Model profile
DeepSeek
New in 2026

DeepSeek V4 Flash Vision (Reasoning, Max Effort)

DeepSeek V4 Flash Vision (Reasoning, Max Effort) is a budget-priced text-first model from DeepSeek with fast runtime profile, partial context coverage, and the clearest fit around agent workflows / coding.

Best for: Agent workflows / CodingFast latencyN/A contextBudget pricing
Intelligence
51.5

Benchmark blend

Coding
65.0

Dev workflow signal

Context
N/A

N/A

Input Price
$0.44

Budget tier

Decision snapshot
67

DeepSeek V4 Flash Vision (Reasoning, Max Effort) currently reads as a budget text-first option with partially published context and a fast runtime profile.

Overall profile
Selective fit
Best for
Agent workflows / Coding
Latency tier
Fast
Price tier
Budget
Source coverage
OpenRouterArtificial Analysis

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
51.5
52

General reasoning and benchmark headroom.

Situational
Speed
115 tok/s
82

TTFT 0.97s

Above average
Context
N/A
N/A

How much prompt and task state can stay in view.

Unavailable
Price
$0.44
86

$1.32 output / 1M

Efficient

Editorial Profile

DeepSeek V4 Flash Vision (Reasoning, Max Effort) in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Selective fitCoding score 65Math score N/A

The DeepSeek V4 Flash Vision (Reasoning, Max Effort) AI model by DeepSeek.

Identity

DeepSeek text-first profile

Positioning

Agent workflows / Coding with partially published context and fast runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • Latency and throughput look responsive enough for interactive loops.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

  • Context limits are only partially published, so long-session planning needs extra validation.

Best fit
  • Code generation, refactors, test writing, and tool-assisted debugging.

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Context
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Input Price
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Intelligence
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Context
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Input Price
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Intelligence
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Context
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Input Price
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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
51.5
GPQA
91.3%
HLE
34.5%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
65.0
SciCode
46.6%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

LCR
78.0%

Extra benchmark cuts are not available for this category yet.

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
N/A
Vision
Text-first
Price architecture
Input
per 1M input tokens
$0.44
Output
per 1M output tokens
$1.32
Blended
AA 3:1 mix
$0.66

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.