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- GPT-5.5 vs. DeepSeek-V4.1-Flash
OpenAIDeepSeekLLM matchup
GPT-5.5vs.DeepSeek-V4.1-Flash
Which one is better?
GPT-5.5 and DeepSeek-V4.1-Flash perform about equally well, but GPT-5.5 costs 33.3 times (input) and 50 times (output) as much.
GPT-5.5
Rank 24
DeepSeek-V4.1-Flash
Rank 29
GPT-5.5
DeepSeek-V4.1-Flash
GPT-5.5
DeepSeek-V4.1-Flash
GPT-5.5
Rank 458 of 876
DeepSeek-V4.1-Flash
Rank 312 of 876
Above 272,000 tokens of context, GPT-5.5 costs more: $10 input and $45 output per 1M tokens.
Choose GPT-5.5 for
Choose DeepSeek-V4.1-Flash for
On this page
Where is the difference?
Strengths at a glance
GPT-5.5DeepSeek-V4.1-FlashMedian of all ranked models
95 % range: GPT-5.5 87.7 to 102.8, DeepSeek-V4.1-Flash 91.4 to 106.3.
The same values and verdicts as the bars below. In the close-up the net starts at 90 points, just below the weaker model's lowest value; the reference group average is 100. Not in the net because a model has no own value there or the data are too thin: Reasoning, Mathematics, Knowledge.
GPT-5.5 is ahead in 1 of 10 areas, DeepSeek-V4.1-Flash in none.
GPT-5.5 ahead: 1GPT-5.5 slightly ahead: 2level: 1too little data: 3DeepSeek-V4.1-Flash slightly ahead: 3
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 4 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.
GPT-5.5

Oct 1, 2026 · 26 s · $0.09
Test details
- Run date
- Oct 1, 2026
- API provider
- openrouter
- Requested API model
- openai/gpt-5.5
- Reasoning setting
- high
- Token limit including reasoning
- 8,192 tokens
- Output tokens
- 3,163 tokens
- Cost of the attempt
- $0.0950
- Response time
- 25.9 s
- API model reported in response
- openai/gpt-5.5
- Pinned endpoint
- OpenAI | openai/gpt-5.5-20260423
- 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 (1)
- 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.
GPT-5.5
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
GPT-5.5 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 92 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.
DeepSeek-V4.1-Flash is more popular than GPT-5.5: 38 to 31 out of 100.
Over time
Weekly values from October 18, 2026 to November 6, 2026
GPT-5.5DeepSeek-V4.1-Flash
All data side by side
The better value is bold. For the overall index only when the gap is clear.
| Metric | GPT-5.5 | DeepSeek-V4.1-Flash |
|---|---|---|
| Intelligence | ||
| Overall indexpoints, 100 = reference group average, higher is better | 100.9 | 99.7 |
| Rank | Rank 24 of 92 | Rank 29 of 92 |
| Price per 1M tokens | ||
| Inputwhat you send | $5above 272,000 tokens: $10 | $0.15 |
| Outputwhat the model writes | $30above 272,000 tokens: $45 | $0.60 |
| Cost per task (own tests)average of 2 original-protocol tasks both models passed (SVG short test not included) | $0.19 | $0.008 |
| Speed | ||
| Tokens per second | 79 | 176 |
| Popularity | ||
