deepseek-v4-flash

deepseek-v4-flash

1,082 Downloads Updated 3 hours ago

DeepSeek-V4-Flash is a preview of the DeepSeek-V4 series, a Mixture-of-Experts model with 284B total parameters and 13B activated, built for efficient reasoning across a 1M-token context window.

tools thinking cloud

ollama run deepseek-v4-flash:cloud

curl http://localhost:11434/api/chat \
  -d '{
    "model": "deepseek-v4-flash:cloud",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='deepseek-v4-flash:cloud',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'deepseek-v4-flash:cloud',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Applications

Claude Code

Claude Code ollama launch claude --model deepseek-v4-flash:cloud

Codex

Codex ollama launch codex --model deepseek-v4-flash:cloud

OpenCode

OpenCode ollama launch opencode --model deepseek-v4-flash:cloud

OpenClaw

OpenClaw ollama launch openclaw --model deepseek-v4-flash:cloud

Models

Name

1 model

Size

Context

Input

deepseek-v4-flash:cloud

1M context window · Text · 3 hours ago

deepseek-v4-flash:cloud

-

1M

Text

Readme

DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

DeepSeek-V4-Flash is a preview of the DeepSeek-V4 series, a Mixture-of-Experts model with 284B total parameters and 13B activated, built for efficient reasoning across a 1M-token context window.

3 Thinking modes:

No thinking: used for fast, intuitive answers
Thinking: used for careful logical analysis
Max thinking: maximum reasoning effort on the hardest problems

Benchmark (Metric)	V4-Flash Non-Think	V4-Flash High	V4-Flash Max	V4-Pro Non-Think	V4-Pro High	V4-Pro Max
Knowledge & Reasoning
MMLU-Pro (EM)	83.0	86.4	86.2	82.9	87.1	87.5
SimpleQA-Verified (Pass@1)	23.1	28.9	34.1	45.0	46.2	57.9
Chinese-SimpleQA (Pass@1)	71.5	73.2	78.9	75.8	77.7	84.4
GPQA Diamond (Pass@1)	71.2	87.4	88.1	72.9	89.1	90.1
HLE (Pass@1)	8.1	29.4	34.8	7.7	34.5	37.7
LiveCodeBench (Pass@1)	55.2	88.4	91.6	56.8	89.8	93.5
Codeforces (Rating)	-	2816	3052	-	2919	3206
HMMT 2026 Feb (Pass@1)	40.8	91.9	94.8	31.7	94.0	95.2
IMOAnswerBench (Pass@1)	41.9	85.1	88.4	35.3	88.0	89.8
Apex (Pass@1)	1.0	19.1	33.0	0.4	27.4	38.3
Apex Shortlist (Pass@1)	9.3	72.1	85.7	9.2	85.5	90.2
Long Context
MRCR 1M (MMR)	37.5	76.9	78.7	44.7	83.3	83.5
CorpusQA 1M (ACC)	15.5	59.3	60.5	35.6	56.5	62.0
Agentic
Terminal Bench 2.0 (Acc)	49.1	56.6	56.9	59.1	63.3	67.9
SWE Verified (Resolved)	73.7	78.6	79.0	73.6	79.4	80.6
SWE Pro (Resolved)	49.1	52.3	52.6	52.1	54.4	55.4
SWE Multilingual (Resolved)	69.7	70.2	73.3	69.8	74.1	76.2
BrowseComp (Pass@1)	-	53.5	73.2	-	80.4	83.4
HLE w/ tools (Pass@1)	-	40.3	45.1	-	44.7	48.2
MCPAtlas (Pass@1)	64.0	67.4	69.0	69.4	74.2	73.6
GDPval-AA (Elo)	-	-	1395	-	-	1554
Toolathlon (Pass@1)	40.7	43.5	47.8	46.3	49.0	51.8

Reference

DeepSeek-V4 technical report

<img src="/assets/library/deepseek-v3/069ccc94-63b0-41e6-b2b3-e8e56068ab1a" width="320" />

DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

**DeepSeek-V4-Flash** is a preview of the DeepSeek-V4 series, a Mixture-of-Experts model with 284B total parameters and 13B activated, built for efficient reasoning across a 1M-token context window.

