Effort) have?
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) has 284 billion parameters.
How does DeepSeek V4 Flash 0731 (Reasoning, Max Effort) perform on benchmarks?
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) achieves a score of 50 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.
Is DeepSeek V4 Flash 0731 (Reasoning, Max Effort) available via API?
Yes, DeepSeek V4 Flash 0731 (Reasoning, Max Effort) is available via API through 1 provider. Compare API providers
Where can I use DeepSeek V4 Flash 0731 (Reasoning, Max Effort)?
DeepSeek V4 Flash 0731 (Reasoning, Max Effort) is available through 1 API provider. Compare providers