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- Gemini 3.7 Flash vs. DeepSeek-V4.1-Flash
GoogleDeepSeekLLM matchup
Gemini 3.7 Flashvs.DeepSeek-V4.1-Flash
Which one is better?
Gemini 3.7 Flash performs better than DeepSeek-V4.1-Flash.
Gemini 3.7 Flash
Rank 16
DeepSeek-V4.1-Flash
Rank 29
Gemini 3.7 Flash
DeepSeek-V4.1-Flash
Gemini 3.7 Flash
DeepSeek-V4.1-Flash
Gemini 3.7 Flash
Rank 49 of 875
DeepSeek-V4.1-Flash
Rank 298 of 875
Choose Gemini 3.7 Flash for
Choose DeepSeek-V4.1-Flash for
On this page
Where is the difference?
Strengths at a glance
Gemini 3.7 FlashDeepSeek-V4.1-Flash
The median of all ranked models is below 100 in every area, so it sits in the centre of the net.
95 % range: Gemini 3.7 Flash 93.5 to 101.9, DeepSeek-V4.1-Flash 91.4 to 106.3.
The same values and verdicts as the bars below. In the top field the net starts at 100 points, the reference group average; values below sit as a hollow point in the centre. Not in the net because a model has no own value there or the data are too thin: Reasoning, Knowledge.
Gemini 3.7 Flash is ahead in 3 of 10 areas, DeepSeek-V4.1-Flash in none.
Gemini 3.7 Flash ahead: 3Gemini 3.7 Flash slightly ahead: 2level: 3too little data: 2
Bar length shows the gap in index points (full width 15 points, one standard deviation of the reference group). Solid means clearly ahead, hatched not certain yet, a thin grey bar level.
Show 3 more areas that do not count toward the overall index
Bar length shows the gap in index points (full width 15 points, one standard deviation of the reference group). Solid means clearly ahead, hatched not certain yet, a thin grey bar level.
Which model for which task?
Everyday tasks, translated from the area values above. Each row names the values it rests on.
See for yourself: same task, one attempt
The same prompt for both models. We show the latest attempt without fixes; it does not count toward the overall index.
Gemini 3.7 Flash
The response reached the token limit. No complete recording is available.
Oct 5, 2026 · 29 s · $0.03
Not yet visually reviewed. A successful recording does not confirm correct physics or full compliance with the prompt.
Test details
- Run date
- Oct 5, 2026
- API provider
- openrouter
- Requested API model
- google/gemini-3.7-flash
- Reasoning setting
- high
- Token limit including reasoning
- 8,192 tokens
- Output tokens
- 8,188 tokens
- Cost of the attempt
- $0.0307
- Response time
- 28.8 s
- API model reported in response
- google/gemini-3.7-flash
- Pinned endpoint
- Google AI Studio | google/gemini-3.7-flash-20260813
- Temperature
- Provider default
- Test protocol
- community-visual-tests-v1
- Technical checks
- Failed
Earlier attempts (3)
- Oct 2, 2026API request failedReasoning setting: high
- Oct 1, 2026API request failedReasoning setting: high
- Sep 7, 2026API request failedReasoning setting: high
DeepSeek-V4.1-Flash
The response reached the token limit. No complete recording is available.
Oct 5, 2026 · 26 s · $0.0049
Not yet visually reviewed. A successful recording does not confirm correct physics or full compliance with the prompt.
Test details
- Run date
- Oct 5, 2026
- API provider
- openrouter
- Requested API model
- deepseek/deepseek-v4.1-flash
- Reasoning setting
- high
- Token limit including reasoning
- 8,192 tokens
- Output tokens
- 8,191 tokens
- Cost of the attempt
- $0.0049
- Response time
- 25.8 s
- API model reported in response
- deepseek/deepseek-v4.1-flash
- Pinned endpoint
- DeepSeek | deepseek/deepseek-v4.1-flash-20260910
- Temperature
- Provider default
- Test protocol
- community-visual-tests-v1
- Technical checks
- Failed
Earlier attempts (2)
- Oct 2, 2026API request failedReasoning setting: high
- Oct 1, 2026API request failedReasoning setting: high
SVG short test
SVG short test
One SVG task with the same fixed settings for every model, without hidden thinking.
