Gemma 3 4B vs GPT-4o (2024-11-20)
GPT-4o (2024-11-20) leads Gemma 3 4B on the Artificial Analysis Intelligence Index, 8.4 to 4.8, and Gemma 3 4B costs 133.3x less per output token ($0.075 vs $10.00 per million). Updated October 22, 2026; 3 benchmarks have a result for both.
Gemma 3 4B or GPT-4o (2024-11-20): which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Gemma 3 4B for output tokens 133.3x cheaper ($0.075 vs $10.00 per million) and a larger context window (131K against 128K tokens).
- Shared results
- 3
- Gemma 3 4B only
- 39
- GPT-4o (2024-11-20) only
- 21
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
GPT-4o (2024-11-20)
GPT-4o (2024-11-20) leads, 8.4 against 4.8.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-4o (2024-11-20) has a GPQA Diamond result, 53.8%.
Directional only
Math
AIME
No call
Only GPT-4o (2024-11-20) has a AIME result, 11.9%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4o (2024-11-20) has a MMLU Pro result, 72.6%.
Directional only
Long documents
Listed context window
Gemma 3 4B
Gemma 3 4B takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 3 4B
Gemma 3 4B $0.0001, GPT-4o (2024-11-20) $0.0075 per turn.
List prices
At a glance
- Coding index
- Gemma 3 4B not benchmarked, GPT-4o (2024-11-20) not benchmarked.
- Widest category
- Reasoning, 24.7 points apart on average over 1 shared benchmark.
- Widest single gap
- GPQA Diamond (Epoch AI run): Gemma 3 4B 23.2% against GPT-4o (2024-11-20) 47.9%, 24.7 points apart on a 0 to 100 scale.
- Output price
- Gemma 3 4B $0.075 against GPT-4o (2024-11-20) $10.00 per million output tokens, 133.3x apart.
- Context window
- Gemma 3 4B takes 131K tokens, GPT-4o (2024-11-20) 128K.
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 3 4B | Bars | GPT-4o (2024-11-20) | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| Math | 1 | 0 | ||
| All shared boards | 1 | 2 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index11 boards, none shared
| Benchmark | Gemma 3 4B | GPT-4o (2024-11-20) | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 18.2% | Only GPT-4o (2024-11-20) measured |
| AA Coding Index | 2.7 | Not measured | Only Gemma 3 4B measured |
| LiveCodeBench (Vals AI) | Not measured | 43.4% | Only GPT-4o (2024-11-20) measured |
| LiveCodeBench (Artificial Analysis run) | 11.2% | Not measured | Only Gemma 3 4B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 0.8% | Not measured | Only Gemma 3 4B measured |
| GSO-Bench | Not measured | 0.0% | Only GPT-4o (2024-11-20) measured |
| WeirdML | Not measured | 25.1% | Only GPT-4o (2024-11-20) measured |
| Cybench | Not measured | 12.5% | Only GPT-4o (2024-11-20) measured |
| LMArena Text: coding | 1230 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: software and IT | 1269 | Not measured | Only Gemma 3 4B measured |
| SciCode | 0.0% | Not measured | Only Gemma 3 4B measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 3 4B | GPT-4o (2024-11-20) | Leader |
|---|---|---|---|
| AA Intelligence Index | 4.8 | 8.4 | GPT-4o (2024-11-20) |
| Epoch Capabilities Index | 115.9 | Not measured | Only Gemma 3 4B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Gemma 3 4B | GPT-4o (2024-11-20) | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 5.0% | Not measured | Only Gemma 3 4B measured |
| TheAgentCompany | Not measured | 8.6% | Only GPT-4o (2024-11-20) measured |
| Berkeley Function Calling Leaderboard (BFCL) | 19.6% | Not measured | Only Gemma 3 4B measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 3 4B | GPT-4o (2024-11-20) | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 53.8% | Only GPT-4o (2024-11-20) measured |
| MMMU Pro (Vals AI) | Not measured | 62.2% | Only GPT-4o (2024-11-20) measured |
| GPQA Diamond (Artificial Analysis run) | 29.1% | Not measured | Only Gemma 3 4B measured |
| Humanity's Last Exam (Artificial Analysis run) | 5.3% | Not measured | Only Gemma 3 4B measured |
| GPQA Diamond (Epoch AI run) | 23.2% | 47.9% | GPT-4o (2024-11-20) |
| VPCT | Not measured | 40.0% | Only GPT-4o (2024-11-20) measured |
| LMArena Text: hard prompts | 1253 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: expert | 1223 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: hard prompts in English | 1253 | Not measured | Only Gemma 3 4B measured |
| Kagi LLM Benchmark | 25.2% | Not measured | Only Gemma 3 4B measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemma 3 4B | GPT-4o (2024-11-20) | Leader |
|---|---|---|---|
| AIME | Not measured | 11.9% | Only GPT-4o (2024-11-20) measured |
