DeepSeek

DeepSeek V4 Pro 0423

Tool callingStructured outputReasoning
DeepSeek V4 Pro 0423 launch post cover

Open MoE flagship with million-token context for coding and long agent runs

Context
1.0M
Released
5mo ago
Parameters
1.7T
Input / 1M tokens
$0.42
Output / 1M tokens
$0.84
Cached input / 1M tokens
$0.04

Sources:models.devOpenRouter

Benchmarks

DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.

DeepSWE 1.1

Primary coding-agent benchmark · 113 tasks · Data generated 2026-09-22

Official leaderboard
62.8%
pass@1 · highest published configuration
mini-swe-agent · max reasoning
pass@4
88.5%
Average cost / attempt
$0.24
Benchmark runs
4

pass@1 is the success rate across scored attempts; pass@4 is the share of tasks solved in at least one of four attempts. Costs are reported by DeepSWE for each configuration. These results are not directly comparable to evaluations using different harnesses. Official source JSON.

Other published benchmarks

EvaluationReported score and source
FrontierMath-Tier-4-v2-Private
2.4%
Epoch AI · deepseek-v4-pro_max
Reasoning effort: max
Epoch AI evaluation
FrontierMath-Tiers-1-3-v2-Private
45.3%
Epoch AI · deepseek-v4-pro_max
Reasoning effort: max
Epoch AI evaluation
GPQA diamond
90.9%
Epoch AI · deepseek-v4-pro_high
Reasoning effort: high
Epoch AI evaluation
GPQA diamond
89.6%
Epoch AI · deepseek-v4-pro_max
Reasoning effort: max
Epoch AI evaluation
GPQA diamond
73.2%
Epoch AI · deepseek-v4-pro_none
Reasoning effort: none
Epoch AI evaluation
OTIS Mock AIME 2024-2025
95.6%
Epoch AI · deepseek-v4-pro_high
Reasoning effort: high
Epoch AI evaluation
OTIS Mock AIME 2024-2025
96.7%
Epoch AI · deepseek-v4-pro_max
Reasoning effort: max
Epoch AI evaluation
OTIS Mock AIME 2024-2025
46.7%
Epoch AI · deepseek-v4-pro_none
Reasoning effort: none
Epoch AI evaluation
SimpleQA Verified
47.0%
Epoch AI · deepseek-v4-pro_max
Reasoning effort: max
Epoch AI evaluation
SWE-Bench verified
77.6%
Epoch AI · deepseek-v4-pro_max
Reasoning effort: max
Epoch AI evaluation

Benchmark compilation: Epoch AI, Capabilities & benchmarking (CC BY attribution). Scores are converted to percentages and model names matched to the Vertical Tabs catalog. Individual evaluations are credited to their original sources. External results may carry separate licences and evaluation configurations; do not interpret scores from different harnesses as directly comparable.

Specifications

Developer
DeepSeek
Model family
DeepSeek
Type
Language model
Predecessor
—
Successor
—
Released
April 24, 2026
Model ID
deepseek/deepseek-v4-pro
Openness
Open weights
License
—
Parameters
1.7T
Architecture
deepseek4
Families
deepseek4
Input modalities
text
Output modalities
text
Modality
text->text
Native context
1.0M
Tokenizer
DeepSeek
Max output tokens
384K
Knowledge cutoff
2025-05
Source freshness
Metadata synced Oct 8, 2026, 10:17 PM UTC

Open-weight builds

Ollama variants

Every published Ollama tag matched to this model, including parameter editions, instruction/base variants, and quantized builds.

