DeepSeek V4.1 Flash 1017 vs Gemini 3.5 Flash
Updated October 21, 2026. 22 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 22 shared
Decision reading
Pick DeepSeek V4.1 Flash 1017 for coding: it scores 83.3 on the Vibe Coding Index against 42.8 for Gemini 3.5 Flash.
Pick Gemini 3.5 Flash when what matters is Finance Agent (Vals AI) or Excel Modeling Benchmark (Vals AI), where it leads.
Model ADeepSeek V4.1 Flash 1017DeepSeek83.3/1002 independent benchmarksNo cost per solved taskModel BGemini 3.5 FlashGoogle42.8/1001 independent benchmark$1.21 per solved task
- Shared results
- 22
- DeepSeek V4.1 Flash 1017 only
- 10
- Gemini 3.5 Flash only
- 88
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, four public coding benchmarks
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 scores 83.3 against 42.8.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 leads, 39.5 against 33.6.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Gemini 3.5 Flash has a GPQA Diamond result, 92.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.5 Flash has a MMLU Pro result, 89.5%.
Directional only
Web design
Design Arena: websites
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 leads, 1312 against 1268.
Same board, both measured
General
Vals Index
No call
Only DeepSeek V4.1 Flash 1017 has a Vals Index result, 61.3%.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 $0.0004, Gemini 3.5 Flash $0.0060 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.5 Flash has the number, $1.21.
Directional only
At a glance
- Coding index
- DeepSeek V4.1 Flash 1017 83.3 from 2 benchmarks, Gemini 3.5 Flash 42.8 from 1 benchmark.
- Widest category
- Coding, 20.2 points apart on average over 8 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): DeepSeek V4.1 Flash 1017 87.7% against Gemini 3.5 Flash 48.7%, 39.1 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash 1017 $0.60 against Gemini 3.5 Flash $9.00 per million output tokens, 15.0x apart.
- Context window
- Both take 1.05M tokens.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | DeepSeek V4.1 Flash 1017 | Bars | Gemini 3.5 Flash | Ties |
|---|---|---|---|---|
| Coding | 8 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 2 | 2 | ||
| Reasoning | 1 | 0 | ||
| Web design | 6 | 1 | ||
| General | 1 | 0 | ||
| All shared boards | 19 | 3 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index80
| Benchmark | DeepSeek V4.1 Flash 1017 | Gemini 3.5 Flash | Leader |
|---|---|---|---|
| LiveBench coding | 96.0% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LMArena WebDev | 1664 | 1499 | DeepSeek V4.1 Flash 1017 |
| LiveCodeBench (Vals AI) | Not measured | 87.6% | Only Gemini 3.5 Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 78.8% | Only Gemini 3.5 Flash measured |
| Terminal-Bench 4 (Vals AI) | 31.8% | 6.1% | DeepSeek V4.1 Flash 1017 |
| Vibe Code Bench (Vals AI) | 87.7% | 48.7% | DeepSeek V4.1 Flash 1017 |
| Code migration (Vals AI) | 44.2% | 26.8% | DeepSeek V4.1 Flash 1017 |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Gemini 3.5 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 74.2% | Only Gemini 3.5 Flash measured |
| SkillsBench (Vals AI) | Not measured | 52.7% | Only Gemini 3.5 Flash measured |
| SciCode | 55.9% | 53.9% | DeepSeek V4.1 Flash 1017 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 46.2% | Only Gemini 3.5 Flash measured |
| WeirdML | Not measured | 62.6% | Only Gemini 3.5 Flash measured |
| ALE-Bench | 1622.0 | 911.0 | DeepSeek V4.1 Flash 1017 |
| LMArena Text: coding | Not measured | 1493 | Only Gemini 3.5 Flash measured |
| LMArena Text: software and IT | Not measured | 1494 | Only Gemini 3.5 Flash measured |
