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ModelCap

DeepSeek V4 Pro 0423

Arena #65Official publisher releaseOpen weights

DeepSeek·#65 of 504 in the all-versions archive

DeepSeek V4 Pro 0423 is a language model from DeepSeek. It ranks #65 of 504 in ModelCap's all-versions archive, with an Index score of 73.8, measured on 2 public benchmarks. Its score range of 68.8–78.8 spans positions #35–#92. It is listed at $0.892 per million input tokens and $1.78 per million output tokens across 13 providers. It reads up to 1M tokens of context, and its weights are openly downloadable.

Figures as of 6 Nov 2026, 13:52 UTC · download the public dataset · methodology

ModelCap Index · All-versions archive
73.8#65
Measured on 2 public benchmarks · range 68.8–78.8
Evidence as of 28 Oct 2026, 00:00 UTC
Market Gravity
61.6
Secondary market signal

Superseded by DeepSeek V4 Pro 0813. It no longer holds a current-board position; its all-versions archive rank is #65.

Input
$0.892
per 1M tokens
Output
$1.78
per 1M tokens
Context
1M
tokens
Providers
13
14 endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Relacefp4Cheapest$0.90$1.501Mfp4100.0%
SiliconFlowfp8$1.00$1.501Mfp8100.0%
Baidufp8$0.891$1.781Mfp8100.0%
StreamLakefp8$0.892$1.781Mfp8100.0%
GMICloudfp8$0.957$1.911Mfp8100.0%
DigitalOcean$1.04$2.091M—100.0%
DeepInfrafp8$1.30$2.601Mfp8100.0%
Alibabafp8$1.42$2.831Mfp8100.0%
Alibabafp8/us-east-1$1.56$3.121Mfp8100.0%
Novitafp8$1.60$3.201Mfp8100.0%
Venice$1.65$3.301M—100.0%
AtlasCloudfp4$1.68$3.381Mfp4100.0%
Nebiusfp8$1.75$3.501Mfp893.33%
Azureus$1.91$3.831M—100.0%

Hugging Face Inference Providers

Exact repository identity

Provider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.

ProviderInputOutputContextTTFTThroughputFeatures
deepinfra
live
$1.30$2.601M707 ms60.1 tok/stools · structured
novita
live
$1.60$3.201M896 ms42.7 tok/stools
featherless-ai
live
——————

Reported evaluation leads (34)

Not independent measurement

Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.

Dataset / taskMetricValueRevisionProvenance
benchflow/skillsbench
skillsbench_v1_1
—50.1
Pinned
be2a6ce2cb1f4ff67ce937307cade0c5a0477a13
Reported
Quarantined
joelniklaus/LEXam-hard
lexam_hard
—38.93
Pinned
1bd50ee3ac80286fed27e5b89f03f4d8b4494244
Reported
Quarantined
actava/chi-bench
chi_bench
—14.2
Unpinned
not published
Reported
Quarantined
actava/chi-bench
prior_authorization
—10.7
Unpinned
not published
Reported
Quarantined
actava/chi-bench
utilization_management
—28
Unpinned
not published
Reported
Quarantined
actava/chi-bench
care_management
—4
Unpinned
not published
Reported
Quarantined
agents-last-exam/agents-last-exam
overall-pass-rate
—12.3904
Unpinned
not published
Reported
Quarantined
agents-last-exam/agents-last-exam
overall-score
—27.6201
Unpinned
not published
Reported
Quarantined
agents-last-exam/agents-last-exam
ale-cli-pass-rate
—14.127
Unpinned
not published
Reported
Quarantined
agents-last-exam/agents-last-exam
ale-cli-score
—30.8416
Unpinned
not published
Reported
Quarantined
agents-last-exam/agents-last-exam
near-term-pass-rate
—19.9005
Unpinned
not published
Reported
Quarantined
agents-last-exam/agents-last-exam
near-term-score
—43.8117
Unpinned
not published
Reported
Quarantined
agents-last-exam/agents-last-exam
full-spectrum-pass-rate
—10.9091
Unpinned
not published
Reported
Quarantined
agents-last-exam/agents-last-exam
full-spectrum-score
—23.799
Unpinned
not published
Reported
Quarantined
agents-last-exam/agents-last-exam
last-exam-pass-rate
—0
Unpinned
not published
Reported
Quarantined
agents-last-exam/agents-last-exam
last-exam-score
—2.5213
Unpinned
not published
Reported
Quarantined
cais/hle
hle
—37.7
Unpinned
not published
Reported
Quarantined
claw-eval/Claw-Eval
general
—58.4
Unpinned
not published
Reported
Quarantined
claw-eval/Claw-Eval
multi_turn
—65.8
Unpinned
not published
Reported
Quarantined
collinear-ai/yc-bench
medium
—1,066,426
Unpinned
not published
Reported
Quarantined

Showing 20 of 34 rows.