1 builds
VariantParametersTypeQuantizationSizeContextInput
deepseek-v4-pro:0813-cloud1.7Tcloud——1Mtext
Additional source evidence
Source model
deepseek/deepseek-v4-pro
Source family
deepseek-thinking
Last updated
2026-04-24
Knowledge cutoff
2025-05
Model context
1M
Model output limit
384K
Open weights
Yes
File attachments
No
Reasoning
Yes
Tool calling
Yes
Structured output
Yes
Temperature control
Yes

Downloadable weights

Published benchmarks

BenchmarkScoreEvaluation detailsEvidence
SWE-Bench Verified80.6 · resolved—Source
Artificial Analysis Coding Agent Index50.1 · average pass@1Claude Code · highSource
SWE-Atlas Codebase QnA67.8 · pass@1Claude Code · highSource
SWE-Bench Pro18 · pass@1Claude Code · hard-aa · highSource
Terminal-Bench64.7 · pass@1Claude Code · high · 2.1Source
MMLU-Pro87.5 · EMpreview checkpoint; max effortSource
SimpleQA-Verified57.9 · pass@1preview checkpoint; max effortSource
Chinese SimpleQA84.4 · pass@1preview checkpoint; max effortSource
GPQA Diamond90.1 · pass@1preview checkpoint; max effortSource
Humanity's Last Exam37.7 · pass@1preview checkpoint; max effort; without toolsSource
LiveCodeBench93.5 · pass@1preview checkpoint; max effortSource
Codeforces3206 · ratingpreview checkpoint; max effortSource
HMMT95.2 · pass@1February 2026 · preview checkpoint; max effortSource
IMOAnswerBench89.8 · pass@1preview checkpoint; max effortSource
MathArena Apex38.3 · pass@1preview checkpoint; max effortSource
MathArena Apex Shortlist90.2 · pass@1preview checkpoint; max effortSource
MRCR83.5 · MMR1M context · preview checkpoint; max effortSource
CorpusQA62 · accuracy1M context · preview checkpoint; max effortSource
Terminal-Bench67.9 · accuracypreview checkpoint; max effort · 2.0Source
SWE-Bench Pro55.4 · resolvedpreview checkpoint; max effortSource
SWE-Bench Multilingual76.2 · resolvedpreview checkpoint; max effortSource
BrowseComp83.4 · pass@1preview checkpoint; max effortSource
Humanity's Last Exam48.2 · pass@1preview checkpoint; max effort; with toolsSource
MCP Atlas73.6 · pass@1public · preview checkpoint; max effortSource
GDPval-AA1554 · Elopreview checkpoint; max effortSource
Toolathlon51.8 · pass@1preview checkpoint; max effortSource
Complete source record (JSON)
{
  "id": "deepseek/deepseek-v4-pro",
  "name": "DeepSeek V4 Pro",
  "description": "Open MoE flagship with million-token context for coding and long agent runs",
  "family": "deepseek-thinking",
  "last_updated": "2026-04-24",
  "knowledge": "2025-05",
  "attachment": false,
  "reasoning": true,
  "tool_call": true,
  "structured_output": true,
  "temperature": true,
  "modalities": {
    "input": [
      "text"
    ],
    "output": [
      "text"
    ]
  },
  "limit": {
    "context": 1000000,
    "output": 384000
  },
  "benchmarks": [
    {
      "name": "SWE-Bench Verified",
      "score": 80.6,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "resolved"
    },
    {
      "name": "Artificial Analysis Coding Agent Index",
      "score": 50.1,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "average pass@1",
      "harness": "Claude Code",
      "variant": "high"
    },
    {
      "name": "SWE-Atlas Codebase QnA",
      "score": 67.8,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "pass@1",
      "harness": "Claude Code",
      "variant": "high"
    },
    {
      "name": "SWE-Bench Pro",
      "score": 18,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "pass@1",
      "harness": "Claude Code",
      "variant": "high",
      "dataset": "hard-aa"
    },
    {
      "name": "Terminal-Bench",
      "score": 64.7,
      "source": "https://artificialanalysis.ai/agents/coding-agents",
      "metric": "pass@1",
      "harness": "Claude Code",
      "variant": "high",
      "version": "2.1"
    },
    {
      "name": "MMLU-Pro",
      "score": 87.5,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "EM",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "SimpleQA-Verified",
      "score": 57.9,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "Chinese SimpleQA",
      "score": 84.4,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "GPQA Diamond",
      "score": 90.1,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "Humanity's Last Exam",
      "score": 37.7,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort; without tools"
    },
    {
      "name": "LiveCodeBench",
      "score": 93.5,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "Codeforces",
      "score": 3206,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "rating",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "HMMT",
      "score": 95.2,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort",
      "dataset": "February 2026"
    },
    {
      "name": "IMOAnswerBench",
      "score": 89.8,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "MathArena Apex",
      "score": 38.3,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "MathArena Apex Shortlist",
      "score": 90.2,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "MRCR",
      "score": 83.5,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "MMR",
      "variant": "preview checkpoint; max effort",
      "dataset": "1M context"
    },
    {
      "name": "CorpusQA",
      "score": 62,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "accuracy",
      "variant": "preview checkpoint; max effort",
      "dataset": "1M context"
    },
    {
      "name": "Terminal-Bench",
      "score": 67.9,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "accuracy",
      "variant": "preview checkpoint; max effort",
      "version": "2.0"
    },
    {
      "name": "SWE-Bench Pro",
      "score": 55.4,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "resolved",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "SWE-Bench Multilingual",
      "score": 76.2,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "resolved",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "BrowseComp",
      "score": 83.4,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "Humanity's Last Exam",
      "score": 48.2,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort; with tools"
    },
    {
      "name": "MCP Atlas",
      "score": 73.6,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort",
      "dataset": "public"
    },
    {
      "name": "GDPval-AA",
      "score": 1554,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "Elo",
      "variant": "preview checkpoint; max effort"
    },
    {
      "name": "Toolathlon",
      "score": 51.8,
      "source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro",
      "metric": "pass@1",
      "variant": "preview checkpoint; max effort"
    }
  ],
  "release_date": "2026-04-24",
  "open_weights": true,
  "weights": [
    {
      "label": "Hugging Face",
      "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro"
    }
  ]
}

