DeepSeek V3.1 vs Gemini 3.7 Flash
Gemini 3.7 Flash leads DeepSeek V3.1 on the Artificial Analysis Intelligence Index, 39.6 to 13.7, and DeepSeek V3.1 costs 2.5x less per output token ($1.50 vs $3.75 per million). Updated October 21, 2026; 10 benchmarks have a result for both.
vs boards won of 10 shared
DeepSeek V3.1 or Gemini 3.7 Flash: which to pick
Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; DeepSeek V3.1 has none, so the two cannot be ranked on coding.
Pick DeepSeek V3.1 for output tokens 2.5x cheaper ($1.50 vs $3.75 per million).
Model ADeepSeek V3.1DeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGemini 3.7 FlashGoogle58.0/1006 independent benchmarks$1.78 per solved task
- Shared results
- 10
- DeepSeek V3.1 only
- 0
- Gemini 3.7 Flash only
- 102
- Like-for-like categories
- 3 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 Gemini 3.7 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 39.6 against 13.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Gemini 3.7 Flash has a GPQA Diamond result, 93.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.7 Flash has a MMLU Pro result, 90.1%.
Directional only
Web design
Design Arena: websites
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 1304 against 1123.
Same board, both measured
Long documents
Listed context window
Gemini 3.7 Flash
Gemini 3.7 Flash takes 1.05M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1
DeepSeek V3.1 $0.0013, Gemini 3.7 Flash $0.0026 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.7 Flash has the number, $1.78.
Directional only
At a glance
- Coding index
- DeepSeek V3.1 not benchmarked, Gemini 3.7 Flash 58.0 from 6 benchmarks.
- Widest category
- Web design, 28.4 points apart on average over 7 shared benchmarks.
- Widest single gap
- Design Arena: SVG: DeepSeek V3.1 967 against Gemini 3.7 Flash 1283, 39.5 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 $1.50 against Gemini 3.7 Flash $3.75 per million output tokens, 2.5x apart.
- Context window
- DeepSeek V3.1 takes 164K tokens, Gemini 3.7 Flash 1.05M.
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 V3.1 | Bars | Gemini 3.7 Flash | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Web design | 0 | 7 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 10 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index22 boards, none shared
| Benchmark | DeepSeek V3.1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 80.5% | Only Gemini 3.7 Flash measured |
| LMArena WebDev | Not measured | 1591 | Only Gemini 3.7 Flash measured |
| AA Coding Index | Not measured | 71.5 | Only Gemini 3.7 Flash measured |
| LiveCodeBench (Vals AI) | Not measured | 88.7% | Only Gemini 3.7 Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 80.8% | Only Gemini 3.7 Flash measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 12.1% | Only Gemini 3.7 Flash measured |
| Vibe Code Bench (Vals AI) | Not measured | 70.4% | Only Gemini 3.7 Flash measured |
| Code migration (Vals AI) | Not measured | 34.8% | Only Gemini 3.7 Flash measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Gemini 3.7 Flash measured |
| IOI (Vals AI) | Not measured | 67.8% | Only Gemini 3.7 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 77.5% | Only Gemini 3.7 Flash measured |
| SkillsBench (Vals AI) | Not measured | 65.9% | Only Gemini 3.7 Flash measured |
| CyberBench (Vals AI) | Not measured | 43.8% | Only Gemini 3.7 Flash measured |
| SciCode | Not measured | 59.8% | Only Gemini 3.7 Flash measured |
| FrontierCode | Not measured | 43.6% | Only Gemini 3.7 Flash measured |
| FrontierSWE | Not measured | 20.3% | Only Gemini 3.7 Flash measured |
| ALE-Bench | Not measured | 904.3 | Only Gemini 3.7 Flash measured |
| LMArena Text: coding | Not measured | 1499 | Only Gemini 3.7 Flash measured |
| LMArena Text: software and IT | Not measured | 1498 | Only Gemini 3.7 Flash measured |
| LMArena WebDev: React | Not measured | 1587 | Only Gemini 3.7 Flash measured |
| LMArena WebDev: HTML | Not measured | 1593 | Only Gemini 3.7 Flash measured |
| LMArena WebDev: from an image | Not measured | 1599 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 16 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.7 | 39.6 | Gemini 3.7 Flash |
