DeepSeek V4 Pro 0813

DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes
- Context
- 1.0M
- Released
- 2mo ago
- Parameters
- —
- Input / 1M tokens
- $0.66
- Output / 1M tokens
- $1.98
- Cached input / 1M tokens
- $0.02
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.
Not evaluated in DeepSWE 1.1 as of 2026-09-22. Results are only shown for exact model versions in the official dataset. Official leaderboard.
Other published benchmarks
| Evaluation | Reported score and source |
|---|---|
| ARC-AGI-2 | 59.7% Third-party evaluator · deepseek-v4-pro-0813_high Reasoning effort: high External evaluation via Epoch AIOriginal-source terms apply |
| ARC-AGI-2 | 56.3% Third-party evaluator · deepseek-v4-pro-0813_low Reasoning effort: low External evaluation via Epoch AIOriginal-source terms apply |
| ARC-AGI-2 | 61.3% Third-party evaluator · deepseek-v4-pro-0813_max Reasoning effort: max External evaluation via Epoch AIOriginal-source terms apply |
| ARC-AGI-2 | 0.8% Third-party evaluator · deepseek-v4-pro-0813_none Reasoning effort: none External evaluation via Epoch AIOriginal-source terms apply |
| FrontierMath-Tier-4-v2-Private | |
| FrontierMath-Tiers-1-3-v2-Private | |
| GPQA diamond | |
| OTIS Mock AIME 2024-2025 | |
| SimpleQA Verified |
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
- August 12, 2026
- Model ID
deepseek/deepseek-v4-pro-0813- Openness
- Open weights
- License
- MIT
- Parameters
- —
- Input modalities
- text
- Output modalities
- text
- Modality
- text->text
- Tokenizer
- DeepSeek
- Max output tokens
- 393K
- Hugging Face
- deepseek-ai/DeepSeek-V4-Pro-0813
- Source freshness
- Metadata synced Oct 8, 2026, 10:17 PM UTC
Additional source evidence
- Source model
- deepseek/deepseek-v4-pro-0813
- Source family
- deepseek-thinking
- Last updated
- 2026-08-22
- 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
| Benchmark | Score | Evaluation details | Evidence |
|---|---|---|---|
| Humanity's Last Exam | 42.7 · score | without tools | Source |
| Humanity's Last Exam | 60 · score | with tools | Source |
| Terminal-Bench | 87.9 · score | DeepSeek Harness minimal mode · max effort · 2.1 | Source |
| NL2Repo | 61.5 · score | DeepSeek Harness minimal mode · max effort | Source |
| CyberGym | 83.3 · score | DeepSeek Harness minimal mode · max effort | Source |
| DeepSWE | 62.7 · score | DeepSeek Harness minimal mode · max effort | Source |
| Toolathlon-Verified | 74.1 · score | — | Source |
| Agents' Last Exam | 25.7 · score | — | Source |
| AutomationBench | 31.8 · score | public | Source |
| DSBench-FullStack | 71.1 · score | internal | Source |
| DSBench-Hard | 67.2 · score | internal | Source |
Complete source record (JSON)
{
"id": "deepseek/deepseek-v4-pro-0813",
"name": "DeepSeek V4 Pro 0813",
"description": "DeepSeek V4 Pro snapshot with million-token context and support for thinking and non-thinking modes",
"family": "deepseek-thinking",
"last_updated": "2026-08-22",
"attachment": false,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"temperature": true,
"modalities": {
"input": [
"text"
],
"output": [
"text"
]
},
"limit": {
"context": 1000000,
"output": 384000
},
"benchmarks": [
{
"name": "Humanity's Last Exam",
"score": 42.7,
"source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813",
"metric": "score",
"variant": "without tools"
},
{
"name": "Humanity's Last Exam",
"score": 60,
"source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813",
"metric": "score",
"variant": "with tools"
},
{
"name": "Terminal-Bench",
"score": 87.9,
"source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813",
"metric": "score",
"harness": "DeepSeek Harness minimal mode",
"variant": "max effort",
"version": "2.1"
},
{
"name": "NL2Repo",
"score": 61.5,
"source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813",
"metric": "score",
"harness": "DeepSeek Harness minimal mode",
"variant": "max effort"
},
{
"name": "CyberGym",
"score": 83.3,
"source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813",
"metric": "score",
"harness": "DeepSeek Harness minimal mode",
"variant": "max effort"
},
{
"name": "DeepSWE",
"score": 62.7,
"source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813",
"metric": "score",
"harness": "DeepSeek Harness minimal mode",
"variant": "max effort"
},
{
"name": "Toolathlon-Verified",
"score": 74.1,
"source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813",
"metric": "score"
},
{
"name": "Agents' Last Exam",
"score": 25.7,
"source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813",
"metric": "score"
},
{
"name": "AutomationBench",
"score": 31.8,
"source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813",
"metric": "score",
"dataset": "public"
},
{
"name": "DSBench-FullStack",
"score": 71.1,
"source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813",
"metric": "score",
"dataset": "internal"
},
{
"name": "DSBench-Hard",
"score": 67.2,
"source": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813",
"metric": "score",
"dataset": "internal"
}
],
"release_date": "2026-08-12",
"open_weights": true,
"license": "MIT",
"weights": [
{
"label": "Hugging Face",
"url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813"
}
]
}Infrastructure
Provider availability
| Provider | Endpoint | Context | Input /M tokens | Output /M tokens | Cached input /M tokens | Cache write /M tokens | Uptime 1d | Data handling |
|---|---|---|---|---|---|---|---|---|
| relace/fp4 | 1.0M | $0.22 | $8.00 | $0.23 | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| wafer | 1.0M | $0.25 | $5.00 | $0.25 | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| ionstream | 1.0M | $0.37 | $2.93 | $0.09 | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| deepseek | 1.0M | $0.66 | $1.98 | $0.02 | — | 83.13% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| streamlake | 1.0M | $0.66 | $1.98 | $0.02 | — | 99.86% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| sail-research/us | 1.0M | $0.90 | $0.99 | $0.19 | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| sail-research/fp4 | 1.0M | $0.90 | $0.99 | $0.19 | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| phala | 1.0M | $0.96 | $2.88 | $0.10 | — | 99.90% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| novita/fp8 | 1.0M | $0.99 | $2.97 | $0.03 | — | 88.18% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| gmicloud/fp8 | 1.0M | $1.06 | $3.17 | $0.04 | — | 98.31% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| alibaba | 1M | $1.12 | $3.37 | $0.11 | — | 97.48% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| deepinfra/fp8 | 1.0M | $1.30 | $2.60 | $0.10 | — | 99.64% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| coreweave/fp8 | 1.0M | $1.31 | $3.96 | $0.04 | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| alibaba/us-east-1 | 1M | $1.32 | $3.96 | $0.13 | — | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| atlas-cloud/fp8 | 1.0M | $1.32 | $3.96 | $0.13 | — | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| baidu/fp8 | 1.0M | $1.32 | $3.96 | $0.04 | — | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| cloudflare | 1.0M | $1.32 | $3.96 | $0.04 | — | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| digitalocean | 1.0M | $1.32 | $3.96 | $0.04 | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| parasail/fp8 | 1.0M | $1.32 | $3.96 | $0.04 | — | 99.93% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| siliconflow/fp8 | 1.0M | $1.32 | $3.96 | $0.04 | — | 99.88% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| together | 1.0M | $1.32 | $3.96 | $0.13 | — | 91.92% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| venice | 1M | $1.65 | $4.95 | $0.17 | — | 93.75% | ZDR: YesTraining: 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.