Other versions (1)

ModelCap Index · All-versions archive

Methodology
73.8
Measured on 2 public benchmarks
All-versions archive
#65 of 504
Score range
68.8–78.8
Rank range
#35–#92
Evidence as of
28 Oct 2026, 00:00 UTC
Benchmarks used
Arena Coding, Arena Overall
Technical details
Public rank basis
Measured (measured)
Evidence label
Measured · 2 public benchmark observations across 2 boards
Index support
63.0% · strong
Identity binding
Exact catalogue product · deepseek/deepseek/deepseek-v4-pro/fp8 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata deepseek-ai/DeepSeek-V4-Pro@b5968e9190ef611bbf34a7229255be88a0e937c1 (not the evaluation revision)
Index observations used
2
Qualified Index evidence point
73.8
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
73.8
Evidence status
confirmed · 77% mass
General preference
74.3
Coding
69.8
Agents & tools
—
Reasoning
—
Evidence breadth
92%
Evidence coverage
63%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
37.1
Liquidity (providers × uptime)
99.5
Open reach (HF downloads)
93.3
Surface (context / tools / modalities)
85.0
Freshness
47.3
  • · OpenRouter popularity #39
  • · 13 live providers
  • · HF 30d downloads 333616
  • · Catalogue: context 1048576, reasoning, tools
  • · First seen 2026-04-24

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

BES evidence selected · measured input only

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Deployment readiness

Metadata index
85.9
strong · 94% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
100.0
Deployability
98.8
Evaluation provenance
54.0

Not yet published: the base model it derives from, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
61.6
OpenRouter weekly popularity
#39 of 339

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

Status
Ranked
Source
LMArena
Official rank
#65 of 419
Rating
1457.8
95% confidence interval
1454–1462
Votes
58K
Source published at
28 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
99%

Market Gravity breakdown

Usage55%
37.1

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
99.5

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
93.3

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
47.3

Time since first public availability, on a six-month half-life.

Specification

Model ID
deepseek/deepseek-v4-pro
Context window
1M tokens
Declared output cap
384K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text
Outputs
Text
Tokenizer
DeepSeek
Cached input tokens
$0.074 / 1M
First seen on OpenRouter
24 Apr 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Not supported: Moderated

Weights & access

Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.

Access
Open weights
Licence
mit
Pinned revision
b5968e9190ef
Parameters
1598.8B
Architecture
DeepseekV4ForCausalLM
Model type
deepseek_v4
Hugging Face downloads (30d)
334K
Downloads (all time)
11.1M
Likes
6K
Repository updated
22 Jun 2026, 12:12 UTC

Benchmark leaderboards featuring DeepSeek V4 Pro 0423

All leaderboards
Public benchmark boards on which DeepSeek V4 Pro 0423 has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)14581454–1462#65 of 419Not reported28 Oct 2026
Arena coding leaderboardArena (LMArena)15001494–1506#80 of 414Default28 Oct 2026
WildClawBench OpenClaw leaderboardWildClawBench43.7#19 of 34Default20 Jul 2026

DeepSeek V4 Pro 0423: common questions

How does DeepSeek V4 Pro 0423 rank among AI models?

DeepSeek V4 Pro 0423 is a superseded version and is not on the current board as of 6 November 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.

How much does DeepSeek V4 Pro 0423 cost per 1M tokens?

DeepSeek V4 Pro 0423 is listed at $0.892 per 1M input tokens and $1.78 per 1M output tokens as of 6 November 2026; the lowest output price among 13 providers is $1.50 on Relace. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $2.68 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of DeepSeek V4 Pro 0423?

DeepSeek V4 Pro 0423 has a published context window of 1M tokens (1,048,576). The snapshot lists a 384,000 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is DeepSeek V4 Pro 0423 open-weight?

Open weights (mit). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is deepseek-ai/DeepSeek-V4-Pro on Hugging Face.

Which API providers serve DeepSeek V4 Pro 0423?

13 providers serve DeepSeek V4 Pro 0423 through OpenRouter as of 6 November 2026: Baidu, StreamLake, Relace, GMICloud, SiliconFlow and DigitalOcean and 7 more. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has DeepSeek V4 Pro 0423 been evaluated on?

DeepSeek V4 Pro 0423 has published results on 3 public boards tracked by ModelCap as of 6 November 2026: Arena text 1458 (#65 of 419), Arena coding 1500 (#80 of 414) and WildClawBench OpenClaw 43.7 (#19 of 34). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

When was DeepSeek V4 Pro 0423 released?

DeepSeek V4 Pro 0423 first appeared in the catalogue on 24 Apr 2026. It has since been superseded by DeepSeek V4 Pro 0813. Rank and price movements since then are recorded on the site's changes feed.