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- Gemini 3.5 Flash-Lite vs. DeepSeek-V4.1-Flash
GoogleDeepSeekLLM matchup
Gemini 3.5 Flash-Litevs.DeepSeek-V4.1-Flash
Which one is better?
DeepSeek-V4.1-Flash performs better than Gemini 3.5 Flash-Lite and is cheaper: Gemini 3.5 Flash-Lite costs 2 times (input) and 4.2 times (output) as much.
Gemini 3.5 Flash-Lite
Rank 57
DeepSeek-V4.1-Flash
Rank 29
Gemini 3.5 Flash-Lite
DeepSeek-V4.1-Flash
Gemini 3.5 Flash-Lite
DeepSeek-V4.1-Flash
Gemini 3.5 Flash-Lite
Rank 221 of 876
DeepSeek-V4.1-Flash
Rank 312 of 876
Choose Gemini 3.5 Flash-Lite for
No clear advantage
Choose DeepSeek-V4.1-Flash for
On this page
Where is the difference?
Strengths at a glance
Gemini 3.5 Flash-LiteDeepSeek-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 3.5 Flash-Lite 64.2 to 76.0, 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, Mathematics, Knowledge.
DeepSeek-V4.1-Flash is ahead in 7 of 10 areas, Gemini 3.5 Flash-Lite in none.
too little data: 3DeepSeek-V4.1-Flash ahead: 7
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 3.5 Flash-Lite

Oct 2, 2026 · 14 s · $0.01
Test details
- Run date
- Oct 2, 2026
- API provider
- openrouter
- Requested API model
- google/gemini-3.5-flash-lite
- Reasoning setting
- high
- Token limit including reasoning
- 8,192 tokens
- Output tokens
- 5,414 tokens
- Cost of the attempt
- $0.0135
- Response time
- 14.3 s
- API model reported in response
- google/gemini-3.5-flash-lite
- Pinned endpoint
- Google AI Studio | google/gemini-3.5-flash-lite-20260721
- Temperature
- Provider default
- Test protocol
- community-visual-tests-v1
- Technical checks
- Passed, not a quality rating
Visually reviewed. This individual test does not establish overall model quality.
Earlier attempts (2)
- 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 3.5 Flash-Lite
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 3.5 Flash-Lite 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
5 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 3.5 Flash-Lite is more popular than DeepSeek-V4.1-Flash: 43 to 38 out of 100.
Over time
Weekly values from October 18, 2026 to November 6, 2026
Gemini 3.5 Flash-LiteDeepSeek-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 3.5 Flash-Lite | DeepSeek-V4.1-Flash |
|---|---|---|
| Intelligence | ||
| Overall indexpoints, 100 = reference group average, higher is better | 73.6 | 99.7 |
| Rank | Rank 57 of 91 | Rank 29 of 91 |
| Price per 1M tokens | ||
| Inputwhat you send | $0.30 | $0.15 |
| Outputwhat the model writes | $2.50 | $0.60 |
| Cost per task (own tests)average of 2 tests both passed | $0.026 | $0.008 |
| Speed | ||
| Tokens per second | 299 | 176 |
| Popularity | ||
| Popularitysearch, usage and mentions, 0 to 100 | 43Rank 221 of 876 | 38Rank 312 of 876 |
| 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 | n/a | n/a |
| Released | Jul 21, 2026 | Sep 10, 2026 |
| Availability | Active | 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 106.6, rank 17. $0.15 input and $0.60 output per 1M tokens.
Gemini 3.5 Flash-Lite vs. DeepSeek V4.1 Flash 1017Overall index 103.4, rank 20. $0.10 input and $0.50 output per 1M tokens.
DeepSeek-V4.1-Flash vs. Claude Haiku 5.5Overall index 126.1, rank 1. $4 input and $20 output per 1M tokens.
DeepSeek-V4.1-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 3.5 Flash-LiteB: DeepSeek-V4.1-Flash
Show 54 more benchmarks
More comparisons
Compare Gemini 3.5 Flash-Lite and DeepSeek-V4.1-Flash with the models people compare them with most often.
