DeepSeek V3 0324 vs Gemma 4 31B
Updated October 21, 2026. 15 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick DeepSeek V3 0324 for coding: it scores 42.0 on the Vibe Coding Index against 38.3 for Gemma 4 31B, though on 1 benchmark against 2.
Pick Gemma 4 31B when output tokens cost 2.8x less, or when the context window is larger, 262K against 164K tokens.
- Shared results
- 15
- DeepSeek V3 0324 only
- 20
- Gemma 4 31B only
- 53
- 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 V3 0324
DeepSeek V3 0324 scores 42.0 against 38.3.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
Gemma 4 31B
Gemma 4 31B leads, 14.7 against 9.7.
Same board, both measured
Agentic work
AA Agentic Index
Gemma 4 31B
Gemma 4 31B leads, 4.2 against 0.8.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only DeepSeek V3 0324 has a GPQA Diamond result, 61.6%.
Directional only
Math
AIME
No call
Only DeepSeek V3 0324 has a AIME result, 52.2%.
Directional only
Knowledge
MMLU Pro
No call
Only DeepSeek V3 0324 has a MMLU Pro result, 79.5%.
Directional only
Long documents
Listed context window
Gemma 4 31B
Gemma 4 31B takes 262K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 31B
DeepSeek V3 0324 $0.0009, Gemma 4 31B $0.0004 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3 0324 42.0 from 1 benchmark, Gemma 4 31B 38.3 from 2 benchmarks.
- Widest category
- Math, 35.6 points apart on average over 1 shared benchmark.
- Widest single gap
- OTIS Mock AIME: DeepSeek V3 0324 37.8% against Gemma 4 31B 73.3%, 35.6 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 0324 $1.14 against Gemma 4 31B $0.40 per million output tokens, 2.8x apart.
- Context window
- DeepSeek V3 0324 takes 164K tokens, Gemma 4 31B 262K.
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 0324 | Bars | Gemma 4 31B | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 1 | ||
| General | 0 | 4 | ||
| All shared boards | 0 | 15 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index04
| Benchmark | DeepSeek V3 0324 | Gemma 4 31B | Leader |
|---|---|---|---|
| SWE-bench Verified | 42.0% | Not measured | Only DeepSeek V3 0324 measured |
| LiveBench coding | Not measured | 49.0% | Only Gemma 4 31B measured |
| LMArena WebDev | Not measured | 1367 | Only Gemma 4 31B measured |
| AA Coding Index | 21.2 | 43.4 | Gemma 4 31B |
| LiveCodeBench (Vals AI) | 65.5% | Not measured | Only DeepSeek V3 0324 measured |
| LiveCodeBench (Artificial Analysis run) | 40.5% | Not measured | Only DeepSeek V3 0324 measured |
| SciCode | 39.0% | 45.5% | Gemma 4 31B |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | 36.4% | Gemma 4 31B |
| WeirdML | 36.1% | 52.3% | Gemma 4 31B |
| ALE-Bench | Not measured | 925.5 | Only Gemma 4 31B measured |
| LMArena Text: coding | Not measured | 1459 | Only Gemma 4 31B measured |
| LMArena Text: software and IT | Not measured | 1463 | Only Gemma 4 31B measured |
| LMArena WebDev: React | Not measured | 1359 | Only Gemma 4 31B measured |
| LMArena WebDev: HTML | Not measured | 1380 | Only Gemma 4 31B measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | Gemma 4 31B | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.7 | 14.7 | Gemma 4 31B |
| Epoch Capabilities Index | Not measured | 143.0 | Only Gemma 4 31B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3 0324 | Gemma 4 31B | Leader |
|---|---|---|---|
| AA Agentic Index | 0.8 | 4.2 | Gemma 4 31B |
| LiveBench research | Not measured | 44.4% | Only Gemma 4 31B measured |
| LiveBench browser | Not measured | 4.0% | Only Gemma 4 31B measured |
| LiveBench long agentic | Not measured | 13.3% | Only Gemma 4 31B measured |
