DeepSeek V4 Pro 0813 vs Gemma 4 31B
DeepSeek V4 Pro 0813 leads Gemma 4 31B on coding, 56.1 to 39.0 on the Vibe Coding Index, and Gemma 4 31B costs 4.9x less per output token ($0.40 vs $1.98 per million). Updated October 22, 2026; 42 benchmarks have a result for both.
DeepSeek V4 Pro 0813 or Gemma 4 31B: which to pick
Pick DeepSeek V4 Pro 0813 for coding: it scores 56.1 on the Vibe Coding Index against 39.0 for Gemma 4 31B.
Pick Gemma 4 31B for output tokens 4.9x cheaper ($0.40 vs $1.98 per million) and work measured by LMArena Text: software and IT or LMArena Text: expert, where it leads.
- Shared results
- 42
- DeepSeek V4 Pro 0813 only
- 36
- Gemma 4 31B only
- 29
- 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
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 scores 56.1 against 39.0.
5 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 36.0 against 14.7.
Same board, both measured
Agentic work
AA Agentic Index
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 41.3 against 4.2.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only DeepSeek V4 Pro 0813 has a GPQA Diamond result, 92.4%.
Directional only
Knowledge
MMLU Pro
No call
Only DeepSeek V4 Pro 0813 has a MMLU Pro result, 87.0%.
Directional only
General
Vals Index
No call
Only DeepSeek V4 Pro 0813 has a Vals Index result, 53.0%.
Directional only
Long documents
Listed context window
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 31B
DeepSeek V4 Pro 0813 $0.0016, Gemma 4 31B $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only DeepSeek V4 Pro 0813 has the number, $0.10.
Directional only
At a glance
- Coding index
- DeepSeek V4 Pro 0813 56.1 from 5 benchmarks, Gemma 4 31B 39.0 from 2 benchmarks.
- Widest category
- Agentic work, 37.1 points apart on average over 1 shared benchmark.
- Widest single gap
- SimpleQA Verified: DeepSeek V4 Pro 0813 52.9% against Gemma 4 31B 10.4%, 42.5 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Pro 0813 $1.98 against Gemma 4 31B $0.40 per million output tokens, 4.9x apart.
- Context window
- DeepSeek V4 Pro 0813 takes 1.05M 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 V4 Pro 0813 | Bars | Gemma 4 31B | Ties |
|---|---|---|---|---|
| Coding | 8 | 1 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 5 | 1 | ||
| Math | 1 | 2 | ||
| Knowledge | 3 | 2 | ||
| General | 14 | 2 | ||
| All shared boards | 34 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index81
| Benchmark | DeepSeek V4 Pro 0813 | Gemma 4 31B | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 49.0% | Only Gemma 4 31B measured |
| LMArena WebDev | 1582 | 1367 | DeepSeek V4 Pro 0813 |
| AA Coding Index | 68.8 | 43.4 | DeepSeek V4 Pro 0813 |
| LiveCodeBench (Vals AI) | 87.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SWE-bench Verified (Vals AI) | 96.4% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Terminal-Bench 4 (Vals AI) | 14.1% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Vibe Code Bench (Vals AI) | 82.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Code migration (Vals AI) | 41.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| IOI (Vals AI) | 51.6% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Terminal-Bench 2.1 (Vals AI) | 54.7% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Vibe Code Bench 1-100 (Vals AI) | 17.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SkillsBench (Vals AI) | 53.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| CyberBench (Vals AI) | 72.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SciCode | 51.0% | 45.5% | DeepSeek V4 Pro 0813 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 36.4% | Only Gemma 4 31B measured |
| FrontierCode | 28.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| WeirdML | 66.2% | 52.3% | DeepSeek V4 Pro 0813 |
