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Gemma 4 31B vs GPT-6 Sol

GPT-6 Sol leads Gemma 4 31B on coding, 76.0 to 39.0 on the Vibe Coding Index, and Gemma 4 31B costs 25.0x less per output token ($0.40 vs $10.00 per million). Updated October 21, 2026; 54 benchmarks have a result for both.

Gemma 4 31BGoogle
Coding
39.0
Overall
42.1
Output $/M
$0.40
32
GPT-6 SolOpenAI
Coding
76.0
Overall
74.6
Output $/M
$10.00
22
vs boards won of 54 shared

Gemma 4 31B or GPT-6 Sol: which to pick

Pick GPT-6 Sol for coding: it scores 76.0 on the Vibe Coding Index against 39.0 for Gemma 4 31B.

Pick Gemma 4 31B for output tokens 25.0x cheaper ($0.40 vs $10.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Shared results
54
Gemma 4 31B only
17
GPT-6 Sol only
47
Like-for-like categories
8 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.

At a glance

Coding index
Gemma 4 31B 39.0 from 2 benchmarks, GPT-6 Sol 76.0 from 5 benchmarks.
Widest category
Agentic work, 55.5 points apart on average over 3 shared benchmarks.
Widest single gap
LiveBench browser: Gemma 4 31B 4.0% against GPT-6 Sol 92.0%, 88.0 points apart on a 0 to 100 scale.
Output price
Gemma 4 31B $0.40 against GPT-6 Sol $10.00 per million output tokens, 25.0x apart.
Context window
Gemma 4 31B takes 262K tokens, GPT-6 Sol 1.05M.

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.

