DeepSeek V4 Flash 0731 vs Gemma 3 4B
DeepSeek V4 Flash 0731 leads Gemma 3 4B on the Artificial Analysis Intelligence Index, 34.3 to 4.8, and Gemma 3 4B costs 5.3x less per output token ($0.075 vs $0.396 per million). Updated October 22, 2026; 10 benchmarks have a result for both.
DeepSeek V4 Flash 0731 or Gemma 3 4B: which to pick
Only DeepSeek V4 Flash 0731 has a coding score, 51.8 on the Vibe Coding Index; Gemma 3 4B has none, so the two cannot be ranked on coding.
Pick Gemma 3 4B for output tokens 5.3x cheaper ($0.075 vs $0.396 per million).
- Shared results
- 10
- DeepSeek V4 Flash 0731 only
- 45
- Gemma 3 4B only
- 32
- 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 4.8.
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
No call
Only DeepSeek V4 Flash 0731 has a Design Arena: websites result, 1237.
Directional only
Long documents
Listed context window
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 3 4B
DeepSeek V4 Flash 0731 $0.0003, Gemma 3 4B $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only DeepSeek V4 Flash 0731 has the number, $0.01.
Directional only
At a glance
- Coding index
- DeepSeek V4 Flash 0731 51.8 from 4 benchmarks, Gemma 3 4B not benchmarked.
- Widest category
- Math, 86.9 points apart on average over 1 shared benchmark.
- Widest single gap
- OTIS Mock AIME: DeepSeek V4 Flash 0731 94.4% against Gemma 3 4B 7.5%, 86.9 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Flash 0731 $0.396 against Gemma 3 4B $0.075 per million output tokens, 5.3x apart.
- Context window
- DeepSeek V4 Flash 0731 takes 1.05M tokens, Gemma 3 4B 131K.
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 | Gemma 3 4B | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 1 | 0 | ||
| General | 3 | 0 | ||
| All shared boards | 10 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | DeepSeek V4 Flash 0731 | Gemma 3 4B | Leader |
|---|---|---|---|
| AA Coding Index | 69.1 | 2.7 | DeepSeek V4 Flash 0731 |
| 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 | 11.2% | Only Gemma 3 4B measured |
| SciCode | 50.3% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 0.8% | Only Gemma 3 4B 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 | 1230 | Only Gemma 3 4B measured |
| LMArena Text: software and IT | Not measured | 1269 | Only Gemma 3 4B measured |
| SciCode | Not measured | 0.0% | Only Gemma 3 4B measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Flash 0731 | Gemma 3 4B | Leader |
|---|---|---|---|
| AA Intelligence Index | 34.3 | 4.8 | DeepSeek V4 Flash 0731 |
| Epoch Capabilities Index | 154.8 | 115.9 | DeepSeek V4 Flash 0731 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | DeepSeek V4 Flash 0731 | Gemma 3 4B | 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 | 5.0% | Only Gemma 3 4B measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 19.6% | Only Gemma 3 4B measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | DeepSeek V4 Flash 0731 | Gemma 3 4B | Leader |
|---|---|---|---|
| GPQA Diamond | 89.9% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| GPQA Diamond (Artificial Analysis run) | 90.8% | 29.1% | DeepSeek V4 Flash 0731 |
| Humanity's Last Exam (Artificial Analysis run) | 38.6% | 5.3% | DeepSeek V4 Flash 0731 |
| GPQA Diamond (Epoch AI run) | 91.0% | 23.2% | DeepSeek V4 Flash 0731 |
| ARC-AGI | 89.0% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| ARC-AGI-2 | 61.4% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| SimpleBench | 61.1% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| 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 | 1253 | Only Gemma 3 4B measured |
| LMArena Text: expert | Not measured | 1223 | Only Gemma 3 4B measured |
| LMArena Text: hard prompts in English | Not measured | 1253 | Only Gemma 3 4B measured |
| Kagi LLM Benchmark | Not measured | 25.2% | Only Gemma 3 4B measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Flash 0731 | Gemma 3 4B | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 12.7 | Only Gemma 3 4B measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 12.7% | Only Gemma 3 4B measured |
| OTIS Mock AIME | 94.4% | 7.5% | DeepSeek V4 Flash 0731 |
| 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 | 1239 | Only Gemma 3 4B measured |
