DeepSeek V4.1 Flash vs Gemini 2.5 Flash
DeepSeek V4.1 Flash leads Gemini 2.5 Flash on the Artificial Analysis Intelligence Index, 24.7 to 15.5, and DeepSeek V4.1 Flash costs 3.0x less per output token ($0.84 vs $2.50 per million). Updated October 22, 2026; 54 benchmarks have a result for both.
vs boards won of 54 shared
DeepSeek V4.1 Flash or Gemini 2.5 Flash: which to pick
Only DeepSeek V4.1 Flash has a coding score, 62.5 on the Vibe Coding Index; Gemini 2.5 Flash has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
Model ADeepSeek V4.1 FlashDeepSeek62.5/1005 independent benchmarksNo cost per solved taskModel BGemini 2.5 FlashGoogleNot benchmarkedNo coding benchmark$0.466 per solved task
- Shared results
- 54
- DeepSeek V4.1 Flash only
- 47
- Gemini 2.5 Flash only
- 19
- Like-for-like categories
- 7 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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, six public coding benchmarks
No call
Only DeepSeek V4.1 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 24.7 against 15.5.
Same board, both measured
Web design
Design Arena: websites
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 1308 against 1074.
Same board, both measured
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
DeepSeek V4.1 Flash $0.0006, Gemini 2.5 Flash $0.0015 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 2.5 Flash has the number, $0.466.
Directional only
At a glance
- Coding index
- DeepSeek V4.1 Flash 62.5 from 5 benchmarks, Gemini 2.5 Flash not benchmarked.
- Widest category
- Web design, 34.3 points apart on average over 7 shared benchmarks.
- Widest single gap
- ARC-AGI-2: DeepSeek V4.1 Flash 72.9% against Gemini 2.5 Flash 2.5%, 70.4 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash $0.84 against Gemini 2.5 Flash $2.50 per million output tokens, 3.0x 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 | Bars | Gemini 2.5 Flash | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 8 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 5 | 0 | ||
| Web design | 7 | 0 | ||
| General | 28 | 0 | ||
| All shared boards | 54 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | DeepSeek V4.1 Flash | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 28.7% | Only Gemini 2.5 Flash measured |
| LiveBench coding | 90.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev | 1618 | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench 4 (Vals AI) | 19.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench (Vals AI) | 84.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| Code migration (Vals AI) | 45.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| IOI (Vals AI) | 40.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 74.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| SWE-bench Multimodal (Vals AI) | 46.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench 1-100 (Vals AI) | 16.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| SkillsBench (Vals AI) | 69.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| CyberBench (Vals AI) | 73.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 69.5% | Only Gemini 2.5 Flash measured |
| SciCode | 51.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 13.6% | Only Gemini 2.5 Flash measured |
| Terminal-Bench | Not measured | 17.1% | Only Gemini 2.5 Flash measured |
| FrontierCode | 43.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| ALE-Bench | 1092.3 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: coding | 1502 | 1423 | DeepSeek V4.1 Flash |
| LMArena Text: software and IT | 1496 | 1425 | DeepSeek V4.1 Flash |
| LMArena WebDev: React | 1628 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev: HTML | 1612 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev: from an image | 1606 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4.1 Flash | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.7 | 15.5 | DeepSeek V4.1 Flash |
| Epoch Capabilities Index | 155.9 | 142.9 | DeepSeek V4.1 Flash |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| LiveBench research | 86.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench browser | 84.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench long agentic | 40.1% | Not measured | Only DeepSeek V4.1 Flash measured |