3 Thinking modes:

- No thinking: used for fast, intuitive answers 
- Thinking: used for careful logical analysis 
- Max thinking: maximum reasoning effort on the hardest problems 
![benchmark](/assets/library/deepseek-v4-flash/3252e416-59e1-4e1f-9a8d-4345b58ac28f)

| Benchmark (Metric) | V4-Flash Non-Think | V4-Flash High | V4-Flash Max | V4-Pro Non-Think | V4-Pro High | V4-Pro Max |
| :--- | :---: | :---: | :---: | :---: | :---: | :---: |
| **Knowledge & Reasoning** | | | | | | |
| MMLU-Pro (EM) | 83.0 | 86.4 | 86.2 | 82.9 | 87.1 | **87.5** |
| SimpleQA-Verified (Pass@1) | 23.1 | 28.9 | 34.1 | 45.0 | 46.2 | **57.9** |
| Chinese-SimpleQA (Pass@1) | 71.5 | 73.2 | 78.9 | 75.8 | 77.7 | **84.4** |
| GPQA Diamond (Pass@1) | 71.2 | 87.4 | 88.1 | 72.9 | 89.1 | **90.1** |
| HLE (Pass@1) | 8.1 | 29.4 | 34.8 | 7.7 | 34.5 | **37.7** |
| LiveCodeBench (Pass@1) | 55.2 | 88.4 | 91.6 | 56.8 | 89.8 | **93.5** |
| Codeforces (Rating) | - | 2816 | 3052 | - | 2919 | **3206** |
| HMMT 2026 Feb (Pass@1) | 40.8 | 91.9 | 94.8 | 31.7 | 94.0 | **95.2** |
| IMOAnswerBench (Pass@1) | 41.9 | 85.1 | 88.4 | 35.3 | 88.0 | **89.8** |
| Apex (Pass@1) | 1.0 | 19.1 | 33.0 | 0.4 | 27.4 | **38.3** |
| Apex Shortlist (Pass@1) | 9.3 | 72.1 | 85.7 | 9.2 | 85.5 | **90.2** |
| **Long Context** | | | | | | |
| MRCR 1M (MMR) | 37.5 | 76.9 | 78.7 | 44.7 | 83.3 | **83.5** |
| CorpusQA 1M (ACC) | 15.5 | 59.3 | 60.5 | 35.6 | 56.5 | **62.0** |
| **Agentic** | | | | | | |
| Terminal Bench 2.0 (Acc) | 49.1 | 56.6 | 56.9 | 59.1 | 63.3 | **67.9** |
| SWE Verified (Resolved) | 73.7 | 78.6 | 79.0 | 73.6 | 79.4 | **80.6** |
| SWE Pro (Resolved) | 49.1 | 52.3 | 52.6 | 52.1 | 54.4 | **55.4** |
| SWE Multilingual (Resolved) | 69.7 | 70.2 | 73.3 | 69.8 | 74.1 | **76.2** |
| BrowseComp (Pass@1) | - | 53.5 | 73.2 | - | 80.4 | **83.4** |
| HLE w/ tools (Pass@1) | - | 40.3 | 45.1 | - | 44.7 | **48.2** |
| MCPAtlas (Pass@1) | 64.0 | 67.4 | 69.0 | 69.4 | **74.2** | 73.6 |
| GDPval-AA (Elo) | - | - | 1395 | - | - | **1554** |
| Toolathlon (Pass@1) | 40.7 | 43.5 | 47.8 | 46.3 | 49.0 | **51.8** |

### Reference

[DeepSeek-V4 technical report](https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash/blob/main/DeepSeek_V4.pdf)

Paste, drop or click to upload images (.png, .jpeg, .jpg, .svg, .gif)