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

> DeepSeek V4 Flash ranked #5 by tokens across OpenCode last week, with 30% of tokens over the past two months. DeepSeek V4 Flash costs $0.30 per 1M input tokens and $1.20 per 1M output tokens.

Fast DeepSeek V4 lane for economical reasoning, coding, and long-context work

- Page: https://opencode.ai/data/deepseek/deepseek-v4-flash
- JSON: https://opencode.ai/data/deepseek/deepseek-v4-flash.json
- Model ID: deepseek/deepseek-v4-flash
- Lab: DeepSeek
- Updated: 2026-10-02T08:39:37.000Z

## 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-Flash) |

## Pricing: USD per 1M tokens

| Input | Output | Cached input | Cache write |
| --- | --- | --- | --- |
| $0.30 | $1.20 | $0.0060 | $0.30 |

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | #5 |
| Tokens | 271T |
| Share of all tokens | 30% |
| Change vs previous 2 months | +110% |
| Unique users | 4.2M |
| Completed sessions | 36,931,115 |
| Average tokens per session | 7.3M |
| Average cost per session | $0.0475 |
| Total spend | $1,755,066 |
| Input tokens served from cache | 94.9% |
| Weekly retention | 65.3% |

## Daily usage: past 2 months

| Date | Tokens | Unique users | Sessions |
| --- | --- | --- | --- |
| 2026-08-08 | 8.2T | 59K | 447,815 |
| 2026-08-09 | 8.3T | 60K | 476,670 |
| 2026-08-10 | 9T | 80K | 548,010 |
| 2026-08-11 | 14T | 190K | 305,429 |
| 2026-08-12 | 17T | 172K | 16,791 |
| 2026-08-13 | 18T | 169K | 8,918 |
| 2026-08-14 | 18T | 167K | 5,380 |
| 2026-08-15 | 17T | 145K | 3,028 |
| 2026-08-16 | 15T | 143K | 6,355 |
| 2026-08-17 | 9.4T | 167K | 5,836 |
| 2026-08-18 | 9T | 158K | 2,160,804 |
| 2026-08-19 | 7.6T | 159K | 2,589,230 |
| 2026-08-20 | 6.9T | 147K | 2,296,278 |
| 2026-08-21 | 3T | 85K | 383,342 |
| 2026-08-22 | 2.2T | 65K | 380,660 |
| 2026-08-23 | 2.1T | 54K | 247,784 |
| 2026-08-24 | 3.2T | 87K | 383,224 |
| 2026-08-25 | 3.1T | 83K | 314,803 |
| 2026-08-26 | 3T | 79K | 324,813 |
| 2026-08-27 | 3.9T | 92K | 572,846 |
| 2026-08-28 | 4T | 89K | 694,233 |
| 2026-08-29 | 3.5T | 69K | 714,067 |
| 2026-08-30 | 3.5T | 67K | 784,701 |
| 2026-08-31 | 4.2T | 89K | 639,804 |
| 2026-09-01 | 4.2T | 89K | 653,308 |
| 2026-09-02 | 4T | 84K | 784,495 |
| 2026-09-03 | 3.8T | 82K | 653,743 |
| 2026-09-04 | 3.3T | 74K | 602,577 |
| 2026-09-05 | 3T | 59K | 717,173 |
| 2026-09-06 | 2.9T | 57K | 734,816 |
| 2026-09-07 | 3.5T | 72K | 908,280 |
| 2026-09-08 | 3.6T | 70K | 978,525 |
| 2026-09-09 | 3.4T | 67K | 916,133 |
| 2026-09-10 | 3.2T | 67K | 846,231 |
| 2026-09-11 | 2.7T | 59K | 931,723 |
| 2026-09-12 | 2.6T | 45K | 1,208,306 |
| 2026-09-13 | 2.6T | 43K | 1,170,288 |
| 2026-09-14 | 2.9T | 57K | 1,094,820 |
| 2026-09-15 | 2.9T | 55K | 1,084,985 |
| 2026-09-16 | 2.8T | 54K | 1,096,738 |
| 2026-09-17 | 2.5T | 51K | 911,289 |
| 2026-09-18 | 2.6T | 48K | 858,004 |
| 2026-09-19 | 2.2T | 36K | 832,581 |
| 2026-09-20 | 2.3T | 34K | 853,647 |
| 2026-09-21 | 2.7T | 52K | 922,078 |
| 2026-09-22 | 2.8T | 48K | 798,024 |
| 2026-09-23 | 2.7T | 45K | 754,178 |
| 2026-09-24 | 2.6T | 44K | 817,855 |
| 2026-09-25 | 1.6T | 29K | 361,963 |
| 2026-09-26 | 822B | 18K | 139,530 |
| 2026-09-27 | 679B | 17K | 123,366 |
| 2026-09-28 | 1.3T | 27K | 211,598 |
| 2026-09-29 | 1.1T | 25K | 220,379 |
| 2026-09-30 | 945B | 24K | 228,622 |
| 2026-10-01 | 643B | 17K | 156,002 |
| 2026-10-02 | 191B | 8.2K | 49,037 |

