Gemma 4 31B vs GPT-5 Pro
Gemma 4 31B costs 300.0x less per output token than GPT-5 Pro ($0.40 vs $120.00 per million). Updated October 21, 2026; 3 benchmarks have a result for both.
Gemma 4 31B or GPT-5 Pro: which to pick
Only Gemma 4 31B has a coding score, 39.0 on the Vibe Coding Index; GPT-5 Pro has none, so the two cannot be ranked on coding.
Pick GPT-5 Pro for a larger context window (400K against 262K tokens) and work measured by WeirdML or Epoch Capabilities Index, where it leads.
- Shared results
- 3
- Gemma 4 31B only
- 68
- GPT-5 Pro only
- 6
- 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 Gemma 4 31B has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Gemma 4 31B has a AA Intelligence Index result, 14.7.
Directional only
Agentic work
AA Agentic Index
No call
Only Gemma 4 31B has a AA Agentic Index result, 4.2.
Directional only
Long documents
Listed context window
GPT-5 Pro
GPT-5 Pro takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 31B
Gemma 4 31B $0.0003, GPT-5 Pro $0.075 per turn.
List prices
At a glance
- Coding index
- Gemma 4 31B 39.0 from 2 benchmarks, GPT-5 Pro not benchmarked.
- Widest category
- Reasoning, 13.3 points apart on average over 1 shared benchmark.
- Widest single gap
- Kagi LLM Benchmark: Gemma 4 31B 63.5% against GPT-5 Pro 76.8%, 13.3 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 31B $0.40 against GPT-5 Pro $120.00 per million output tokens, 300.0x apart.
- Context window
- Gemma 4 31B takes 262K tokens, GPT-5 Pro 400K.
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 | Gemma 4 31B | Bars | GPT-5 Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| All shared boards | 0 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Gemma 4 31B | GPT-5 Pro | Leader |
|---|---|---|---|
| LiveBench coding | 49.0% | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev | 1367 | Not measured | Only Gemma 4 31B measured |
| AA Coding Index | 43.4 | Not measured | Only Gemma 4 31B measured |
| SciCode | 45.5% | Not measured | Only Gemma 4 31B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 36.4% | Not measured | Only Gemma 4 31B measured |
| WeirdML | 52.3% | 60.4% | GPT-5 Pro |
| ALE-Bench | 925.5 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: coding | 1459 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: software and IT | 1463 | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev: React | 1359 | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev: HTML | 1380 | Not measured | Only Gemma 4 31B measured |
| SciCode | 8.9% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 31B | GPT-5 Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.7 | Not measured | Only Gemma 4 31B measured |
| Epoch Capabilities Index | 143.0 | 150.6 | GPT-5 Pro |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Gemma 4 31B | GPT-5 Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 4.2 | Not measured | Only Gemma 4 31B measured |
| LiveBench research | 44.4% | Not measured | Only Gemma 4 31B measured |
| LiveBench browser | 4.0% | Not measured | Only Gemma 4 31B measured |
| LiveBench long agentic | 13.3% | Not measured | Only Gemma 4 31B measured |
| τ²-Bench Telecom | 65.5% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 4 31B | GPT-5 Pro | Leader |
|---|---|---|---|
| LiveBench reasoning | 68.3% | Not measured | Only Gemma 4 31B measured |
| GPQA Diamond (Artificial Analysis run) | 85.7% | Not measured | Only Gemma 4 31B measured |
| Humanity's Last Exam (Artificial Analysis run) | 23.6% | Not measured | Only Gemma 4 31B measured |
| GPQA Diamond (Epoch AI run) | 75.8% | Not measured | Only Gemma 4 31B measured |
| ARC-AGI | Not measured | 70.2% | Only GPT-5 Pro measured |
| ARC-AGI-2 | Not measured | 18.3% | Only GPT-5 Pro measured |
| SimpleBench | Not measured | 61.6% | Only GPT-5 Pro measured |
| Chess puzzles | Not measured | 48.0% | Only GPT-5 Pro measured |
| LMArena Text: hard prompts | 1448 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: expert | 1464 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: hard prompts in English | 1456 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: diagrams | 1283 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: homework | 1310 | Not measured | Only Gemma 4 31B measured |
| Kagi LLM Benchmark | 63.5% | 76.8% | GPT-5 Pro |
| Neither model has a result on the other 8 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Gemma 4 31B | GPT-5 Pro | Leader |
|---|---|---|---|
| OTIS Mock AIME | 73.3% | Not measured | Only Gemma 4 31B measured |
| FrontierMath, tiers 1 to 3 | Not measured | 55.8% | Only GPT-5 Pro measured |
| FrontierMath, tier 4 | Not measured | 19.5% | Only GPT-5 Pro measured |