| MATH 500 (Vals AI) | Not measured | 74.0% | Only GPT-4o (2024-11-20) measured |
| MGSM (Vals AI) | Not measured | 90.4% | Only GPT-4o (2024-11-20) measured |
| AA Math Index | 12.7 | Not measured | Only Gemma 3 4B measured |
| AIME 2025 (Artificial Analysis run) | 12.7% | Not measured | Only Gemma 3 4B measured |
| OTIS Mock AIME | 7.5% | 6.3% | Gemma 3 4B |
| MATH level 5 | Not measured | 49.8% | Only GPT-4o (2024-11-20) measured |
| LMArena Text: math | 1239 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: mathematical work | 1256 | Not measured | 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 index12 boards, none shared
| Benchmark | Gemma 3 4B | GPT-4o (2024-11-20) | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 72.6% | Only GPT-4o (2024-11-20) measured |
| LegalBench (Vals AI) | Not measured | 82.2% | Only GPT-4o (2024-11-20) measured |
| CaseLaw (Vals AI) | Not measured | 59.7% | Only GPT-4o (2024-11-20) measured |
| CorpFin (Vals AI) | Not measured | 45.9% | Only GPT-4o (2024-11-20) measured |
| TaxEval (Vals AI) | Not measured | 74.5% | Only GPT-4o (2024-11-20) measured |
| MortgageTax (Vals AI) | Not measured | 57.4% | Only GPT-4o (2024-11-20) measured |
| MMLU Pro (Artificial Analysis run) | 41.7% | Not measured | Only Gemma 3 4B measured |
| GeoBench | Not measured | 71.0% | Only GPT-4o (2024-11-20) measured |
| LMArena Text: science | 1306 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: medicine and healthcare | 1342 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: legal and government | 1327 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: business and finance | 1311 | Not measured | Only Gemma 3 4B measured |
| Neither model has a result on the other 8 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 3 4B | GPT-4o (2024-11-20) | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | Gemma 3 4B | GPT-4o (2024-11-20) | Leader |
|---|---|---|---|
| IFBench | 28.3% | Not measured | Only Gemma 3 4B measured |
| Long context reasoning (AA-LCR) | 6.7% | Not measured | Only Gemma 3 4B measured |
| DTBench | 50.9% | Not measured | Only Gemma 3 4B measured |
| LMCA | 2.8% | Not measured | Only Gemma 3 4B measured |
| Creative writing (Lech Mazur) | Not measured | 81.8% | Only GPT-4o (2024-11-20) measured |
| LMArena Text | 1291 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: instruction following | 1239 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: creative writing | 1270 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: English | 1300 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: non-English | 1273 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: German | 1281 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: Russian | 1294 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: multi-turn | 1255 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: longer queries | 1273 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: writing and language | 1288 | Not measured | Only Gemma 3 4B measured |
| LMArena Text: entertainment and media | 1233 | Not measured | Only Gemma 3 4B measured |
| Neither model has a result on the other 32 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 3 4B | GPT-4o (2024-11-20) | 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 | Google Gemma 3 4B | OpenAI GPT-4o (2024-11-20) |
|---|---|---|
| Maker | OpenAI | |
| Weights | Open weights | No public weights listed |
| Released | March 13, 2025 | November 20, 2024 |
| Context window | 131K | 128K |
| Input $/Mtok | $0.045 | $2.50 |
| Output $/Mtok | $0.075 | $10.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 3 4B better than GPT-4o (2024-11-20) for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 3 4B for output tokens 133.3x cheaper ($0.075 vs $10.00 per million) and a larger context window (131K against 128K tokens).
Which is cheaper, Gemma 3 4B or GPT-4o (2024-11-20)?
Gemma 3 4B costs $0.045 per million input tokens and $0.075 per million output tokens; GPT-4o (2024-11-20) costs $2.50 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 3 4B or GPT-4o (2024-11-20)?
Gemma 3 4B, with 131K tokens against 128K.
How many benchmarks is the Gemma 3 4B vs GPT-4o (2024-11-20) comparison based on?
3 benchmarks have a result for both models as of October 22, 2026. Gemma 3 4B's coding index rests on 0 independent benchmarks and GPT-4o (2024-11-20)'s on 0. Where only one model has a result, the page says so instead of naming a winner.