Prompt
Return only one standalone SVG of a pelican riding a bicycle. Use viewBox="0 0 800 600", simple shapes, two clearly visible wheels and a recognizable pelican with a long beak. At most 30 SVG elements and 1800 characters. No Markdown, explanations, comments, scripts, animation, CSS or external resources.
Gemini 3.7 Flash
Unavailable in this round
DeepSeek-V4.1-Flash

Oct 14, 2026 · $0.0001
Test details
- Test run
- Oct 14, 2026
- Provider
- decart/fp4
- API model
- deepseek/deepseek-v4.1-flash
- Output
- 590 tokens
- Reasoning
- API reports 0 reasoning tokens
- Cost of the attempt
- $0.0001
- Test round
- 43b8c5c46830
Gemini 3.7 Flash and DeepSeek-V4.1-Flash in the overall index
Every model with a place in the overall index, both models of this matchup highlighted. You can add or hide other models.
Overall index (Gradually Meta-Score v4)
20 of 91 models
4 models in this view are measured at a lower reasoning effort than max in the overall index. Dashed column: lower reasoning effort than the top.
Popularity compared
How often the models are searched for, used and mentioned, on a scale from 0 to 100.
Gemini 3.7 Flash is more popular than DeepSeek-V4.1-Flash: 57 to 38 out of 100.
Over time
Weekly values from October 18, 2026 to November 5, 2026
Gemini 3.7 FlashDeepSeek-V4.1-Flash
All data side by side
The better value is bold. For the overall index only when the gap is clear.
| Metric | Gemini 3.7 Flash | DeepSeek-V4.1-Flash |
|---|---|---|
| Intelligence | ||
| Overall indexpoints, 100 = reference group average, higher is better | 107.1 | 99.7 |
| Rank | Rank 16 of 91 | Rank 29 of 91 |
| Price per 1M tokens | ||
| Inputwhat you send | n/a | $0.15 |
| Outputwhat the model writes | n/a | $0.60 |
| Cost per task (own tests)average of 2 tests both passed | $0.042 | $0.008 |
| Speed | ||
| Tokens per second | n/a | 176 |
| Popularity | ||
| Popularitysearch, usage and mentions, 0 to 100 | 57Rank 49 of 875 | 38Rank 298 of 875 |
| Technical | ||
| Context windowhow much text the model reads at once | 1.05 M tokens≈ 1,570 A4 pages | 1 M tokens≈ 1,500 A4 pages |
| Knowledge cutoff | March 2026 | n/a |
| Released | Aug 13, 2026 | Sep 10, 2026 |
| Availability | Discontinued | Active |
| Open weights | no | yes |
- DeepSeek-V4.1-Flash: At peak times (Mon, Tue, Wed, Thu, Fri, 01:00-04:00 UTC; Mon, Tue, Wed, Thu, Fri, 06:00-10:00 UTC) the price is $0.30 input and $1.20 output per 1M tokens. The table shows the off-peak price.
Prices without caching or batch discounts · Page count as a rule of thumb from Artificial Analysis
Is there a better choice?
Overall index 106.5, rank 18. $0.75 input and $3.75 output per 1M tokens.
DeepSeek-V4.1-Flash vs. Gemini 3.8 FlashOverall index 106.6, rank 17. $0.15 input and $0.60 output per 1M tokens.
Gemini 3.7 Flash vs. DeepSeek V4.1 Flash 1017Overall index 126.1, rank 1. $4 input and $20 output per 1M tokens.
Gemini 3.7 Flash vs. Claude Opus 5.5Shared benchmarks
Single results from the same benchmark version, task and metric. A value is bold only with the same test setup and a clear gap.
A: Gemini 3.7 FlashB: DeepSeek-V4.1-Flash
Show 54 more benchmarks
More comparisons
Compare Gemini 3.7 Flash and DeepSeek-V4.1-Flash with the models people compare them with most often.