| τ²-Bench Telecom | 47.1% | 65.5% | Gemma 4 31B |
| METR time horizons | 49.6% | Not measured | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V3 0324 | Gemma 4 31B | Leader |
|---|---|---|---|
| GPQA Diamond | 61.6% | Not measured | Only DeepSeek V3 0324 measured |
| LiveBench reasoning | Not measured | 68.3% | Only Gemma 4 31B measured |
| GPQA Diamond (Artificial Analysis run) | 65.5% | 85.7% | Gemma 4 31B |
| Humanity's Last Exam (Artificial Analysis run) | 4.7% | 23.6% | Gemma 4 31B |
| GPQA Diamond (Epoch AI run) | 67.6% | 75.8% | Gemma 4 31B |
| SimpleBench | 27.2% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: hard prompts | Not measured | 1448 | Only Gemma 4 31B measured |
| LMArena Text: expert | Not measured | 1464 | Only Gemma 4 31B measured |
| LMArena Text: hard prompts in English | Not measured | 1456 | Only Gemma 4 31B measured |
| LMArena Vision: diagrams | Not measured | 1283 | Only Gemma 4 31B measured |
| LMArena Vision: homework | Not measured | 1310 | Only Gemma 4 31B measured |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | Gemma 4 31B | Leader |
|---|---|---|---|
| AIME | 52.2% | Not measured | Only DeepSeek V3 0324 measured |
| MATH 500 (Vals AI) | 88.6% | Not measured | Only DeepSeek V3 0324 measured |
| MGSM (Vals AI) | 91.7% | Not measured | Only DeepSeek V3 0324 measured |
| AA Math Index | 41.0 | Not measured | Only DeepSeek V3 0324 measured |
| AIME 2025 (Artificial Analysis run) | 41.0% | Not measured | Only DeepSeek V3 0324 measured |
| OTIS Mock AIME | 37.8% | 73.3% | Gemma 4 31B |
| MATH level 5 | 75.5% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: math | Not measured | 1463 | Only Gemma 4 31B measured |
| LMArena Text: mathematical work | Not measured | 1465 | Only Gemma 4 31B measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | DeepSeek V3 0324 | Gemma 4 31B | Leader |
|---|---|---|---|
| MMLU Pro | 79.5% | Not measured | Only DeepSeek V3 0324 measured |
| LegalBench (Vals AI) | 77.7% | Not measured | Only DeepSeek V3 0324 measured |
| CaseLaw (Vals AI) | Not measured | 52.6% | Only Gemma 4 31B measured |
| CorpFin (Vals AI) | 54.7% | Not measured | Only DeepSeek V3 0324 measured |
| TaxEval (Vals AI) | 71.1% | Not measured | Only DeepSeek V3 0324 measured |
| MortgageTax (Vals AI) | Not measured | 61.4% | Only Gemma 4 31B measured |
| MedQA (Vals AI) | 82.0% | Not measured | Only DeepSeek V3 0324 measured |
| MMLU Pro (Artificial Analysis run) | 81.9% | Not measured | Only DeepSeek V3 0324 measured |
| SimpleQA Verified | Not measured | 10.4% | Only Gemma 4 31B measured |
| LMArena Text: science | Not measured | 1457 | Only Gemma 4 31B measured |
| LMArena Text: medicine and healthcare | Not measured | 1451 | Only Gemma 4 31B measured |
| LMArena Text: legal and government | Not measured | 1438 | Only Gemma 4 31B measured |
| LMArena Text: business and finance | Not measured | 1430 | Only Gemma 4 31B measured |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | DeepSeek V3 0324 | Gemma 4 31B | Leader |
|---|---|---|---|
| LiveBench design | Not measured | 58.4% | Only Gemma 4 31B measured |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | DeepSeek V3 0324 | Gemma 4 31B | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 53.3% | Only Gemma 4 31B measured |
| SAGE (Vals AI) | Not measured | 55.0% | Only Gemma 4 31B measured |
| IFBench | 41.0% | 75.6% | Gemma 4 31B |
| Long context reasoning (AA-LCR) | 40.7% | 69.7% | Gemma 4 31B |
| DTBench | 64.8% | 82.7% | Gemma 4 31B |
| LMCA | 15.5% | 39.3% | Gemma 4 31B |
