# DeepSeek V4 Pro Usage, Cost & Rank | OpenCode Data

> DeepSeek V4 Pro ranked #13 by tokens across OpenCode last week, with 1.9% of tokens over the past two months. DeepSeek V4 Pro costs $1.74 per 1M input tokens and $3.48 per 1M output tokens.

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

- Page: https://opencode.ai/data/deepseek/deepseek-v4-pro
- JSON: https://opencode.ai/data/deepseek/deepseek-v4-pro.json
- Model ID: deepseek/deepseek-v4-pro
- Lab: DeepSeek
- Updated: 2026-10-02T07:36:56.000Z

## Model facts

| Fact | Value |
| --- | --- |
| Context window | 1M |
| Max output | 384K |
| Knowledge cutoff | 2025-05 |
| Release date | 2026-04-24 |
| Input modalities | text |
| Output modalities | text |
| Reasoning | Yes |
| Tool calling | Yes |
| Open weights | Yes |
| Weights | [Hugging Face](https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro) |

## Pricing: USD per 1M tokens

| Input | Output | Cached input | Cache write |
| --- | --- | --- | --- |
| $1.74 | $3.48 | $0.20 | - |

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #13 |
| Tokens | 17T |
| Share of all tokens | 1.9% |
| Change vs previous 2 months | -42% |
| Unique users | 961K |
| Completed sessions | 1,443,418 |
| Average tokens per session | 12M |
| Average cost per session | $0.3111 |
| Total spend | $449,015 |
| Input tokens served from cache | 96.9% |
| Weekly retention | 56.1% |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-08-08 | 349B | 20K | 46,077 |
| 2026-08-09 | 329B | 19K | 44,855 |
| 2026-08-10 | 495B | 28K | 74,281 |
| 2026-08-11 | 546B | 41K | 34,150 |
| 2026-08-12 | 809B | 37K | 2,405 |
| 2026-08-13 | 1.8T | 48K | 3,016 |
| 2026-08-14 | 1.7T | 45K | 1,282 |
| 2026-08-15 | 1.5T | 36K | 567 |
| 2026-08-16 | 1.3T | 37K | 916 |
| 2026-08-17 | 807B | 44K | 250 |
| 2026-08-18 | 592B | 39K | 39,313 |
| 2026-08-19 | 486B | 34K | 42,987 |
| 2026-08-20 | 401B | 31K | 39,523 |
| 2026-08-21 | 342B | 29K | 33,315 |
| 2026-08-22 | 226B | 21K | 24,337 |
| 2026-08-23 | 215B | 16K | 20,185 |
| 2026-08-24 | 357B | 28K | 37,414 |
| 2026-08-25 | 359B | 27K | 42,999 |
| 2026-08-26 | 305B | 24K | 54,644 |
| 2026-08-27 | 269B | 21K | 23,857 |
| 2026-08-28 | 218B | 17K | 19,486 |
| 2026-08-29 | 170B | 12K | 13,568 |
| 2026-08-30 | 166B | 11K | 13,682 |
| 2026-08-31 | 230B | 17K | 20,201 |
| 2026-09-01 | 212B | 17K | 20,609 |
| 2026-09-02 | 175B | 16K | 19,634 |
| 2026-09-03 | 151B | 15K | 19,685 |
| 2026-09-04 | 108B | 13K | 18,139 |
| 2026-09-05 | 82B | 8.9K | 15,561 |
| 2026-09-06 | 85B | 8.8K | 16,822 |
| 2026-09-07 | 118B | 12K | 36,130 |
| 2026-09-08 | 109B | 11K | 34,848 |
| 2026-09-09 | 117B | 11K | 35,323 |
| 2026-09-10 | 126B | 12K | 37,289 |
| 2026-09-11 | 95B | 8.7K | 29,290 |
| 2026-09-12 | 78B | 6K | 22,739 |
| 2026-09-13 | 83B | 6K | 21,875 |
| 2026-09-14 | 119B | 9.3K | 31,253 |
| 2026-09-15 | 112B | 8.8K | 28,896 |
| 2026-09-16 | 109B | 8.5K | 28,832 |
| 2026-09-17 | 108B | 8.6K | 28,846 |
| 2026-09-18 | 104B | 7.6K | 27,458 |
| 2026-09-19 | 91B | 6.7K | 24,858 |
| 2026-09-20 | 94B | 6.9K | 22,236 |
| 2026-09-21 | 120B | 9.6K | 30,548 |
| 2026-09-22 | 114B | 8.2K | 42,684 |
| 2026-09-23 | 95B | 7.4K | 25,995 |
| 2026-09-24 | 86B | 6.8K | 24,076 |
| 2026-09-25 | 76B | 5.8K | 20,961 |
| 2026-09-26 | 62B | 4.9K | 16,914 |
| 2026-09-27 | 63B | 4.8K | 16,915 |
| 2026-09-28 | 86B | 7.1K | 27,812 |
| 2026-09-29 | 82B | 7K | 27,907 |
| 2026-09-30 | 80B | 6.5K | 30,057 |
| 2026-10-01 | 74B | 5.7K | 20,328 |
| 2026-10-02 | 16B | 2.1K | 5,588 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | China | 3.9T | 23.1% |
| 2 | United States | 2.1T | 12.2% |
| 3 | Brazil | 820B | 4.8% |
| 4 | Japan | 688B | 4% |
| 5 | Germany | 602B | 3.5% |
| 6 | Hong Kong | 505B | 3% |
| 7 | Singapore | 468B | 2.7% |
| 8 | India | 438B | 2.6% |
| 9 | Spain | 426B | 2.5% |
| 10 | Indonesia | 388B | 2.3% |
| 11 | France | 352B | 2.1% |
| 12 | Russia | 336B | 2% |
| 13 | United Kingdom | 300B | 1.8% |
| 14 | Colombia | 291B | 1.7% |
| 15 | Argentina | 277B | 1.6% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 9 | [mimo-v2.5](https://opencode.ai/data/xiaomi/mimo-v2-5.md) | Xiaomi | 788B |
| 10 | [muse-spark-1.2-contributor](https://opencode.ai/data/meta/muse-spark-1-2-contributor.md) | Meta | 733B |
| 11 | [deepseek-v4-flash-vision-exp](https://opencode.ai/data/deepseek/deepseek-v4-flash-vision-exp.md) | DeepSeek | 684B |
| 12 | [gpt-6-luna](https://opencode.ai/data/openai/gpt-6-luna.md) | OpenAI | 638B |
| 13 | [deepseek-v4-pro](https://opencode.ai/data/deepseek/deepseek-v4-pro.md) | DeepSeek | 462B |
| 14 | [mimo-v2.6-pro](https://opencode.ai/data/xiaomi/mimo-v2-6-pro.md) | Xiaomi | 461B |
| 15 | [nemotron-3.5-lightning](https://opencode.ai/data/nvidia/nemotron-3-5-lightning.md) | NVIDIA | 264B |
| 16 | [ling-3.0-flash-fin](https://opencode.ai/data/inclusionai/ling-3-0-flash-fin.md) | inclusionAI | 256B |
| 17 | [qwen3.8-flash](https://opencode.ai/data/alibaba/qwen3-8-flash.md) | Qwen | 254B |
| 18 | [gpt-5.6-luna](https://opencode.ai/data/openai/gpt-5-6-luna.md) | OpenAI | 194B |