Boards won, where both have a result
CategoryGemma 4 31BBarsGPT-6 SolTies
Coding26
Intelligence02
Agentic work03
Reasoning53
Math21
Knowledge42
Web design01
General194
All shared boards3222
CodingLike-for-likeSix of these boards feed the Vibe Coding Index26
Coding benchmarks for Gemma 4 31B and GPT-6 Sol
BenchmarkGemma 4 31BGPT-6 SolLeader
LiveBench coding49.0%93.1%GPT-6 Sol
LMArena WebDev13671683GPT-6 Sol
AA Coding Index43.4Not measuredOnly Gemma 4 31B measured
Terminal-Bench 4 (Vals AI)Not measured44.4%Only GPT-6 Sol measured
Vibe Code Bench (Vals AI)Not measured87.8%Only GPT-6 Sol measured
Code migration (Vals AI)Not measured57.2%Only GPT-6 Sol measured
ProgramBench (Vals AI)Not measured2.0%Only GPT-6 Sol measured
IOI (Vals AI)Not measured82.6%Only GPT-6 Sol measured
Terminal-Bench 2.1 (Vals AI)Not measured83.2%Only GPT-6 Sol measured
CyberBench (Vals AI)Not measured78.0%Only GPT-6 Sol measured
SciCode45.5%57.6%GPT-6 Sol
Terminal-Bench Hard (Artificial Analysis run)36.4%Not measuredOnly Gemma 4 31B measured
FrontierCodeNot measured49.3%Only GPT-6 Sol measured
WeirdML52.3%Not measuredOnly Gemma 4 31B measured
ALE-Bench925.52462.0GPT-6 Sol
LMArena Text: coding14591448Gemma 4 31B
LMArena Text: software and IT14631433Gemma 4 31B
LMArena WebDev: React13591685GPT-6 Sol
LMArena WebDev: HTML13801685GPT-6 Sol
LMArena WebDev: from an imageNot measured1660Only GPT-6 Sol measured
SciCode8.9%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemma 4 31B and GPT-6 Sol
BenchmarkGemma 4 31BGPT-6 SolLeader
AA Intelligence Index14.747.6GPT-6 Sol
Epoch Capabilities Index143.0163.7GPT-6 Sol
Agentic workLike-for-likePublic boards, shown as published, kept out of the index03
Agentic work benchmarks for Gemma 4 31B and GPT-6 Sol
BenchmarkGemma 4 31BGPT-6 SolLeader
AA Agentic Index4.2Not measuredOnly Gemma 4 31B measured
Design Arena: agents building web appsNot measured1231Only GPT-6 Sol measured
Design Arena: agents building full-stack appsNot measured1238Only GPT-6 Sol measured
Design Arena: agents building mobile appsNot measured1214Only GPT-6 Sol measured
LiveBench research44.4%69.3%GPT-6 Sol
LiveBench browser4.0%92.0%GPT-6 Sol
LiveBench long agentic13.3%66.9%GPT-6 Sol
SREBench (Vals AI)Not measured30.5%Only GPT-6 Sol measured
Finance Agent (Vals AI)Not measured49.0%Only GPT-6 Sol measured
Tax Agent Bench (Vals AI)Not measured15.0%Only GPT-6 Sol measured
Legal Research Bench (Vals AI)Not measured28.9%Only GPT-6 Sol measured
Excel Modeling Benchmark (Vals AI)Not measured71.5%Only GPT-6 Sol measured
BioMysteryBench (Vals AI)Not measured74.8%Only GPT-6 Sol measured
Terminal-Bench-Science (Vals AI)Not measured30.0%Only GPT-6 Sol measured
Vals Science IndexNot measured45.0%Only GPT-6 Sol measured
τ²-Bench Telecom65.5%Not measuredOnly Gemma 4 31B measured
APEX-AgentsNot measured54.3%Only GPT-6 Sol measured
SpireClimbNot measured7.5%Only GPT-6 Sol measured
Vending-Bench 2Not measured$14,428Only GPT-6 Sol measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index53
Reasoning benchmarks for Gemma 4 31B and GPT-6 Sol
BenchmarkGemma 4 31BGPT-6 SolLeader
LiveBench reasoning68.3%88.7%GPT-6 Sol
MysteryMechanism (Vals AI)Not measured30.2%Only GPT-6 Sol measured
GPQA Diamond (Artificial Analysis run)85.7%Not measuredOnly Gemma 4 31B measured
Humanity's Last Exam (Artificial Analysis run)23.6%47.9%GPT-6 Sol
GPQA Diamond (Epoch AI run)75.8%94.3%GPT-6 Sol
ARC-AGINot measured95.5%Only GPT-6 Sol measured
ARC-AGI-2Not measured89.6%Only GPT-6 Sol measured
Chess puzzlesNot measured56.0%Only GPT-6 Sol measured
Mystery game puzzlesNot measured56.0%Only GPT-6 Sol measured
EBR-benchNot measured53.3%Only GPT-6 Sol measured
LMArena Text: hard prompts14481422Gemma 4 31B
LMArena Text: expert14641437Gemma 4 31B
LMArena Text: hard prompts in English14561420Gemma 4 31B
LMArena Vision: diagrams12831270Gemma 4 31B
LMArena Vision: homework13101286Gemma 4 31B
Kagi LLM Benchmark63.5%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index21
Math benchmarks for Gemma 4 31B and GPT-6 Sol
BenchmarkGemma 4 31BGPT-6 SolLeader
OTIS Mock AIME73.3%100.0%GPT-6 Sol
FrontierMath, tiers 1 to 3Not measured89.8%Only GPT-6 Sol measured
FrontierMath, tier 4Not measured90.0%Only GPT-6 Sol measured
ProofBenchNot measured83.0%Only GPT-6 Sol measured
LMArena Text: math14631407Gemma 4 31B
LMArena Text: mathematical work14651424Gemma 4 31B
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index42
Knowledge benchmarks for Gemma 4 31B and GPT-6 Sol
BenchmarkGemma 4 31BGPT-6 SolLeader
CaseLaw (Vals AI)52.6%Not measuredOnly Gemma 4 31B measured
MortgageTax (Vals AI)61.4%Not measuredOnly Gemma 4 31B measured
MedCode (Vals AI)Not measured47.1%Only GPT-6 Sol measured
SimpleQA Verified10.4%60.7%GPT-6 Sol
LMArena Text: science14571389Gemma 4 31B
LMArena Text: medicine and healthcare14511366Gemma 4 31B
LMArena Text: legal and government14381396Gemma 4 31B
LMArena Text: business and finance14301380Gemma 4 31B
FACTS Benchmark Suite45.3%72.5%GPT-6 Sol
Neither model has a result on the other 9 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index01
Web design benchmarks for Gemma 4 31B and GPT-6 Sol
BenchmarkGemma 4 31BGPT-6 SolLeader
Design Arena: websitesNot measured1292Only GPT-6 Sol measured
Design Arena: UI componentsNot measured1292Only GPT-6 Sol measured
Design Arena: game devNot measured1314Only GPT-6 Sol measured
Design Arena: data vizNot measured1269Only GPT-6 Sol measured
Design Arena: 3DNot measured1318Only GPT-6 Sol measured
Design Arena: all code categoriesNot measured1301Only GPT-6 Sol measured
Design Arena: SVGNot measured1316Only GPT-6 Sol measured
Design Arena: ASCII artNot measured1225Only GPT-6 Sol measured
LiveBench design58.4%82.2%GPT-6 Sol
GeneralLike-for-likePublic boards, shown as published, kept out of the index194
General benchmarks for Gemma 4 31B and GPT-6 Sol
BenchmarkGemma 4 31BGPT-6 SolLeader
LiveBench data analysis53.3%81.2%GPT-6 Sol
Public Benefits Bench (Vals AI)Not measured56.6%Only GPT-6 Sol measured
SAGE (Vals AI)55.0%44.8%Gemma 4 31B
MedScribe (Vals AI)Not measured82.0%Only GPT-6 Sol measured
IFBench75.6%Not measuredOnly Gemma 4 31B measured
Long context reasoning (AA-LCR)69.7%83.7%GPT-6 Sol
DTBench82.7%97.3%GPT-6 Sol
LMCA39.3%59.1%GPT-6 Sol
Surface Evolver Bench30.6%Not measuredOnly Gemma 4 31B measured
Furniture assemblyNot measured58.3%Only GPT-6 Sol measured
LMArena Text14431398Gemma 4 31B
LMArena Text: instruction following14331413Gemma 4 31B
LMArena Text: creative writing14171378Gemma 4 31B
LMArena Vision12761240Gemma 4 31B
LMArena Text: English14511396Gemma 4 31B
LMArena Text: non-English14301388Gemma 4 31B
LMArena Text: Chinese14751412Gemma 4 31B
LMArena Text: GermanNot measured1379Only GPT-6 Sol measured
LMArena Text: JapaneseNot measured1377Only GPT-6 Sol measured
LMArena Text: KoreanNot measured1336Only GPT-6 Sol measured
LMArena Text: French14361399Gemma 4 31B
LMArena Text: Spanish14421387Gemma 4 31B
LMArena Text: Russian14601402Gemma 4 31B
LMArena Text: Polish14331372Gemma 4 31B
LMArena Text: multi-turn14521414Gemma 4 31B
LMArena Text: longer queries14461416Gemma 4 31B
LMArena Text: writing and language14321389Gemma 4 31B
LMArena Text: entertainment and media14051373Gemma 4 31B
LMArena Vision: English12711229Gemma 4 31B
LMArena Vision: Chinese1326Not measuredOnly Gemma 4 31B measured
LMArena Vision: reading text12821258Gemma 4 31B
LMArena Vision: humor1280Not measuredOnly Gemma 4 31B measured
LMArena Vision: captioning1218Not measuredOnly Gemma 4 31B measured
LMArena Vision: recognizing things1226Not measuredOnly Gemma 4 31B measured
LMArena Vision: creative writing12851219Gemma 4 31B
LMArena Document1425Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 10 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemma 4 31B and GPT-6 Sol
BenchmarkGemma 4 31BGPT-6 SolLeader
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$0.0003Fits in one request
GPT-6 Sol$0.0070Fits in one request