| Popularitysearch, usage and mentions, 0 to 100 | 31Rank 458 of 876 | 38Rank 312 of 876 |
| Technical | ||
| Context windowhow much text the model reads at once | 1.05 M tokens≈ 1,580 A4 pages | 1 M tokens≈ 1,500 A4 pages |
| Knowledge cutoff | Dec 1, 2025 | n/a |
| Released | Apr 23, 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 108.7, rank 14$4 input and $20 output per 1M tokens
DeepSeek-V4.1-Flash vs. GPT-5.6 SolOverall index 106.6, rank 17$0.15 input and $0.60 output per 1M tokens
GPT-5.5 vs. DeepSeek V4.1 Flash 1017Overall index 103.4, rank 20$0.10 input and $0.50 output per 1M tokens
GPT-5.5 vs. Claude Haiku 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: GPT-5.5B: DeepSeek-V4.1-Flash
Show 54 more benchmarks
More comparisons
Compare GPT-5.5 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
- 8GPT-6 Astra vs. DeepSeek-V4.1-Flash
- 9Grok 4.7 vs. DeepSeek-V4.1-Flash
Show all 59 comparisons
- 10Claude Sonnet 5 vs. DeepSeek-V4.1-Flash
- 11GPT-5.6 Terra vs. DeepSeek-V4.1-Flash
- 12DeepSeek-V4.1-Flash vs. Qwen 3.8 Max 0902
- 13Claude Opus 5 vs. DeepSeek-V4.1-Flash
- 14Claude Opus 4.6 vs. DeepSeek-V4.1-Flash
- 15DeepSeek-V4.1-Flash vs. GLM-5.3-Flash
- 16Claude Sonnet 4.6 vs. DeepSeek-V4.1-Flash
- 17Claude Opus 5.5 vs. GPT-5.5
- 18DeepSeek-V4.1-Flash vs. Mistral Large 4
- 19DeepSeek-V4-Pro vs. DeepSeek-V4.1-Flash
- 20DeepSeek-V4.1-Flash vs. GLM-5.2
- 21GPT-6.1 Sol vs. DeepSeek-V4.1-Flash
- 22Gemini 3.1 Pro Preview vs. DeepSeek-V4.1-Flash
- 23DeepSeek-V4.1-Flash vs. MiMo-V2.5-Pro
- 24DeepSeek-V4.1-Flash vs. GLM-5.3
- 25Gemini 3.5 Flash-Lite vs. DeepSeek-V4.1-Flash
- 26Gemini 3.6 Flash vs. DeepSeek-V4.1-Flash
- 27Claude Opus 4.8 vs. DeepSeek-V4.1-Flash
- 28Claude Haiku 4.5 vs. DeepSeek-V4.1-Flash
- 29DeepSeek-V4.1-Flash vs. Kimi K3
- 30GPT-6 Luna vs. GPT-5.5
- 31GPT-5.6 Sol vs. DeepSeek-V4.1-Flash
- 32Claude Fable 5 vs. DeepSeek-V4.1-Flash
- 33GPT-5.6 Luna vs. DeepSeek-V4.1-Flash
- 34Gemini 4 Argon vs. DeepSeek-V4.1-Flash
- 35DeepSeek-V4.1-Flash vs. Qwen 3.8 27B
- 36Grok 4.6 vs. DeepSeek-V4.1-Flash
- 37Claude Haiku 5.5 vs. GPT-5.5
- 38DeepSeek-V4.1-Flash vs. Mistral Medium 3.5
- 39DeepSeek-V4.1-Flash vs. MiMo-V2.5
- 40GPT-5.5 vs. Gemini 3.8 Flash
- 41Claude Sonnet 4.5 vs. DeepSeek-V4.1-Flash
- 42GPT-6 Sol vs. GPT-5.5
- 43GPT-6.1 Sol vs. GPT-5.5
- 44Claude Fable 5.1 vs. DeepSeek-V4.1-Flash
- 45Claude Opus 4.5 vs. DeepSeek-V4.1-Flash
- 46Claude Sonnet 5.5 vs. GPT-5.5
- 47GPT-5.5 vs. DeepSeek V4.1 Flash 1017
- 48Claude Opus 4.7 vs. DeepSeek-V4.1-Flash
- 49DeepSeek-V4.1-Flash vs. GLM-5.1
- 50DeepSeek-V4.1-Flash vs. Mistral Large 3
- 51Gemini 3.5 Flash vs. DeepSeek-V4.1-Flash
- 52GPT-5.6 Luna vs. GPT-5.5
- 53Claude Opus 4.8 vs. GPT-5.5
- 54GPT-5.5 vs. GLM-5.3-Flash
- 55Claude Haiku 4.5 vs. GPT-5.5
- 56GPT-6.1 Terra vs. DeepSeek-V4.1-Flash
- 57GPT-6.1 Terra vs. GPT-5.5
- 58Muse Wonder vs. DeepSeek-V4.1-Flash
- 59DeepSeek-V4.1-Flash vs. Kimi K3.1 Pro