| LMArena WebDev: React | 1667 | 1495 | DeepSeek V4.1 Flash 1017 |
| LMArena WebDev: HTML | 1687 | 1522 | DeepSeek V4.1 Flash 1017 |
| LMArena WebDev: from an image | Not measured | 1504 | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4.1 Flash 1017 | Gemini 3.5 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 39.5 | 33.6 | DeepSeek V4.1 Flash 1017 |
| Epoch Capabilities Index | Not measured | 154.9 | Only Gemini 3.5 Flash measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | DeepSeek V4.1 Flash 1017 | Gemini 3.5 Flash | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1202 | Only Gemini 3.5 Flash measured |
| Design Arena: agents building full-stack apps | Not measured | 1197 | Only Gemini 3.5 Flash measured |
| Design Arena: agents building mobile apps | Not measured | 1175 | Only Gemini 3.5 Flash measured |
| Design Arena: agents building Android apps | Not measured | 1190 | Only Gemini 3.5 Flash measured |
| Design Arena: agents building Godot games | Not measured | 1098 | Only Gemini 3.5 Flash measured |
| Design Arena: agents building games | Not measured | 1180 | Only Gemini 3.5 Flash measured |
| Design Arena: HTML slides | Not measured | 1142 | Only Gemini 3.5 Flash measured |
| Design Arena: PowerPoint slides | Not measured | 1178 | Only Gemini 3.5 Flash measured |
| Design Arena: spreadsheets | 1238 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench research | 79.5% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench browser | 76.0% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench long agentic | 50.9% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Finance Agent (Vals AI) | 57.0% | 57.9% | Gemini 3.5 Flash |
| Tax Agent Bench (Vals AI) | 44.4% | 21.6% | DeepSeek V4.1 Flash 1017 |
| Legal Research Bench (Vals AI) | 45.2% | 30.8% | DeepSeek V4.1 Flash 1017 |
| Harvey's Legal Agent Benchmark (Vals AI) | 14.2% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Excel Modeling Benchmark (Vals AI) | 61.8% | 63.5% | Gemini 3.5 Flash |
| Terminal-Bench-Science (Vals AI) | Not measured | 5.7% | Only Gemini 3.5 Flash measured |
| τ²-Bench Telecom | Not measured | 95.6% | Only Gemini 3.5 Flash measured |
| APEX-Agents | Not measured | 27.5% | Only Gemini 3.5 Flash measured |
| Vending-Bench 2 | Not measured | $5,396 | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 18 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4.1 Flash 1017 | Gemini 3.5 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 92.7% | Only Gemini 3.5 Flash measured |
| LiveBench reasoning | 89.1% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| MMMU Pro (Vals AI) | Not measured | 88.3% | Only Gemini 3.5 Flash measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 92.2% | Only Gemini 3.5 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 43.3% | 42.7% | DeepSeek V4.1 Flash 1017 |
| GPQA Diamond (Epoch AI run) | Not measured | 92.8% | Only Gemini 3.5 Flash measured |
| ARC-AGI | Not measured | 92.5% | Only Gemini 3.5 Flash measured |
| ARC-AGI-2 | Not measured | 72.1% | Only Gemini 3.5 Flash measured |
| SimpleBench | Not measured | 76.7% | Only Gemini 3.5 Flash measured |
| Chess puzzles | Not measured | 45.0% | Only Gemini 3.5 Flash measured |
| Mystery game puzzles | Not measured | 32.0% | Only Gemini 3.5 Flash measured |
| EBR-bench | Not measured | 4.8% | Only Gemini 3.5 Flash measured |
| LMArena Text: hard prompts | Not measured | 1488 | Only Gemini 3.5 Flash measured |
| LMArena Text: expert | Not measured | 1495 | Only Gemini 3.5 Flash measured |
| LMArena Text: hard prompts in English | Not measured | 1483 | Only Gemini 3.5 Flash measured |
| LMArena Vision: diagrams | Not measured | 1323 | Only Gemini 3.5 Flash measured |
