DeepSeek V4 Flash 0731 vs Gemini 2.5 Flash
DeepSeek V4 Flash 0731 leads Gemini 2.5 Flash on the Artificial Analysis Intelligence Index, 34.3 to 15.5, and DeepSeek V4 Flash 0731 costs 8.9x less per output token ($0.28 vs $2.50 per million). Updated October 21, 2026; 19 benchmarks have a result for both.
DeepSeek V4 Flash 0731 or Gemini 2.5 Flash: which to pick
Only DeepSeek V4 Flash 0731 has a coding score, 51.8 on the Vibe Coding Index; Gemini 2.5 Flash has none, so the two cannot be ranked on coding.
Pick Gemini 2.5 Flash for work measured by MedScribe (Vals AI), where it leads.
- Shared results
- 19
- DeepSeek V4 Flash 0731 only
- 36
- Gemini 2.5 Flash only
- 50
- Like-for-like categories
- 5 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 Flash 0731 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 34.3 against 15.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Flash 0731 has a AA Agentic Index result, 41.0.
Directional only
Reasoning
GPQA Diamond
No call
Only DeepSeek V4 Flash 0731 has a GPQA Diamond result, 89.9%.
Directional only
Knowledge
MMLU Pro
No call
Only DeepSeek V4 Flash 0731 has a MMLU Pro result, 86.2%.
Directional only
Web design
Design Arena: websites
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 1238 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 Flash 0731
DeepSeek V4 Flash 0731 $0.0003, Gemini 2.5 Flash $0.0015 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 $0.01, Gemini 2.5 Flash $0.466.
Published attempt cost and pass rate
At a glance
- Coding index
- DeepSeek V4 Flash 0731 51.8 from 4 benchmarks, Gemini 2.5 Flash not benchmarked.
- Widest category
- Reasoning, 34.5 points apart on average over 5 shared benchmarks.
- Widest single gap
- ARC-AGI-2: DeepSeek V4 Flash 0731 61.4% against Gemini 2.5 Flash 2.5%, 58.8 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Flash 0731 $0.28 against Gemini 2.5 Flash $2.50 per million output tokens, 8.9x 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 Flash 0731 | Bars | Gemini 2.5 Flash | Ties |
|---|---|---|---|---|
| Intelligence | 2 | 0 | ||
| Reasoning | 5 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 7 | 0 | ||
| General | 3 | 1 | ||
| All shared boards | 18 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index21 boards, none shared
| Benchmark | DeepSeek V4 Flash 0731 | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 28.7% | Only Gemini 2.5 Flash measured |
| AA Coding Index | 69.1 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| LiveCodeBench (Vals AI) | 87.3% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| SWE-bench Verified (Vals AI) | 88.8% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Terminal-Bench 4 (Vals AI) | 18.7% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Vibe Code Bench (Vals AI) | 74.7% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Code migration (Vals AI) | 38.6% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| IOI (Vals AI) | 32.7% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Terminal-Bench 2.1 (Vals AI) | 67.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| SkillsBench (Vals AI) | 50.7% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| CyberBench (Vals AI) | 72.1% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 69.5% | Only Gemini 2.5 Flash measured |
| SciCode | 50.3% | Not measured | Only DeepSeek V4 Flash 0731 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 | 18.8% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| WeirdML | 63.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| ALE-Bench | 1306.1 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| LMArena Text: coding | Not measured | 1423 | Only Gemini 2.5 Flash measured |
| LMArena Text: software and IT | Not measured | 1425 | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Flash 0731 | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 34.3 | 15.5 | DeepSeek V4 Flash 0731 |