| LMArena Text: math | 1463 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: mathematical work | 1465 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemma 4 31B | GPT-5 Pro | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 52.6% | Not measured | Only Gemma 4 31B measured |
| MortgageTax (Vals AI) | 61.4% | Not measured | Only Gemma 4 31B measured |
| SimpleQA Verified | 10.4% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: science | 1457 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: medicine and healthcare | 1451 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: legal and government | 1438 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: business and finance | 1430 | Not measured | Only Gemma 4 31B measured |
| FACTS Benchmark Suite | 45.3% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Gemma 4 31B | GPT-5 Pro | Leader |
|---|---|---|---|
| LiveBench design | 58.4% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 8 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index30 boards, none shared
| Benchmark | Gemma 4 31B | GPT-5 Pro | Leader |
|---|---|---|---|
| LiveBench data analysis | 53.3% | Not measured | Only Gemma 4 31B measured |
| SAGE (Vals AI) | 55.0% | Not measured | Only Gemma 4 31B measured |
| IFBench | 75.6% | Not measured | Only Gemma 4 31B measured |
| Long context reasoning (AA-LCR) | 69.7% | Not measured | Only Gemma 4 31B measured |
| DTBench | 82.7% | Not measured | Only Gemma 4 31B measured |
| LMCA | 39.3% | Not measured | Only Gemma 4 31B measured |
| Surface Evolver Bench | 30.6% | Not measured | Only Gemma 4 31B measured |
| LMArena Text | 1443 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: instruction following | 1433 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: creative writing | 1417 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision | 1276 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: English | 1451 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: non-English | 1430 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Chinese | 1475 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: French | 1436 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Spanish | 1442 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Russian | 1460 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Polish | 1433 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: multi-turn | 1452 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: longer queries | 1446 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: writing and language | 1432 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: entertainment and media | 1405 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: English | 1271 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: Chinese | 1326 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: reading text | 1282 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: humor | 1280 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: captioning | 1218 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: recognizing things | 1226 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: creative writing | 1285 | Not measured | Only Gemma 4 31B measured |
| LMArena Document | 1425 | Not measured | Only Gemma 4 31B 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 | Gemma 4 31B | GPT-5 Pro | 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 | Google Gemma 4 31B | OpenAI GPT-5 Pro |
|---|---|---|
| Maker | OpenAI | |
| Weights | Open weights | No public weights listed |
| Released | April 2, 2026 | October 6, 2025 |
| Context window | 262K | 400K |
| Input $/Mtok | $0.14 | $15.00 |
| Output $/Mtok | $0.40 | $120.00 |
| Coding index | 39.0 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 31B better than GPT-5 Pro for coding?
Only Gemma 4 31B has a coding score, 39.0 on the Vibe Coding Index; GPT-5 Pro has none, so the two cannot be ranked on coding. Pick GPT-5 Pro for a larger context window (400K against 262K tokens) and work measured by WeirdML or Epoch Capabilities Index, where it leads.
Which is cheaper, Gemma 4 31B or GPT-5 Pro?
Gemma 4 31B costs $0.14 per million input tokens and $0.40 per million output tokens; GPT-5 Pro costs $15.00 and $120.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 4 31B or GPT-5 Pro?
GPT-5 Pro, with 400K tokens against 262K.
How many benchmarks is the Gemma 4 31B vs GPT-5 Pro comparison based on?
3 benchmarks have a result for both models as of October 21, 2026. Gemma 4 31B's coding index rests on 2 independent benchmarks and GPT-5 Pro's on 0. Where only one model has a result, the page says so instead of naming a winner.