| Epoch Capabilities Index | Not measured | 158.0 | Only Gemini 3.7 Flash measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | DeepSeek V3.1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1223 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building full-stack apps | Not measured | 1208 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building mobile apps | Not measured | 1230 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Android apps | Not measured | 1242 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Godot games | Not measured | 1264 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building games | Not measured | 1235 | Only Gemini 3.7 Flash measured |
| Design Arena: spreadsheets | Not measured | 1053 | Only Gemini 3.7 Flash measured |
| LiveBench research | Not measured | 76.5% | Only Gemini 3.7 Flash measured |
| LiveBench browser | Not measured | 56.0% | Only Gemini 3.7 Flash measured |
| LiveBench long agentic | Not measured | 28.3% | Only Gemini 3.7 Flash measured |
| SREBench (Vals AI) | Not measured | 4.6% | Only Gemini 3.7 Flash measured |
| Finance Agent (Vals AI) | Not measured | 59.0% | Only Gemini 3.7 Flash measured |
| Tax Agent Bench (Vals AI) | Not measured | 22.8% | Only Gemini 3.7 Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 34.6% | Only Gemini 3.7 Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 71.3% | Only Gemini 3.7 Flash measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 7.1% | Only Gemini 3.7 Flash measured |
| APEX-Agents | Not measured | 67.8% | Only Gemini 3.7 Flash measured |
| Remote Labor Index | Not measured | 5.0% | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | DeepSeek V3.1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 93.9% | Only Gemini 3.7 Flash measured |
| LiveBench reasoning | Not measured | 87.8% | Only Gemini 3.7 Flash measured |
| MMMU Pro (Vals AI) | Not measured | 89.0% | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 94.5% | Only Gemini 3.7 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 47.9% | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Epoch AI run) | Not measured | 94.8% | Only Gemini 3.7 Flash measured |
| ARC-AGI | Not measured | 95.5% | Only Gemini 3.7 Flash measured |
| ARC-AGI-2 | Not measured | 84.6% | Only Gemini 3.7 Flash measured |
| Chess puzzles | Not measured | 66.0% | Only Gemini 3.7 Flash measured |
| Mystery game puzzles | Not measured | 37.0% | Only Gemini 3.7 Flash measured |
| LMArena Text: hard prompts | Not measured | 1495 | Only Gemini 3.7 Flash measured |
| LMArena Text: expert | Not measured | 1512 | Only Gemini 3.7 Flash measured |
| LMArena Text: hard prompts in English | Not measured | 1487 | Only Gemini 3.7 Flash measured |
| LMArena Vision: diagrams | Not measured | 1329 | Only Gemini 3.7 Flash measured |
| LMArena Vision: homework | Not measured | 1320 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 6 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | DeepSeek V3.1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 97.2% | Only Gemini 3.7 Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 71.6% | Only Gemini 3.7 Flash measured |
| FrontierMath, tier 4 | Not measured | 36.6% | Only Gemini 3.7 Flash measured |
| ProofBench | Not measured | 58.0% | Only Gemini 3.7 Flash measured |
| LMArena Text: math | Not measured | 1511 | Only Gemini 3.7 Flash measured |
| LMArena Text: mathematical work | Not measured | 1502 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | DeepSeek V3.1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 90.1% | Only Gemini 3.7 Flash measured |
| LegalBench (Vals AI) | Not measured | 87.3% | Only Gemini 3.7 Flash measured |
| TaxEval (Vals AI) | Not measured | 74.7% | Only Gemini 3.7 Flash measured |
| MortgageTax (Vals AI) | Not measured | 66.7% | Only Gemini 3.7 Flash measured |
| MedCode (Vals AI) | Not measured | 53.4% | Only Gemini 3.7 Flash measured |
| SimpleQA Verified | Not measured | 69.2% | Only Gemini 3.7 Flash measured |
| LMArena Text: science | Not measured | 1511 | Only Gemini 3.7 Flash measured |
| LMArena Text: medicine and healthcare | Not measured | 1494 | Only Gemini 3.7 Flash measured |
| LMArena Text: legal and government | Not measured | 1496 | Only Gemini 3.7 Flash measured |
| LMArena Text: business and finance | Not measured | 1479 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V3.1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1123 | 1304 | Gemini 3.7 Flash |
| Design Arena: UI components | 1085 | 1299 | Gemini 3.7 Flash |
| Design Arena: game dev | 1084 | 1318 | Gemini 3.7 Flash |
| Design Arena: data viz | 1095 | 1315 | Gemini 3.7 Flash |
| Design Arena: 3D | 1077 | 1308 | Gemini 3.7 Flash |
| Design Arena: all code categories | 1112 | 1308 | Gemini 3.7 Flash |
| Design Arena: SVG | 967 | 1283 | Gemini 3.7 Flash |