| Epoch Capabilities Index | 154.8 | 142.9 | DeepSeek V4 Flash 0731 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | DeepSeek V4 Flash 0731 | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 41.0 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Finance Agent (Vals AI) | 49.5% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Tax Agent Bench (Vals AI) | 28.1% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Legal Research Bench (Vals AI) | 30.3% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Excel Modeling Benchmark (Vals AI) | 57.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| BioMysteryBench (Vals AI) | 64.4% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| τ²-Bench Telecom | Not measured | 31.6% | Only Gemini 2.5 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 |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | DeepSeek V4 Flash 0731 | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | 89.9% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| GPQA Diamond (Artificial Analysis run) | 90.8% | 79.0% | DeepSeek V4 Flash 0731 |
| Humanity's Last Exam (Artificial Analysis run) | 38.6% | 12.1% | DeepSeek V4 Flash 0731 |
| GPQA Diamond (Epoch AI run) | 91.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| ARC-AGI | 89.0% | 33.3% | DeepSeek V4 Flash 0731 |
| ARC-AGI-2 | 61.4% | 2.5% | DeepSeek V4 Flash 0731 |
| SimpleBench | 61.1% | 41.2% | DeepSeek V4 Flash 0731 |
| Chess puzzles | 32.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Mystery game puzzles | 34.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| LMArena Text: hard prompts | Not measured | 1422 | Only Gemini 2.5 Flash measured |
| LMArena Text: expert | Not measured | 1426 | Only Gemini 2.5 Flash measured |
| LMArena Text: hard prompts in English | Not measured | 1420 | Only Gemini 2.5 Flash measured |
| LMArena Vision: diagrams | Not measured | 1245 | Only Gemini 2.5 Flash measured |
| LMArena Vision: homework | Not measured | 1244 | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | DeepSeek V4 Flash 0731 | 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 | 94.4% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| FrontierMath, tiers 1 to 3 | 57.5% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| FrontierMath, tier 4 | 24.4% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| ProofBench | 56.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| LMArena Text: math | Not measured | 1411 | Only Gemini 2.5 Flash measured |
| LMArena Text: mathematical work | Not measured | 1422 | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Flash 0731 | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| MMLU Pro | 86.2% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| LegalBench (Vals AI) | 77.7% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| CorpFin (Vals AI) | 61.9% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| TaxEval (Vals AI) | 70.7% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| MedCode (Vals AI) | 41.4% | 40.4% | DeepSeek V4 Flash 0731 |
| MMLU Pro (Artificial Analysis run) | Not measured | 83.2% | Only Gemini 2.5 Flash measured |
| SimpleQA Verified | 33.6% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| LMArena Text: science | Not measured | 1433 | Only Gemini 2.5 Flash measured |
| LMArena Text: medicine and healthcare | Not measured | 1428 | Only Gemini 2.5 Flash measured |
| LMArena Text: legal and government | Not measured | 1430 | Only Gemini 2.5 Flash measured |
| LMArena Text: business and finance | Not measured | 1404 | Only Gemini 2.5 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 index70
| Benchmark | DeepSeek V4 Flash 0731 | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1238 | 1074 | DeepSeek V4 Flash 0731 |
| Design Arena: UI components | 1235 | 1005 | DeepSeek V4 Flash 0731 |
| Design Arena: game dev | 1208 | 1005 | DeepSeek V4 Flash 0731 |
| Design Arena: data viz | 1180 | 1060 | DeepSeek V4 Flash 0731 |
| Design Arena: 3D | 1209 | 1021 | DeepSeek V4 Flash 0731 |
| Design Arena: all code categories | 1230 | 1059 | DeepSeek V4 Flash 0731 |
| Design Arena: SVG | 1185 | 1020 | DeepSeek V4 Flash 0731 |