| LMArena Text: mathematical work | Not measured | 1256 | Only Gemma 3 4B measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | DeepSeek V4 Flash 0731 | Gemma 3 4B | 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% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 41.7% | Only Gemma 3 4B measured |
| SimpleQA Verified | 33.6% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| LMArena Text: science | Not measured | 1306 | Only Gemma 3 4B measured |
| LMArena Text: medicine and healthcare | Not measured | 1342 | Only Gemma 3 4B measured |
| LMArena Text: legal and government | Not measured | 1327 | Only Gemma 3 4B measured |
| LMArena Text: business and finance | Not measured | 1311 | Only Gemma 3 4B measured |
| Neither model has a result on the other 7 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | DeepSeek V4 Flash 0731 | Gemma 3 4B | Leader |
|---|---|---|---|
| Design Arena: websites | 1237 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: UI components | 1233 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: game dev | 1207 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: data viz | 1180 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: 3D | 1208 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: all code categories | 1229 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| Design Arena: SVG | 1184 | Not measured | Only DeepSeek V4 Flash 0731 measured |
| 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 index30
| Benchmark | DeepSeek V4 Flash 0731 | Gemma 3 4B | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 80.4% | Not measured | Only DeepSeek V4 Flash 0731 measured |
| IFBench | Not measured | 28.3% | Only Gemma 3 4B measured |
| Long context reasoning (AA-LCR) | 79.7% | 6.7% | DeepSeek V4 Flash 0731 |
| DTBench | 90.9% | 50.9% | DeepSeek V4 Flash 0731 |
| LMCA | 41.7% | 2.8% | DeepSeek V4 Flash 0731 |
| LMArena Text | Not measured | 1291 | Only Gemma 3 4B measured |
| LMArena Text: instruction following | Not measured | 1239 | Only Gemma 3 4B measured |
| LMArena Text: creative writing | Not measured | 1270 | Only Gemma 3 4B measured |
| LMArena Text: English | Not measured | 1300 | Only Gemma 3 4B measured |
| LMArena Text: non-English | Not measured | 1273 | Only Gemma 3 4B measured |
| LMArena Text: German | Not measured | 1281 | Only Gemma 3 4B measured |
| LMArena Text: Russian | Not measured | 1294 | Only Gemma 3 4B measured |
| LMArena Text: multi-turn | Not measured | 1255 | Only Gemma 3 4B measured |
| LMArena Text: longer queries | Not measured | 1273 | Only Gemma 3 4B measured |
| LMArena Text: writing and language | Not measured | 1288 | Only Gemma 3 4B measured |
| LMArena Text: entertainment and media | Not measured | 1233 | Only Gemma 3 4B measured |
| Neither model has a result on the other 30 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Flash 0731 | Gemma 3 4B | 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
Gemma 3 4B costs less
Repository review
50K input + 3K output tokens
Gemma 3 4B costs less
Agent loop
200K input + 10K output tokens
Gemma 3 4B 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 Gemma 3 4B |
|---|---|---|
| Maker | DeepSeek | |
| Weights | Open weights | Open weights |
| Released | July 31, 2026 | March 13, 2025 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $0.14 | $0.045 |
| Output $/Mtok | $0.396 | $0.075 |
| Coding index | 51.8 | Not benchmarked |
| Independent measurements behind it | 4 | 0 |
| Cost per solved task | $0.01 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Flash 0731 better than Gemma 3 4B for coding?
Only DeepSeek V4 Flash 0731 has a coding score, 51.8 on the Vibe Coding Index; Gemma 3 4B has none, so the two cannot be ranked on coding. Pick Gemma 3 4B for output tokens 5.3x cheaper ($0.075 vs $0.396 per million).
Which is cheaper, DeepSeek V4 Flash 0731 or Gemma 3 4B?
DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.396 per million output tokens; Gemma 3 4B costs $0.045 and $0.075. Cost per solved task is known for DeepSeek V4 Flash 0731 only.
Which has the bigger context window, DeepSeek V4 Flash 0731 or Gemma 3 4B?
DeepSeek V4 Flash 0731, with 1.05M tokens against 131K.
How many benchmarks is the DeepSeek V4 Flash 0731 vs Gemma 3 4B comparison based on?
10 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash 0731's coding index rests on 4 independent benchmarks and Gemma 3 4B's on 0. Where only one model has a result, the page says so instead of naming a winner.