| SREBench (Vals AI) | 0.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Finance Agent (Vals AI) | 53.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Tax Agent Bench (Vals AI) | 26.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| Legal Research Bench (Vals AI) | 41.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 57.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| BioMysteryBench (Vals AI) | 67.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vals Science Index | 29.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| τ²-Bench Telecom | Not measured | 31.6% | Only Gemini 2.5 Flash measured |
| APEX-Agents | 39.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| BALROG | Not measured | 33.5% | Only Gemini 2.5 Flash measured |
| Vending-Bench 2 | Not measured | $549 | Only Gemini 2.5 Flash measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 56.2% | Only Gemini 2.5 Flash measured |
| BrowseComp-Plus | Not measured | 39.9% | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 24 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | DeepSeek V4.1 Flash | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| LiveBench reasoning | 86.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| MysteryMechanism (Vals AI) | 21.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 79.0% | Only Gemini 2.5 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 39.2% | 12.1% | DeepSeek V4.1 Flash |
| GPQA Diamond (Epoch AI run) | 89.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| ARC-AGI | 94.5% | 33.3% | DeepSeek V4.1 Flash |
| ARC-AGI-2 | 72.9% | 2.5% | DeepSeek V4.1 Flash |
| SimpleBench | Not measured | 41.2% | Only Gemini 2.5 Flash measured |
| Chess puzzles | 48.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Mystery game puzzles | 43.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: hard prompts | 1483 | 1422 | DeepSeek V4.1 Flash |
| LMArena Text: expert | 1501 | 1426 | DeepSeek V4.1 Flash |
| LMArena Text: hard prompts in English | 1488 | 1420 | DeepSeek V4.1 Flash |
| LMArena Vision: diagrams | 1297 | 1245 | DeepSeek V4.1 Flash |
| LMArena Vision: homework | 1307 | 1244 | DeepSeek V4.1 Flash |
| Kagi LLM Benchmark | Not measured | 56.8% | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4.1 Flash | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 73.3 | Only Gemini 2.5 Flash measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 73.3% | Only Gemini 2.5 Flash measured |
| OTIS Mock AIME | 98.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| FrontierMath, tiers 1 to 3 | 67.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| ProofBench | 54.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: math | 1478 | 1411 | DeepSeek V4.1 Flash |
| LMArena Text: mathematical work | 1485 | 1422 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | DeepSeek V4.1 Flash | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| MedCode (Vals AI) | 41.2% | 40.4% | DeepSeek V4.1 Flash |
| MMLU Pro (Artificial Analysis run) | Not measured | 83.2% | Only Gemini 2.5 Flash measured |
| SimpleQA Verified | 42.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: science | 1469 | 1433 | DeepSeek V4.1 Flash |
| LMArena Text: medicine and healthcare | 1484 | 1428 | DeepSeek V4.1 Flash |
| LMArena Text: legal and government | 1443 | 1430 | DeepSeek V4.1 Flash |
| LMArena Text: business and finance | 1461 | 1404 | DeepSeek V4.1 Flash |
| FACTS Benchmark Suite | Not measured | 47.2% | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 9 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | DeepSeek V4.1 Flash | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1308 | 1074 | DeepSeek V4.1 Flash |
| Design Arena: UI components | 1312 | 1002 | DeepSeek V4.1 Flash |
| Design Arena: game dev | 1330 | 1004 | DeepSeek V4.1 Flash |
| Design Arena: data viz | 1291 | 1060 | DeepSeek V4.1 Flash |
| Design Arena: 3D | 1355 | 1020 | DeepSeek V4.1 Flash |
| Design Arena: all code categories | 1320 | 1059 | DeepSeek V4.1 Flash |
| Design Arena: SVG | 1245 | 1020 | DeepSeek V4.1 Flash |
| Design Arena: ASCII art | 1265 | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench design | 79.2% | Not measured | Only DeepSeek V4.1 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index280