Gemma 4 31B costs less

Repository review

50K input + 3K output tokens

Gemma 4 31B$0.0082Fits in one request
GPT-6 Sol$0.130Fits in one request

Gemma 4 31B costs less

Agent loop

200K input + 10K output tokens

Gemma 4 31B$0.032Fits in one request
GPT-6 Sol$0.500Fits in one request

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.

Specifications of Gemma 4 31B and GPT-6 Sol
SpecificationGoogle Gemma 4 31BOpenAI GPT-6 Sol
MakerGoogleOpenAI
WeightsOpen weightsNo public weights listed
ReleasedApril 2, 2026September 22, 2026
Context window262K1.05M
Input $/Mtok$0.14$2.00
Output $/Mtok$0.40$10.00
Coding index39.076.0
Independent measurements behind it25
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 4 31B better than GPT-6 Sol for coding?

Pick GPT-6 Sol for coding: it scores 76.0 on the Vibe Coding Index against 39.0 for Gemma 4 31B. Pick Gemma 4 31B for output tokens 25.0x cheaper ($0.40 vs $10.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Gemma 4 31B or GPT-6 Sol?

Gemma 4 31B costs $0.14 per million input tokens and $0.40 per million output tokens; GPT-6 Sol costs $2.00 and $10.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemma 4 31B or GPT-6 Sol?

GPT-6 Sol, with 1.05M tokens against 262K.

How many benchmarks is the Gemma 4 31B vs GPT-6 Sol comparison based on?

54 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-6 Sol's on 5. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gemma-4-31b-it-vs-gpt-6-sol">LLMBenchmark.ai, Gemma 4 31B vs GPT-6 Sol</a></p>