## Top countries: past 2 months

| Rank | Country | Tokens | Share |
| --- | --- | --- | --- |
| 1 | China | 68T | 25% |
| 2 | United States | 32T | 11.9% |
| 3 | India | 13T | 4.8% |
| 4 | Japan | 11T | 3.9% |
| 5 | Brazil | 10T | 3.8% |
| 6 | Hong Kong | 9.3T | 3.4% |
| 7 | Germany | 8.2T | 3% |
| 8 | Singapore | 7.9T | 2.9% |
| 9 | Indonesia | 7.2T | 2.7% |
| 10 | Russia | 7.1T | 2.6% |
| 11 | France | 4.7T | 1.7% |
| 12 | Spain | 4.5T | 1.7% |
| 13 | Vietnam | 3.9T | 1.4% |
| 14 | United Kingdom | 3.6T | 1.3% |
| 15 | Netherlands | 3.6T | 1.3% |

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 1 | [space-bunny](https://opencode.ai/data/unknown/space-bunny.md) | - | 57T |
| 2 | [deepseek-v4.1-flash](https://opencode.ai/data/deepseek/deepseek-v4-1-flash.md) | DeepSeek | 33T |
| 3 | [muse-spark-1.3-contributor](https://opencode.ai/data/meta/muse-spark-1-3-contributor.md) | Meta | 31T |
| 4 | [mimo-v2.6-flash](https://opencode.ai/data/xiaomi/mimo-v2-6-flash.md) | Xiaomi | 8.8T |
| 5 | [deepseek-v4-flash](https://opencode.ai/data/deepseek/deepseek-v4-flash.md) | DeepSeek | 5.7T |
| 6 | [nemotron-3-ultra](https://opencode.ai/data/nvidia/nemotron-3-ultra.md) | NVIDIA | 3.6T |
| 7 | [longcat-2.5-preview](https://opencode.ai/data/meituan/longcat-2-5-preview.md) | Meituan | 2.6T |
| 8 | [glm-5.3-flash](https://opencode.ai/data/zhipuai/glm-5-3-flash.md) | Zhipu | 2.1T |
| 9 | [mimo-v2.5](https://opencode.ai/data/xiaomi/mimo-v2-5.md) | Xiaomi | 794B |
| 10 | [muse-spark-1.2-contributor](https://opencode.ai/data/meta/muse-spark-1-2-contributor.md) | Meta | 738B |

## Benchmarks

| Benchmark | Score | Metric | Source |
| --- | --- | --- | --- |
| SWE-Bench Verified | 79 | resolved | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| MMLU-Pro | 86.2 | EM | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| SimpleQA-Verified | 34.1 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| Chinese SimpleQA | 78.9 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| GPQA Diamond | 88.1 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| Humanity's Last Exam | 34.8 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| LiveCodeBench | 91.6 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| Codeforces | 3052 | rating | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| HMMT | 94.8 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| IMOAnswerBench | 88.4 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| MathArena Apex | 33 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| MathArena Apex Shortlist | 85.7 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| MRCR | 78.7 | MMR | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| CorpusQA | 60.5 | accuracy | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| Terminal-Bench | 56.9 | accuracy | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| SWE-Bench Pro | 52.6 | resolved | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| SWE-Bench Multilingual | 73.3 | resolved | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| BrowseComp | 73.2 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| Humanity's Last Exam | 45.1 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| MCP Atlas | 69 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| GDPval-AA | 1395 | Elo | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |
| Toolathlon | 47.8 | pass@1 | https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash |

## 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.