## Benchmarks

| Benchmark | Score | Metric | Source |
| --- | --- | --- | --- |
| SWE-Bench Verified | 80.6 | resolved | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| Artificial Analysis Coding Agent Index | 50.1 | average pass@1 | https://artificialanalysis.ai/agents/coding-agents |
| SWE-Atlas Codebase QnA | 67.8 | pass@1 | https://artificialanalysis.ai/agents/coding-agents |
| SWE-Bench Pro | 18 | pass@1 | https://artificialanalysis.ai/agents/coding-agents |
| Terminal-Bench | 64.7 | pass@1 | https://artificialanalysis.ai/agents/coding-agents |
| MMLU-Pro | 87.5 | EM | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| SimpleQA-Verified | 57.9 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| Chinese SimpleQA | 84.4 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| GPQA Diamond | 90.1 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| Humanity's Last Exam | 37.7 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| LiveCodeBench | 93.5 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| Codeforces | 3206 | rating | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| HMMT | 95.2 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| IMOAnswerBench | 89.8 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| MathArena Apex | 38.3 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| MathArena Apex Shortlist | 90.2 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| MRCR | 83.5 | MMR | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| CorpusQA | 62 | accuracy | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| Terminal-Bench | 67.9 | accuracy | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| SWE-Bench Pro | 55.4 | resolved | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| SWE-Bench Multilingual | 76.2 | resolved | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| BrowseComp | 83.4 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| Humanity's Last Exam | 48.2 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| MCP Atlas | 73.6 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| GDPval-AA | 1554 | Elo | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |
| Toolathlon | 51.8 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro |

## Methodology

- Updates: Aggregated every hour. Days and weeks use UTC.
- Tokens: Input, output, reasoning, and cached tokens for each request.
- Users and sessions: Approximate counts of distinct users and OpenCode sessions.
- Cost: Session cost is the average cost per OpenCode session. Token prices are list prices from the OpenCode model catalog.
- Retention: The share of a model's users in one week who use it again the next week.
- Citation: Cite OpenCode Data (opencode.ai/data) with the update time shown at the top of the page.