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- DeepSeek-V4.1-Flash vs. Kimi K3
DeepSeekMoonshot AILLM matchup
DeepSeek-V4.1-Flashvs.Kimi K3
Which one is better?
DeepSeek-V4.1-Flash and Kimi K3 perform about equally well, but Kimi K3 costs 20 times (input) and 25 times (output) as much.
DeepSeek-V4.1-Flash
Rank 29
Kimi K3
Rank 23
DeepSeek-V4.1-Flash
Kimi K3
DeepSeek-V4.1-Flash
Kimi K3
DeepSeek-V4.1-Flash
Rank 298 of 875
Kimi K3
Rank 19 of 875
Choose DeepSeek-V4.1-Flash for
Choose Kimi K3 for
On this page
Where is the difference?
Strengths at a glance
DeepSeek-V4.1-FlashKimi K3
The median of all ranked models is below 100 in every area, so it sits in the centre of the net.
95 % range: DeepSeek-V4.1-Flash 91.4 to 106.3, Kimi K3 90.7 to 103.9.
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.
Kimi K3 is ahead in 4 of 10 areas, DeepSeek-V4.1-Flash in none.
DeepSeek-V4.1-Flash slightly ahead: 1level: 2too little data: 2Kimi K3 slightly ahead: 1Kimi K3 ahead: 4
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.
DeepSeek-V4.1-Flash vs. Kimi K3 at the same effort
Both models measured at the same reasoning efforts. This shows whether a lead comes from the model or only from more compute.
| Effort | DeepSeek-V4.1-Flash | Kimi K3 | Gap | Verdict | Test series |
|---|---|---|---|---|---|
| max | 99.7 | 101.2 | 2.5 | tied | 5 |
| Overall index (max vs. max) | 99.7 | 101.2 | 1.5 | level |
Gap and verdict compare only the Artificial Analysis test series in which both models are measured at that effort. Tied below 3 points, ahead only beyond two standard errors. The single values rest on all test series of each model, so their difference can deviate from the gap.
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
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.
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
Kimi K3

Oct 14, 2026 · $0.0049
Test details
- Test run
- Oct 14, 2026
- Provider
- chutes/mxfp4
- API model
- moonshotai/kimi-k3
- Output
- 495 tokens
- Reasoning
- API reports 0 reasoning tokens
- Cost of the attempt
- $0.0049
- Test round
- 43b8c5c46830
Earlier tests
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
Kimi K3

Oct 1, 2026 · 173 s · $0.08
Test details
- Run date
- Oct 1, 2026
- API provider
- openrouter
- Requested API model
- moonshotai/kimi-k3
- Reasoning setting
- high
- Token limit including reasoning
- 8,192 tokens
- Output tokens
- 5,145 tokens
- Cost of the attempt
- $0.0775
- Response time
- 173.4 s
- API model reported in response
- moonshotai/kimi-k3
- Pinned endpoint
- Moonshot AI | moonshotai/kimi-k3-20260715
- 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 and Kimi K3 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.
Kimi K3 is more popular than DeepSeek-V4.1-Flash: 68 to 38 out of 100.
Over time
Weekly values from October 18, 2026 to November 5, 2026
DeepSeek-V4.1-FlashKimi K3
All data side by side
The better value is bold. For the overall index only when the gap is clear.
| Metric | DeepSeek-V4.1-Flash | Kimi K3 |
|---|---|---|
| Intelligence | ||
| Overall indexpoints, 100 = reference group average, higher is better | 99.7 | 101.2 |
| Rank | Rank 29 of 91 | Rank 23 of 91 |
| Price per 1M tokens | ||
| Inputwhat you send | $0.15 | $3 |
| Outputwhat the model writes | $0.60 | $15 |
| Cost per task (own tests)average of 2 tests both passed | $0.008 | $0.043 |
| Speed | ||
| Tokens per second | 176 | 39 |
| Popularity | ||
| Popularitysearch, usage and mentions, 0 to 100 | 38Rank 298 of 875 | 68Rank 19 of 875 |
| Technical | ||
| Context windowhow much text the model reads at once | 1 M tokens≈ 1,500 A4 pages | 1.05 M tokens≈ 1,570 A4 pages |
| Knowledge cutoff | n/a | n/a |
| Released | Sep 10, 2026 | Jul 16, 2026 |
| Availability | Active | Active |
| Open weights | yes | 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.
Kimi K3 vs. DeepSeek V4.1 Flash 1017Overall index 112.9, rank 11. $2 input and $10 output per 1M tokens.