Infrastructure

Provider availability

All providers
ProviderEndpointContextInput /M tokensOutput /M tokensCached input /M tokensCache write /M tokensUptime 1dData handling
Baidubaidu/fp81.0M$0.44$0.88$0.04—99.79%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

StreamLakestreamlake/fp81.0M$0.44$0.89$0.04—98.96%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Parasailparasail/fp81.0M$0.45$3.48$0.10—95.38%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

GMICloudgmicloud/fp81.0M$0.96$1.91$0.08—99.93%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

DigitalOceandigitalocean1.0M$1.04$2.09$0.21—99.79%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Rekareka1.0M$1.05$2.10$0.21—97.92%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Cloudflarecloudflare1.0M$1.15$2.55$0.20—99.41%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

DeepInfradeepinfra/fp81.0M$1.30$2.60$0.10—100.00%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Alibabaalibaba/fp81M$1.42$2.83$0.12—99.21%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

SiliconFlowsiliconflow/fp81.0M$1.50$3.14$0.14—99.93%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Alibabaalibaba/fp8/us-east-11M$1.56$3.12$0.13—100.00%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Novitanovita/fp81.0M$1.60$3.20$0.14—88.96%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Venicevenice1M$1.65$3.30$0.33—97.75%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

AtlasCloudatlas-cloud/fp41.0M$1.68$3.38$0.13—97.92%
ZDR: No

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Azureazure/us1.0M$1.91$3.83$0.16—98.67%
ZDR: Yes

Training: Unknown

Prompt logging: Unknown

Retention: Unknown

Checked 2026-10-15

Provider data:OpenRouter

Deployment graph

Can I run this?

Vertical Tabs only shows compatibility when it has structured evidence tying this exact model to hardware, runtime, quantization, memory use, and observed performance.

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