| Design Arena: ASCII art | Not measured | 1276 | Only Gemini 3.7 Flash measured |
| LiveBench design | Not measured | 73.2% | Only Gemini 3.7 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3.1 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 68.0% | Only Gemini 3.7 Flash measured |
| SAGE (Vals AI) | Not measured | 49.2% | Only Gemini 3.7 Flash measured |
| MedScribe (Vals AI) | Not measured | 83.9% | Only Gemini 3.7 Flash measured |
| Long context reasoning (AA-LCR) | Not measured | 83.0% | Only Gemini 3.7 Flash measured |
| DTBench | 82.7% | 96.8% | Gemini 3.7 Flash |
| LMCA | 24.3% | 50.4% | Gemini 3.7 Flash |
| Furniture assembly | Not measured | 26.7% | Only Gemini 3.7 Flash measured |
| LMArena Text | Not measured | 1489 | Only Gemini 3.7 Flash measured |
| LMArena Text: instruction following | Not measured | 1484 | Only Gemini 3.7 Flash measured |
| LMArena Text: creative writing | Not measured | 1488 | Only Gemini 3.7 Flash measured |
| LMArena Vision | Not measured | 1314 | Only Gemini 3.7 Flash measured |
| LMArena Text: English | Not measured | 1483 | Only Gemini 3.7 Flash measured |
| LMArena Text: non-English | Not measured | 1487 | Only Gemini 3.7 Flash measured |
| LMArena Text: Chinese | Not measured | 1552 | Only Gemini 3.7 Flash measured |
| LMArena Text: German | Not measured | 1506 | Only Gemini 3.7 Flash measured |
| LMArena Text: Japanese | Not measured | 1511 | Only Gemini 3.7 Flash measured |
| LMArena Text: Korean | Not measured | 1481 | Only Gemini 3.7 Flash measured |
| LMArena Text: French | Not measured | 1500 | Only Gemini 3.7 Flash measured |
| LMArena Text: Spanish | Not measured | 1495 | Only Gemini 3.7 Flash measured |
| LMArena Text: Russian | Not measured | 1515 | Only Gemini 3.7 Flash measured |
| LMArena Text: Polish | Not measured | 1503 | Only Gemini 3.7 Flash measured |
| LMArena Text: multi-turn | Not measured | 1485 | Only Gemini 3.7 Flash measured |
| LMArena Text: longer queries | Not measured | 1492 | Only Gemini 3.7 Flash measured |
| LMArena Text: writing and language | Not measured | 1491 | Only Gemini 3.7 Flash measured |
| LMArena Text: entertainment and media | Not measured | 1477 | Only Gemini 3.7 Flash measured |
| LMArena Vision: English | Not measured | 1309 | Only Gemini 3.7 Flash measured |
| LMArena Vision: Chinese | Not measured | 1394 | Only Gemini 3.7 Flash measured |
| LMArena Vision: reading text | Not measured | 1322 | Only Gemini 3.7 Flash measured |
| LMArena Vision: humor | Not measured | 1299 | Only Gemini 3.7 Flash measured |
| LMArena Vision: creative writing | Not measured | 1312 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 | Gemini 3.7 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 V3.1$0.0013Fits in one request
Gemini 3.7 Flash$0.0026Fits in one request
DeepSeek V3.1 costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.1$0.032Fits in one request
Gemini 3.7 Flash$0.049Fits in one request
DeepSeek V3.1 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.1$0.125Exceeds the context window
Gemini 3.7 Flash$0.188Fits in one request
DeepSeek V3.1 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 V3.1 | Google Gemini 3.7 Flash |
|---|---|---|
| Maker | DeepSeek | |
| Weights | Open weights | No public weights listed |
| Released | August 21, 2025 | August 13, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.55 | $0.75 |
| Output $/Mtok | $1.50 | $3.75 |
| Coding index | Not benchmarked | 58.0 |
| Independent measurements behind it | 0 | 6 |
| Cost per solved task | Not computable | $1.78 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3.1 better than Gemini 3.7 Flash for coding?
Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; DeepSeek V3.1 has none, so the two cannot be ranked on coding. Pick DeepSeek V3.1 for output tokens 2.5x cheaper ($1.50 vs $3.75 per million).
Which is cheaper, DeepSeek V3.1 or Gemini 3.7 Flash?
DeepSeek V3.1 costs $0.55 per million input tokens and $1.50 per million output tokens; Gemini 3.7 Flash costs $0.75 and $3.75. Cost per solved task is known for Gemini 3.7 Flash only.
Which has the bigger context window, DeepSeek V3.1 or Gemini 3.7 Flash?
Gemini 3.7 Flash, with 1.05M tokens against 164K.
How many benchmarks is the DeepSeek V3.1 vs Gemini 3.7 Flash comparison based on?
10 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.1's coding index rests on 0 independent benchmarks and Gemini 3.7 Flash's on 6. Where only one model has a result, the page says so instead of naming a winner.