| Benchmark | DeepSeek V4.1 Flash | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Public Benefits Bench (Vals AI) | 64.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| SAGE (Vals AI) | 47.9% | 44.8% | DeepSeek V4.1 Flash |
| MedScribe (Vals AI) | 85.5% | 83.0% | DeepSeek V4.1 Flash |
| IFBench | Not measured | 50.3% | Only Gemini 2.5 Flash measured |
| Long context reasoning (AA-LCR) | 84.0% | 65.3% | DeepSeek V4.1 Flash |
| DTBench | 89.9% | 76.5% | DeepSeek V4.1 Flash |
| LMCA | 47.0% | 27.5% | DeepSeek V4.1 Flash |
| Surface Evolver Bench | 46.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Furniture assembly | 34.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text | 1464 | 1417 | DeepSeek V4.1 Flash |
| LMArena Text: instruction following | 1473 | 1405 | DeepSeek V4.1 Flash |
| LMArena Text: creative writing | 1437 | 1400 | DeepSeek V4.1 Flash |
| LMArena Vision | 1278 | 1235 | DeepSeek V4.1 Flash |
| LMArena Text: English | 1473 | 1418 | DeepSeek V4.1 Flash |
| LMArena Text: non-English | 1449 | 1409 | DeepSeek V4.1 Flash |
| LMArena Text: Chinese | 1501 | 1449 | DeepSeek V4.1 Flash |
| LMArena Text: German | 1470 | 1417 | DeepSeek V4.1 Flash |
| LMArena Text: Japanese | 1432 | 1396 | DeepSeek V4.1 Flash |
| LMArena Text: Korean | 1436 | 1385 | DeepSeek V4.1 Flash |
| LMArena Text: French | 1465 | 1432 | DeepSeek V4.1 Flash |
| LMArena Text: Spanish | 1459 | 1422 | DeepSeek V4.1 Flash |
| LMArena Text: Russian | 1467 | 1415 | DeepSeek V4.1 Flash |
| LMArena Text: Polish | 1457 | 1413 | DeepSeek V4.1 Flash |
| LMArena Text: multi-turn | 1461 | 1408 | DeepSeek V4.1 Flash |
| LMArena Text: longer queries | 1473 | 1419 | DeepSeek V4.1 Flash |
| LMArena Text: writing and language | 1450 | 1405 | DeepSeek V4.1 Flash |
| LMArena Text: entertainment and media | 1445 | 1393 | DeepSeek V4.1 Flash |
| LMArena Vision: English | 1288 | 1239 | DeepSeek V4.1 Flash |
| LMArena Vision: Chinese | 1327 | 1284 | DeepSeek V4.1 Flash |
| LMArena Vision: reading text | 1282 | 1237 | DeepSeek V4.1 Flash |
| LMArena Vision: humor | 1260 | 1225 | DeepSeek V4.1 Flash |
| LMArena Vision: captioning | Not measured | 1277 | Only Gemini 2.5 Flash measured |
| LMArena Vision: recognizing things | Not measured | 1252 | Only Gemini 2.5 Flash measured |
| LMArena Vision: creative writing | 1275 | 1241 | DeepSeek V4.1 Flash |
| 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 | Gemini 2.5 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$0.0006Fits in one request
Gemini 2.5 Flash$0.0015Fits in one request
DeepSeek V4.1 Flash costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash$0.014Fits in one request
Gemini 2.5 Flash$0.022Fits in one request
DeepSeek V4.1 Flash costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4.1 Flash$0.053Fits in one request
Gemini 2.5 Flash$0.085Fits in one request
DeepSeek V4.1 Flash 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 | Google Gemini 2.5 Flash |
|---|---|---|
| Maker | DeepSeek | |
| Weights | Open weights | No public weights listed |
| Released | September 10, 2026 | June 17, 2025 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.2225 | $0.30 |
| Output $/Mtok | $0.84 | $2.50 |
| Coding index | 62.5 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | $0.466 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash better than Gemini 2.5 Flash for coding?
Only DeepSeek V4.1 Flash has a coding score, 62.5 on the Vibe Coding Index; Gemini 2.5 Flash has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, DeepSeek V4.1 Flash or Gemini 2.5 Flash?
DeepSeek V4.1 Flash costs $0.2225 per million input tokens and $0.84 per million output tokens; Gemini 2.5 Flash costs $0.30 and $2.50. Cost per solved task is known for Gemini 2.5 Flash only.
Which has the bigger context window, DeepSeek V4.1 Flash or Gemini 2.5 Flash?
Neither: both take 1.05M tokens.
How many benchmarks is the DeepSeek V4.1 Flash vs Gemini 2.5 Flash comparison based on?
54 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4.1 Flash's coding index rests on 5 independent benchmarks and Gemini 2.5 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.