| ALE-Bench | 1403.2 | 925.5 | DeepSeek V4 Pro 0813 |
| LMArena Text: coding | 1469 | 1459 | DeepSeek V4 Pro 0813 |
| LMArena Text: software and IT | 1462 | 1463 | Gemma 4 31B |
| LMArena WebDev: React | 1588 | 1359 | DeepSeek V4 Pro 0813 |
| LMArena WebDev: HTML | 1566 | 1380 | DeepSeek V4 Pro 0813 |
| SciCode | Not measured | 8.9% | Only Gemma 4 31B 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 Pro 0813 | Gemma 4 31B | Leader |
|---|---|---|---|
| AA Intelligence Index | 36.0 | 14.7 | DeepSeek V4 Pro 0813 |
| Epoch Capabilities Index | 155.6 | 143.0 | DeepSeek V4 Pro 0813 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Pro 0813 | Gemma 4 31B | Leader |
|---|---|---|---|
| AA Agentic Index | 41.3 | 4.2 | DeepSeek V4 Pro 0813 |
| 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 |
| SREBench (Vals AI) | 1.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Finance Agent (Vals AI) | 50.4% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Tax Agent Bench (Vals AI) | 26.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Legal Research Bench (Vals AI) | 40.9% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 10.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Excel Modeling Benchmark (Vals AI) | 52.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Terminal-Bench-Science (Vals AI) | 4.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| τ²-Bench Telecom | Not measured | 65.5% | Only Gemma 4 31B measured |
| APEX-Agents | 47.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | DeepSeek V4 Pro 0813 | Gemma 4 31B | Leader |
|---|---|---|---|
| GPQA Diamond | 92.4% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LiveBench reasoning | Not measured | 68.3% | Only Gemma 4 31B measured |
| GPQA Diamond (Artificial Analysis run) | 92.8% | 85.7% | DeepSeek V4 Pro 0813 |
| Humanity's Last Exam (Artificial Analysis run) | 41.0% | 23.6% | DeepSeek V4 Pro 0813 |
| GPQA Diamond (Epoch AI run) | 91.7% | 75.8% | DeepSeek V4 Pro 0813 |
| ARC-AGI | 90.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| ARC-AGI-2 | 61.3% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Chess puzzles | 46.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| Mystery game puzzles | 43.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: hard prompts | 1458 | 1448 | DeepSeek V4 Pro 0813 |
| LMArena Text: expert | 1459 | 1464 | Gemma 4 31B |
| LMArena Text: hard prompts in English | 1463 | 1456 | DeepSeek V4 Pro 0813 |
| LMArena Vision: diagrams | Not measured | 1283 | Only Gemma 4 31B measured |
| LMArena Vision: homework | Not measured | 1310 | Only Gemma 4 31B measured |
| Kagi LLM Benchmark | Not measured | 63.5% | Only Gemma 4 31B measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | DeepSeek V4 Pro 0813 | Gemma 4 31B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.6% | 73.3% | DeepSeek V4 Pro 0813 |
| FrontierMath, tiers 1 to 3 | 64.6% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| ProofBench | 50.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: math | 1441 | 1463 | Gemma 4 31B |
| LMArena Text: mathematical work | 1443 | 1465 | Gemma 4 31B |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | DeepSeek V4 Pro 0813 | Gemma 4 31B | Leader |
|---|---|---|---|
| MMLU Pro | 87.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LegalBench (Vals AI) | 82.4% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| CaseLaw (Vals AI) | Not measured | 52.6% | Only Gemma 4 31B measured |
| CorpFin (Vals AI) | 65.4% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| TaxEval (Vals AI) | 73.1% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| MortgageTax (Vals AI) | Not measured | 61.4% | Only Gemma 4 31B measured |
| MedCode (Vals AI) | 42.5% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| SimpleQA Verified | 52.9% | 10.4% | DeepSeek V4 Pro 0813 |