| LMArena Vision: homework | Not measured | 1330 | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 4 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | DeepSeek V4.1 Flash 1017 | Gemini 3.5 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 95.6% | Only Gemini 3.5 Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 62.8% | Only Gemini 3.5 Flash measured |
| FrontierMath, tier 4 | Not measured | 26.8% | Only Gemini 3.5 Flash measured |
| ProofBench | Not measured | 31.0% | Only Gemini 3.5 Flash measured |
| LMArena Text: math | Not measured | 1504 | Only Gemini 3.5 Flash measured |
| LMArena Text: mathematical work | Not measured | 1495 | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | DeepSeek V4.1 Flash 1017 | Gemini 3.5 Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 89.5% | Only Gemini 3.5 Flash measured |
| LegalBench (Vals AI) | Not measured | 83.6% | Only Gemini 3.5 Flash measured |
| CorpFin (Vals AI) | Not measured | 64.7% | Only Gemini 3.5 Flash measured |
| TaxEval (Vals AI) | Not measured | 74.4% | Only Gemini 3.5 Flash measured |
| MortgageTax (Vals AI) | Not measured | 68.1% | Only Gemini 3.5 Flash measured |
| MedCode (Vals AI) | Not measured | 55.8% | Only Gemini 3.5 Flash measured |
| SimpleQA Verified | Not measured | 66.2% | Only Gemini 3.5 Flash measured |
| LMArena Text: science | Not measured | 1495 | Only Gemini 3.5 Flash measured |
| LMArena Text: medicine and healthcare | Not measured | 1483 | Only Gemini 3.5 Flash measured |
| LMArena Text: legal and government | Not measured | 1488 | Only Gemini 3.5 Flash measured |
| LMArena Text: business and finance | Not measured | 1467 | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index61
| Benchmark | DeepSeek V4.1 Flash 1017 | Gemini 3.5 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1312 | 1268 | DeepSeek V4.1 Flash 1017 |
| Design Arena: UI components | 1305 | 1272 | DeepSeek V4.1 Flash 1017 |
| Design Arena: game dev | 1365 | 1263 | DeepSeek V4.1 Flash 1017 |
| Design Arena: data viz | 1330 | 1236 | DeepSeek V4.1 Flash 1017 |
| Design Arena: 3D | 1368 | 1244 | DeepSeek V4.1 Flash 1017 |
| Design Arena: all code categories | 1335 | 1266 | DeepSeek V4.1 Flash 1017 |
| Design Arena: SVG | Not measured | 1254 | Only Gemini 3.5 Flash measured |
| Design Arena: ASCII art | 1244 | 1253 | Gemini 3.5 Flash |
| LiveBench design | 83.4% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4.1 Flash 1017 | Gemini 3.5 Flash | Leader |
|---|---|---|---|
| Vals Index | 61.3% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench data analysis | 79.5% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Public Benefits Bench (Vals AI) | Not measured | 59.5% | Only Gemini 3.5 Flash measured |
| SAGE (Vals AI) | Not measured | 49.9% | Only Gemini 3.5 Flash measured |
| MedScribe (Vals AI) | Not measured | 76.6% | Only Gemini 3.5 Flash measured |
| Vals Multimodal Index | Not measured | 62.9% | Only Gemini 3.5 Flash measured |
| IFBench | Not measured | 76.3% | Only Gemini 3.5 Flash measured |
| Long context reasoning (AA-LCR) | 82.7% | 74.3% | DeepSeek V4.1 Flash 1017 |
| DTBench | Not measured | 94.7% | Only Gemini 3.5 Flash measured |
| LMCA | Not measured | 47.1% | Only Gemini 3.5 Flash measured |
| Surface Evolver Bench | Not measured | 58.1% | Only Gemini 3.5 Flash measured |
| LMArena Text | Not measured | 1482 | Only Gemini 3.5 Flash measured |
| LMArena Text: instruction following | Not measured | 1467 | Only Gemini 3.5 Flash measured |
| LMArena Text: creative writing | Not measured | 1470 | Only Gemini 3.5 Flash measured |
| LMArena Vision | Not measured | 1308 | Only Gemini 3.5 Flash measured |