| Design Arena: ASCII art | 1090 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | DeepSeek V4 Flash 0731 | Gemini 2.5 Flash | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 44.8% | Only Gemini 2.5 Flash measured |
| MedScribe (Vals AI) | 80.4% | 83.0% | Gemini 2.5 Flash |
| IFBench | Not measured | 50.3% | Only Gemini 2.5 Flash measured |
| Long context reasoning (AA-LCR) | 79.7% | 65.3% | DeepSeek V4 Flash 0731 |
| DTBench | 90.9% | 76.5% | DeepSeek V4 Flash 0731 |
| LMCA | 41.7% | 27.5% | DeepSeek V4 Flash 0731 |
| LMArena Text | Not measured | 1417 | Only Gemini 2.5 Flash measured |
| LMArena Text: instruction following | Not measured | 1405 | Only Gemini 2.5 Flash measured |
| LMArena Text: creative writing | Not measured | 1400 | Only Gemini 2.5 Flash measured |
| LMArena Vision | Not measured | 1235 | Only Gemini 2.5 Flash measured |
| LMArena Text: English | Not measured | 1418 | Only Gemini 2.5 Flash measured |
| LMArena Text: non-English | Not measured | 1409 | Only Gemini 2.5 Flash measured |
| LMArena Text: Chinese | Not measured | 1449 | Only Gemini 2.5 Flash measured |
| LMArena Text: German | Not measured | 1417 | Only Gemini 2.5 Flash measured |
| LMArena Text: Japanese | Not measured | 1396 | Only Gemini 2.5 Flash measured |
| LMArena Text: Korean | Not measured | 1385 | Only Gemini 2.5 Flash measured |
| LMArena Text: French | Not measured | 1432 | Only Gemini 2.5 Flash measured |
| LMArena Text: Spanish | Not measured | 1422 | Only Gemini 2.5 Flash measured |
| LMArena Text: Russian | Not measured | 1415 | Only Gemini 2.5 Flash measured |
| LMArena Text: Polish | Not measured | 1413 | Only Gemini 2.5 Flash measured |
| LMArena Text: multi-turn | Not measured | 1408 | Only Gemini 2.5 Flash measured |
| LMArena Text: longer queries | Not measured | 1419 | Only Gemini 2.5 Flash measured |
| LMArena Text: writing and language | Not measured | 1405 | Only Gemini 2.5 Flash measured |
| LMArena Text: entertainment and media | Not measured | 1393 | Only Gemini 2.5 Flash measured |
| LMArena Vision: English | Not measured | 1239 | Only Gemini 2.5 Flash measured |
| LMArena Vision: Chinese | Not measured | 1284 | Only Gemini 2.5 Flash measured |
| LMArena Vision: reading text | Not measured | 1237 | Only Gemini 2.5 Flash measured |
| LMArena Vision: humor | Not measured | 1225 | Only Gemini 2.5 Flash measured |
| 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 | Not measured | 1241 | Only Gemini 2.5 Flash measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Flash 0731 | 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 Flash 0731 costs less
Repository review
50K input + 3K output tokens
DeepSeek V4 Flash 0731 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4 Flash 0731 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 Flash 0731 | Google Gemini 2.5 Flash |
|---|---|---|
| Maker | DeepSeek | |
| Weights | Open weights | No public weights listed |
| Released | July 31, 2026 | June 17, 2025 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.14 | $0.30 |
| Output $/Mtok | $0.28 | $2.50 |
| Coding index | 51.8 | Not benchmarked |
| Independent measurements behind it | 4 | 0 |
| Cost per solved task | $0.01 | $0.466 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Flash 0731 better than Gemini 2.5 Flash for coding?
Only DeepSeek V4 Flash 0731 has a coding score, 51.8 on the Vibe Coding Index; Gemini 2.5 Flash has none, so the two cannot be ranked on coding. Pick Gemini 2.5 Flash for work measured by MedScribe (Vals AI), where it leads.
Which is cheaper, DeepSeek V4 Flash 0731 or Gemini 2.5 Flash?
DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.28 per million output tokens; Gemini 2.5 Flash costs $0.30 and $2.50. Per solved SWE-bench Verified task, DeepSeek V4 Flash 0731 costs $0.01 and Gemini 2.5 Flash $0.466.
Which has the bigger context window, DeepSeek V4 Flash 0731 or Gemini 2.5 Flash?
Neither: both take 1.05M tokens.
How many benchmarks is the DeepSeek V4 Flash 0731 vs Gemini 2.5 Flash comparison based on?
19 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash 0731's coding index rests on 4 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.