| LMArena Text: science | 1457 | 1457 | Gemma 4 31B |
| LMArena Text: medicine and healthcare | 1446 | 1451 | Gemma 4 31B |
| LMArena Text: legal and government | 1459 | 1438 | DeepSeek V4 Pro 0813 |
| LMArena Text: business and finance | 1442 | 1430 | DeepSeek V4 Pro 0813 |
| FACTS Benchmark Suite | Not measured | 45.3% | Only Gemma 4 31B measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | DeepSeek V4 Pro 0813 | 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 index142
| Benchmark | DeepSeek V4 Pro 0813 | Gemma 4 31B | Leader |
|---|---|---|---|
| Vals Index | 53.0% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LiveBench data analysis | Not measured | 53.3% | Only Gemma 4 31B measured |
| SAGE (Vals AI) | Not measured | 55.0% | Only Gemma 4 31B measured |
| MedScribe (Vals AI) | 80.2% | Not measured | Only DeepSeek V4 Pro 0813 measured |
| IFBench | Not measured | 75.6% | Only Gemma 4 31B measured |
| Long context reasoning (AA-LCR) | 80.3% | 69.7% | DeepSeek V4 Pro 0813 |
| DTBench | 93.9% | 82.7% | DeepSeek V4 Pro 0813 |
| LMCA | 45.5% | 39.3% | DeepSeek V4 Pro 0813 |
| Surface Evolver Bench | Not measured | 30.6% | Only Gemma 4 31B measured |
| LMArena Text | 1446 | 1443 | DeepSeek V4 Pro 0813 |
| LMArena Text: instruction following | 1448 | 1433 | DeepSeek V4 Pro 0813 |
| LMArena Text: creative writing | 1439 | 1417 | DeepSeek V4 Pro 0813 |
| LMArena Vision | Not measured | 1276 | Only Gemma 4 31B measured |
| LMArena Text: English | 1457 | 1451 | DeepSeek V4 Pro 0813 |
| LMArena Text: non-English | 1431 | 1430 | DeepSeek V4 Pro 0813 |
| LMArena Text: Chinese | 1481 | 1475 | DeepSeek V4 Pro 0813 |
| LMArena Text: Korean | 1449 | Not measured | Only DeepSeek V4 Pro 0813 measured |
| LMArena Text: French | 1446 | 1436 | DeepSeek V4 Pro 0813 |
| LMArena Text: Spanish | 1435 | 1442 | Gemma 4 31B |
| LMArena Text: Russian | 1448 | 1460 | Gemma 4 31B |
| LMArena Text: Polish | Not measured | 1433 | Only Gemma 4 31B measured |
| LMArena Text: multi-turn | 1454 | 1452 | DeepSeek V4 Pro 0813 |
| LMArena Text: longer queries | 1458 | 1446 | DeepSeek V4 Pro 0813 |
| LMArena Text: writing and language | 1443 | 1432 | DeepSeek V4 Pro 0813 |
| LMArena Text: entertainment and media | 1424 | 1405 | DeepSeek V4 Pro 0813 |
| 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 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Pro 0813 | 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 V4 Pro 0813 | Google Gemma 4 31B |
|---|---|---|
| Maker | DeepSeek | |
| Weights | Open weights | Open weights |
| Released | August 12, 2026 | April 2, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.66 | $0.14 |
| Output $/Mtok | $1.98 | $0.40 |
| Coding index | 56.1 | 39.0 |
| Independent measurements behind it | 5 | 2 |
| Cost per solved task | $0.10 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Pro 0813 better than Gemma 4 31B for coding?
Pick DeepSeek V4 Pro 0813 for coding: it scores 56.1 on the Vibe Coding Index against 39.0 for Gemma 4 31B. Pick Gemma 4 31B for output tokens 4.9x cheaper ($0.40 vs $1.98 per million) and work measured by LMArena Text: software and IT or LMArena Text: expert, where it leads.
Which is cheaper, DeepSeek V4 Pro 0813 or Gemma 4 31B?
DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; Gemma 4 31B costs $0.14 and $0.40. Cost per solved task is known for DeepSeek V4 Pro 0813 only.
Which has the bigger context window, DeepSeek V4 Pro 0813 or Gemma 4 31B?
DeepSeek V4 Pro 0813, with 1.05M tokens against 262K.
How many benchmarks is the DeepSeek V4 Pro 0813 vs Gemma 4 31B comparison based on?
42 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Pro 0813's coding index rests on 5 independent benchmarks and Gemma 4 31B's on 2. Where only one model has a result, the page says so instead of naming a winner.