| Fiction.LiveBench | 50.0% | Not measured | Only DeepSeek V3 0324 measured |
| Creative writing (Lech Mazur) | 77.0% | Not measured | Only DeepSeek V3 0324 measured |
| Surface Evolver Bench | Not measured | 30.6% | Only Gemma 4 31B measured |
| LMArena Text | Not measured | 1443 | Only Gemma 4 31B measured |
| LMArena Text: instruction following | Not measured | 1433 | Only Gemma 4 31B measured |
| LMArena Text: creative writing | Not measured | 1417 | Only Gemma 4 31B measured |
| LMArena Vision | Not measured | 1276 | Only Gemma 4 31B measured |
| LMArena Text: English | Not measured | 1451 | Only Gemma 4 31B measured |
| LMArena Text: non-English | Not measured | 1430 | Only Gemma 4 31B measured |
| LMArena Text: Chinese | Not measured | 1475 | Only Gemma 4 31B measured |
| LMArena Text: French | Not measured | 1436 | Only Gemma 4 31B measured |
| LMArena Text: Spanish | Not measured | 1442 | Only Gemma 4 31B measured |
| LMArena Text: Russian | Not measured | 1460 | Only Gemma 4 31B measured |
| LMArena Text: Polish | Not measured | 1433 | Only Gemma 4 31B measured |
| LMArena Text: multi-turn | Not measured | 1452 | Only Gemma 4 31B measured |
| LMArena Text: longer queries | Not measured | 1446 | Only Gemma 4 31B measured |
| LMArena Text: writing and language | Not measured | 1432 | Only Gemma 4 31B measured |
| LMArena Text: entertainment and media | Not measured | 1405 | Only Gemma 4 31B measured |
| LMArena Vision: English | Not measured | 1271 | Only Gemma 4 31B measured |
| LMArena Vision: Chinese | Not measured | 1326 | Only Gemma 4 31B measured |
| LMArena Vision: reading text | Not measured | 1282 | Only Gemma 4 31B measured |
| LMArena Vision: humor | Not measured | 1280 | Only Gemma 4 31B measured |
| LMArena Vision: captioning | Not measured | 1218 | Only Gemma 4 31B measured |
| LMArena Vision: recognizing things | Not measured | 1226 | Only Gemma 4 31B measured |
| LMArena Vision: creative writing | Not measured | 1285 | Only Gemma 4 31B measured |
| LMArena Document | Not measured | 1425 | Only Gemma 4 31B measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 0324 | Gemma 4 31B | 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 4 31B costs less
Repository review
50K input + 3K output tokens
Gemma 4 31B costs less
Agent loop
200K input + 10K output tokens
Gemma 4 31B 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 0324 | Google Gemma 4 31B |
|---|---|---|
| Maker | DeepSeek | |
| Weights | Open weights | Open weights |
| Released | March 24, 2025 | April 2, 2026 |
| Context window | 164K | 262K |
| Input $/Mtok | $0.29 | $0.20 |
| Output $/Mtok | $1.14 | $0.40 |
| Coding index | 42.0 | 38.3 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3 0324 better than Gemma 4 31B for coding?
Pick DeepSeek V3 0324 for coding: it scores 42.0 on the Vibe Coding Index against 38.3 for Gemma 4 31B, though on 1 benchmark against 2. Pick Gemma 4 31B when output tokens cost 2.8x less, or when the context window is larger, 262K against 164K tokens.
Which is cheaper, DeepSeek V3 0324 or Gemma 4 31B?
DeepSeek V3 0324 costs $0.29 per million input tokens and $1.14 per million output tokens; Gemma 4 31B costs $0.20 and $0.40. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3 0324 or Gemma 4 31B?
Gemma 4 31B, with 262K tokens against 164K.
How many benchmarks is the DeepSeek V3 0324 vs Gemma 4 31B comparison based on?
15 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3 0324's coding index rests on 1 independent benchmark and Gemma 4 31B's on 2. Where only one model has a result, the page says so instead of naming a winner.