| LMArena Text: English | Not measured | 1481 | Only Gemini 3.5 Flash measured |
| LMArena Text: non-English | Not measured | 1475 | Only Gemini 3.5 Flash measured |
| LMArena Text: Chinese | Not measured | 1527 | Only Gemini 3.5 Flash measured |
| LMArena Text: German | Not measured | 1494 | Only Gemini 3.5 Flash measured |
| LMArena Text: Japanese | Not measured | 1486 | Only Gemini 3.5 Flash measured |
| LMArena Text: Korean | Not measured | 1448 | Only Gemini 3.5 Flash measured |
| LMArena Text: French | Not measured | 1490 | Only Gemini 3.5 Flash measured |
| LMArena Text: Spanish | Not measured | 1480 | Only Gemini 3.5 Flash measured |
| LMArena Text: Russian | Not measured | 1493 | Only Gemini 3.5 Flash measured |
| LMArena Text: Polish | Not measured | 1516 | Only Gemini 3.5 Flash measured |
| LMArena Text: multi-turn | Not measured | 1481 | Only Gemini 3.5 Flash measured |
| LMArena Text: longer queries | Not measured | 1483 | Only Gemini 3.5 Flash measured |
| LMArena Text: writing and language | Not measured | 1478 | Only Gemini 3.5 Flash measured |
| LMArena Text: entertainment and media | Not measured | 1459 | Only Gemini 3.5 Flash measured |
| LMArena Vision: English | Not measured | 1305 | Only Gemini 3.5 Flash measured |
| LMArena Vision: Chinese | Not measured | 1377 | Only Gemini 3.5 Flash measured |
| LMArena Vision: reading text | Not measured | 1317 | Only Gemini 3.5 Flash measured |
| LMArena Vision: humor | Not measured | 1321 | Only Gemini 3.5 Flash measured |
| LMArena Vision: creative writing | Not measured | 1301 | Only Gemini 3.5 Flash measured |
| LMArena Document | Not measured | 1463 | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4.1 Flash 1017 | Gemini 3.5 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
DeepSeek V4.1 Flash 1017$0.0004Fits in one request
Gemini 3.5 Flash$0.0060Fits in one request
DeepSeek V4.1 Flash 1017 costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash 1017$0.0093Fits in one request
Gemini 3.5 Flash$0.102Fits in one request
DeepSeek V4.1 Flash 1017 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4.1 Flash 1017$0.036Fits in one request
Gemini 3.5 Flash$0.390Fits in one request
DeepSeek V4.1 Flash 1017 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | DeepSeek V4.1 Flash 1017 | Google Gemini 3.5 Flash |
|---|---|---|
| Maker | DeepSeek | |
| Weights | Open weights | No public weights listed |
| Released | October 17, 2026 | May 19, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.15 | $1.50 |
| Output $/Mtok | $0.60 | $9.00 |
| Coding index | 83.3 | 42.8 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | $1.21 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash 1017 better than Gemini 3.5 Flash for coding?
Pick DeepSeek V4.1 Flash 1017 for coding: it scores 83.3 on the Vibe Coding Index against 42.8 for Gemini 3.5 Flash. Pick Gemini 3.5 Flash when what matters is Finance Agent (Vals AI) or Excel Modeling Benchmark (Vals AI), where it leads.
Which is cheaper, DeepSeek V4.1 Flash 1017 or Gemini 3.5 Flash?
DeepSeek V4.1 Flash 1017 costs $0.15 per million input tokens and $0.60 per million output tokens; Gemini 3.5 Flash costs $1.50 and $9.00. Cost per solved task is known for Gemini 3.5 Flash only.
Which has the bigger context window, DeepSeek V4.1 Flash 1017 or Gemini 3.5 Flash?
Neither: both take 1.05M tokens.
How many benchmarks is the DeepSeek V4.1 Flash 1017 vs Gemini 3.5 Flash comparison based on?
22 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4.1 Flash 1017's coding index rests on 2 independent benchmarks and Gemini 3.5 Flash's on 1. Where only one model has a result, the page says so instead of naming a winner.