Compare another matchup
Predecessor and successor
The most popular comparisons
- 1Gemini 3.8 Flash vs. DeepSeek-V4.1-Flash
- 2Muse Spark 1.3 vs. DeepSeek-V4.1-Flash
- 3Claude Sonnet 5.5 vs. DeepSeek-V4.1-Flash
- 4Claude Opus 5.5 vs. DeepSeek-V4.1-Flash
- 5GPT-6 Luna vs. DeepSeek-V4.1-Flash
- 6GPT-6 Sol vs. DeepSeek-V4.1-Flash
- 7Claude Haiku 5.5 vs. DeepSeek-V4.1-Flash
- 8Gemini 3.8 Flash vs. Gemini 3.5 Flash-Lite
- 9GPT-6 Astra vs. DeepSeek-V4.1-Flash
Show all 55 comparisons
- 10Grok 4.7 vs. DeepSeek-V4.1-Flash
- 11Claude Sonnet 5 vs. DeepSeek-V4.1-Flash
- 12Claude Haiku 5.5 vs. Gemini 3.5 Flash-Lite
- 13GPT-6 Luna vs. Gemini 3.5 Flash-Lite
- 14GPT-5.6 Terra vs. DeepSeek-V4.1-Flash
- 15DeepSeek-V4.1-Flash vs. Qwen 3.8 Max 0902
- 16Claude Opus 5 vs. DeepSeek-V4.1-Flash
- 17Claude Opus 4.6 vs. DeepSeek-V4.1-Flash
- 18DeepSeek-V4.1-Flash vs. GLM-5.3-Flash
- 19Claude Sonnet 4.6 vs. DeepSeek-V4.1-Flash
- 20DeepSeek-V4.1-Flash vs. Mistral Large 4
- 21DeepSeek-V4-Pro vs. DeepSeek-V4.1-Flash
- 22DeepSeek-V4.1-Flash vs. GLM-5.2
- 23Claude Sonnet 5.5 vs. Gemini 3.5 Flash-Lite
- 24GPT-6.1 Sol vs. DeepSeek-V4.1-Flash
- 25Gemini 3.1 Pro Preview vs. DeepSeek-V4.1-Flash
- 26DeepSeek-V4.1-Flash vs. MiMo-V2.5-Pro
- 27DeepSeek-V4.1-Flash vs. GLM-5.3
- 28Gemini 3.6 Flash vs. DeepSeek-V4.1-Flash
- 29Claude Opus 4.8 vs. DeepSeek-V4.1-Flash
- 30Claude Haiku 4.5 vs. DeepSeek-V4.1-Flash
- 31DeepSeek-V4.1-Flash vs. Kimi K3
- 32GPT-5.6 Sol vs. DeepSeek-V4.1-Flash
- 33Gemini 4 Argon vs. Gemini 3.5 Flash-Lite
- 34Claude Fable 5 vs. DeepSeek-V4.1-Flash
- 35GPT-5.6 Luna vs. DeepSeek-V4.1-Flash
- 36Gemini 4 Argon vs. DeepSeek-V4.1-Flash
- 37DeepSeek-V4.1-Flash vs. Qwen 3.8 27B
- 38Gemini 3.5 Flash-Lite vs. Qwen 3.8 27B
- 39Grok 4.6 vs. DeepSeek-V4.1-Flash
- 40Gemini 3.5 Flash-Lite vs. Qwen 3.8 Max 0902
- 41Gemini 3.7 Flash vs. Gemini 3.5 Flash-Lite
- 42DeepSeek-V4.1-Flash vs. Mistral Medium 3.5
- 43DeepSeek-V4.1-Flash vs. MiMo-V2.5
- 44Gemini 3.5 Flash-Lite vs. GLM-5.3
- 45Claude Sonnet 4.5 vs. DeepSeek-V4.1-Flash
- 46Claude Fable 5.1 vs. DeepSeek-V4.1-Flash
- 47Claude Opus 4.5 vs. DeepSeek-V4.1-Flash
- 48Claude Opus 4.7 vs. DeepSeek-V4.1-Flash
- 49DeepSeek-V4.1-Flash vs. GLM-5.1
- 50Claude Haiku 4.5 vs. Gemini 3.5 Flash-Lite
- 51DeepSeek-V4.1-Flash vs. Mistral Large 3
- 52Gemini 3.5 Flash vs. DeepSeek-V4.1-Flash
- 53GPT-6.1 Terra vs. DeepSeek-V4.1-Flash
- 54Muse Wonder vs. DeepSeek-V4.1-Flash
- 55DeepSeek-V4.1-Flash vs. Kimi K3.1 Pro