Model profile
DeepSeek
New in 2026

DeepSeek: DeepSeek V4 Pro 0423

DeepSeek: DeepSeek V4 Pro 0423 is a budget-priced text-first model from DeepSeek with balanced runtime profile, large context posture, and the clearest fit around long-context research / agent workflows.

Best for: Long-context research / Agent workflowsBalanced latencyLarge contextBudget pricing
Intelligence
53.2

Benchmark blend

Coding
68.8

Dev workflow signal

Context
1049K Tokens

Large

Input Price
$1.32

Budget tier

Decision snapshot
70

DeepSeek: DeepSeek V4 Pro 0423 currently reads as a budget text-first option with large context and a balanced runtime profile.

Overall profile
Strong all-rounder
Best for
Long-context research / Agent workflows
Latency tier
Balanced
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
53.2
53

General reasoning and benchmark headroom.

Situational
Speed
67 tok/s
64

TTFT 1.08s

Competitive
Context
1049K Tokens
100

How much prompt and task state can stay in view.

Above average
Price
$1.32
86

$3.96 output / 1M

Efficient

Editorial Profile

DeepSeek: DeepSeek V4 Pro 0423 in one narrative

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

Strong all-rounderCoding score 69Math score N/A

DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...

Identity

DeepSeek text-first profile

Positioning

Long-context research / Agent workflows with large context and balanced runtime.

Cost posture

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

Strengths
  • Coding indicators point to a strong developer workflow fit.

  • Large context headroom supports repo-wide prompts and long research sessions.

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

  • Latency is balanced rather than ultra-fast, which is fine for most workflows but not the snappiest tier.

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

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

  • Long-context summarization, repo analysis, and policy or document review.

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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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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
53.2
GPQA
92.8%
HLE
41.0%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
68.8
SciCode
49.2%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

LCR
75.3%

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
1049K Tokens
Vision
Text-first
Modalities
text
Tokenizer
DeepSeek
Max Completion
384000
Moderation
No
Supported Parameters
frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_completion_tokensmax_tokensmin_ppresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p
Input Modalities
text
Output Modalities
text
Price architecture
Input
per 1M input tokens
$1.32
Output
per 1M output tokens
$3.96
Blended
AA 3:1 mix
$1.98

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

OR Cache Read
$0.00

Metadata

Raw source tables at the end

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