DeepSeek-V4.1-Flash vs. Kimi K3.1 ProOverall index 103.4, rank 20. $0.10 input and $0.50 output per 1M tokens.
Kimi K3 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: DeepSeek-V4.1-FlashB: Kimi K3
Show 54 more benchmarks
More comparisons
Compare DeepSeek-V4.1-Flash and Kimi K3 with the models people compare them with most often.
Compare another matchup
Predecessor and successor
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
- 4Claude Opus 5.5 vs. Kimi K3
- 5Muse Spark 1.3 vs. DeepSeek-V4.1-Flash
- 6Claude Haiku 5.5 vs. DeepSeek-V4.1-Flash
- 7Claude Sonnet 5.5 vs. DeepSeek-V4.1-Flash
- 8GPT-6 Sol vs. DeepSeek-V4.1-Flash
- 9GPT-6 Astra vs. DeepSeek-V4.1-Flash
Show all 57 comparisons
- 10GPT-6 Astra vs. Kimi K3
- 11Claude Sonnet 5 vs. DeepSeek-V4.1-Flash
- 12Grok 4.7 vs. DeepSeek-V4.1-Flash
- 13Claude Opus 5 vs. DeepSeek-V4.1-Flash
- 14GPT-5.6 Terra vs. DeepSeek-V4.1-Flash
- 15Claude Sonnet 5.5 vs. Kimi K3
- 16DeepSeek-V4.1-Flash vs. GLM-5.3-Flash
- 17Grok 4.7 vs. Kimi K3
- 18Gemini 3.1 Pro Preview vs. Kimi K3
- 19Claude Opus 4.6 vs. DeepSeek-V4.1-Flash
- 20Claude Sonnet 4.6 vs. DeepSeek-V4.1-Flash
- 21DeepSeek-V4.1-Flash vs. Qwen 3.8 Max 0902
- 22GPT-6.1 Sol vs. DeepSeek-V4.1-Flash
- 23DeepSeek-V4-Pro vs. DeepSeek-V4.1-Flash
- 24DeepSeek-V4.1-Flash vs. Mistral Large 4
- 25Claude Opus 5 vs. Kimi K3
- 26Kimi K3 vs. GLM-5.3-Flash
- 27GPT-6.1 Sol vs. Kimi K3
- 28DeepSeek-V4.1-Flash vs. MiMo-V2.5-Pro
- 29DeepSeek-V4-Pro vs. Kimi K3
- 30Gemini 3.5 Flash-Lite vs. DeepSeek-V4.1-Flash
- 31Claude Haiku 4.5 vs. DeepSeek-V4.1-Flash
- 32Gemini 3.1 Pro Preview vs. DeepSeek-V4.1-Flash
- 33Kimi K3 vs. GLM-5.3
- 34DeepSeek-V4.1-Flash vs. GLM-5.2
- 35Gemini 3.6 Flash vs. DeepSeek-V4.1-Flash
- 36DeepSeek-V4.1-Flash vs. GLM-5.3
- 37GPT-6 Sol vs. Kimi K3
- 38GPT-5.6 Sol vs. DeepSeek-V4.1-Flash
- 39Claude Opus 4.8 vs. DeepSeek-V4.1-Flash
- 40Claude Fable 5 vs. Kimi K3
- 41Kimi K3 vs. Mistral Large 4
- 42Grok 4.6 vs. DeepSeek-V4.1-Flash
- 43Claude Fable 5 vs. DeepSeek-V4.1-Flash
- 44Claude Opus 4.8 vs. Kimi K3
- 45GPT-5.6 Luna vs. DeepSeek-V4.1-Flash
- 46GPT-5.4 vs. Kimi K3
- 47Claude Opus 4.7 vs. DeepSeek-V4.1-Flash
- 48Claude Sonnet 4.5 vs. DeepSeek-V4.1-Flash
- 49Claude Opus 4.5 vs. DeepSeek-V4.1-Flash
- 50Claude Fable 5.1 vs. DeepSeek-V4.1-Flash
- 51DeepSeek-V4.1-Flash vs. Mistral Medium 3.5
- 52DeepSeek-V4.1-Flash vs. MiMo-V2.5
- 53DeepSeek-V4.1-Flash vs. GLM-5.1
- 54DeepSeek-V4.1-Flash vs. Mistral Large 3
- 55Muse Wonder Full vs. Kimi K3
- 56GPT-5.5 vs. DeepSeek-V4.1-Flash
- 57Muse Wonder Full vs. DeepSeek-V4.1-Flash