Compare another matchup
Predecessor and successor
- PredecessorGemini 3.7 Flash vs. Gemini 3.6 FlashPredecessor of Gemini 3.7 Flash
- SuccessorGemini 3.7 Flash vs. Gemini 3.8 FlashSuccessor of Gemini 3.7 Flash
- PredecessorDeepSeek-V4.1-Flash vs. DeepSeek-V4-FlashPredecessor of DeepSeek-V4.1-Flash
- SuccessorDeepSeek-V4.1-Flash vs. DeepSeek V4.1 Flash 1017Successor of DeepSeek-V4.1-Flash
The most popular comparisons
- 1Claude Opus 5.5 vs. DeepSeek-V4.1-Flash
- 2Gemini 3.8 Flash vs. DeepSeek-V4.1-Flash
- 3GPT-6 Luna vs. DeepSeek-V4.1-Flash
- 4Muse Spark 1.3 vs. DeepSeek-V4.1-Flash
- 5Claude Haiku 5.5 vs. DeepSeek-V4.1-Flash
- 6Claude Sonnet 5.5 vs. DeepSeek-V4.1-Flash
- 7GPT-6 Sol vs. DeepSeek-V4.1-Flash
- 8GPT-6 Astra vs. DeepSeek-V4.1-Flash
- 9Claude Sonnet 5 vs. DeepSeek-V4.1-Flash
Show all 50 comparisons
- 10Grok 4.7 vs. DeepSeek-V4.1-Flash
- 11Claude Opus 5 vs. DeepSeek-V4.1-Flash
- 12GPT-5.6 Terra vs. DeepSeek-V4.1-Flash
- 13DeepSeek-V4.1-Flash vs. GLM-5.3-Flash
- 14Claude Opus 4.6 vs. DeepSeek-V4.1-Flash
- 15Claude Sonnet 4.6 vs. DeepSeek-V4.1-Flash
- 16DeepSeek-V4.1-Flash vs. Qwen 3.8 Max 0902
- 17GPT-6.1 Sol vs. DeepSeek-V4.1-Flash
- 18DeepSeek-V4-Pro vs. DeepSeek-V4.1-Flash
- 19DeepSeek-V4.1-Flash vs. Mistral Large 4
- 20DeepSeek-V4.1-Flash vs. MiMo-V2.5-Pro
- 21Gemini 3.5 Flash-Lite vs. DeepSeek-V4.1-Flash
- 22Claude Haiku 4.5 vs. DeepSeek-V4.1-Flash
- 23Gemini 3.1 Pro Preview vs. DeepSeek-V4.1-Flash
- 24Gemini 3.7 Flash vs. Qwen 3.8 Max 0902
- 25Claude Haiku 5.5 vs. Gemini 3.7 Flash
- 26DeepSeek-V4.1-Flash vs. GLM-5.2
- 27Gemini 3.6 Flash vs. DeepSeek-V4.1-Flash
- 28GPT-5.6 Luna vs. Gemini 3.7 Flash
- 29DeepSeek-V4.1-Flash vs. GLM-5.3
- 30GPT-6 Luna vs. Gemini 3.7 Flash
- 31GPT-5.6 Sol vs. DeepSeek-V4.1-Flash
- 32Claude Opus 4.8 vs. DeepSeek-V4.1-Flash
- 33DeepSeek-V4.1-Flash vs. Kimi K3
- 34Claude Sonnet 5.5 vs. Gemini 3.7 Flash
- 35Gemini 3.7 Flash vs. DeepSeek-V4-Pro
- 36Grok 4.6 vs. DeepSeek-V4.1-Flash
- 37Gemini 3.7 Flash vs. Gemini 3.1 Pro Preview
- 38Claude Fable 5 vs. DeepSeek-V4.1-Flash
- 39GPT-5.6 Luna vs. DeepSeek-V4.1-Flash
- 40Gemini 3.7 Flash vs. Gemini 3.5 Flash-Lite
- 41Claude Opus 4.7 vs. DeepSeek-V4.1-Flash
- 42Claude Sonnet 4.5 vs. DeepSeek-V4.1-Flash
- 43Claude Opus 4.5 vs. DeepSeek-V4.1-Flash
- 44Claude Fable 5.1 vs. DeepSeek-V4.1-Flash
- 45DeepSeek-V4.1-Flash vs. Mistral Medium 3.5
- 46DeepSeek-V4.1-Flash vs. MiMo-V2.5
- 47DeepSeek-V4.1-Flash vs. GLM-5.1
- 48DeepSeek-V4.1-Flash vs. Mistral Large 3
- 49GPT-5.5 vs. DeepSeek-V4.1-Flash
- 50Muse Wonder Full vs. DeepSeek-V4.1-Flash