GPT-5.4 Mini vs Llama 4 Maverick
Updated October 21, 2026. 62 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-5.4 Mini for coding: it scores 28.2 on the Vibe Coding Index against 18.1 for Llama 4 Maverick, though on 1 benchmark against 2.
Pick Llama 4 Maverick when output tokens cost 6.9x less, or when the context window is larger, 524K against 400K tokens.
- Shared results
- 62
- GPT-5.4 Mini only
- 26
- Llama 4 Maverick only
- 22
- Like-for-like categories
- 7 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
GPT-5.4 Mini
GPT-5.4 Mini scores 28.2 against 18.1.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.4 Mini
GPT-5.4 Mini leads, 24.1 against 9.3.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.4 Mini
GPT-5.4 Mini leads, 17.9 against 0.6.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.4 Mini
GPT-5.4 Mini leads, 83.1% against 69.4%.
Same board, both measured
Math
AIME
GPT-5.4 Mini
GPT-5.4 Mini leads, 95.6% against 25.2%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.4 Mini
GPT-5.4 Mini leads, 84.5% against 79.4%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Llama 4 Maverick has a Design Arena: websites result, 871.
Directional only
Long documents
Listed context window
Llama 4 Maverick
Llama 4 Maverick takes 524K tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 4 Maverick
GPT-5.4 Mini $0.0030, Llama 4 Maverick $0.0005 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.4 Mini
GPT-5.4 Mini $0.70, Llama 4 Maverick $1.491.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.4 Mini 28.2 from 1 benchmark, Llama 4 Maverick 18.1 from 2 benchmarks.
- Widest category
- Agentic work, 41.4 points apart on average over 2 shared benchmarks.
- Widest single gap
- AIME: GPT-5.4 Mini 95.6% against Llama 4 Maverick 25.2%, 70.4 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 Mini $4.50 against Llama 4 Maverick $0.6525 per million output tokens, 6.9x apart.
- Context window
- GPT-5.4 Mini takes 400K tokens, Llama 4 Maverick 524K.
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 | GPT-5.4 Mini | Bars | Llama 4 Maverick | Ties |
|---|---|---|---|---|
| Coding | 8 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 11 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 8 | 0 | ||
| General | 28 | 0 | ||
| All shared boards | 62 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index80
| Benchmark | GPT-5.4 Mini | Llama 4 Maverick | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 15.6% | Only Llama 4 Maverick measured |
| SWE-bench Verified | Not measured | 21.0% | Only Llama 4 Maverick measured |
| LMArena WebDev | 1397 | Not measured | Only GPT-5.4 Mini measured |
| AA Coding Index | 56.1 | 16.3 | GPT-5.4 Mini |
| LiveCodeBench (Vals AI) | 81.5% | 47.3% | GPT-5.4 Mini |
| SWE-bench Verified (Vals AI) | 73.0% | Not measured | Only GPT-5.4 Mini measured |
| Terminal-Bench 4 (Vals AI) | 2.5% | Not measured | Only GPT-5.4 Mini measured |
| Vibe Code Bench (Vals AI) | 48.0% | Not measured | Only GPT-5.4 Mini measured |
| Code migration (Vals AI) | 12.9% | Not measured | Only GPT-5.4 Mini measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only GPT-5.4 Mini measured |
| Terminal-Bench 2.1 (Vals AI) | 54.7% | Not measured | Only GPT-5.4 Mini measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 39.7% | Only Llama 4 Maverick measured |
| SciCode | 52.1% | 31.7% | GPT-5.4 Mini |
| Terminal-Bench Hard (Artificial Analysis run) | 52.3% | 6.8% | GPT-5.4 Mini |
| FrontierCode | 27.0% | Not measured | Only GPT-5.4 Mini measured |
| WeirdML | 60.3% | 24.5% | GPT-5.4 Mini |
| ALE-Bench | 1188.6 | 173.0 | GPT-5.4 Mini |
| LMArena Text: coding | 1438 | 1301 | GPT-5.4 Mini |
| LMArena Text: software and IT | 1436 | 1299 | GPT-5.4 Mini |
| LMArena WebDev: React | 1386 | Not measured | Only GPT-5.4 Mini measured |
| LMArena WebDev: HTML | 1419 | Not measured | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 Mini | Llama 4 Maverick | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.1 | 9.3 | GPT-5.4 Mini |
| Epoch Capabilities Index | 148.7 | 132.2 | GPT-5.4 Mini |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 Mini | Llama 4 Maverick | Leader |
|---|---|---|---|
| AA Agentic Index | 17.9 | 0.6 | GPT-5.4 Mini |
| Finance Agent (Vals AI) | 45.4% | Not measured | Only GPT-5.4 Mini measured |
| Tax Agent Bench (Vals AI) | 8.8% | Not measured | Only GPT-5.4 Mini measured |
| Legal Research Bench (Vals AI) | 12.5% | Not measured | Only GPT-5.4 Mini measured |
| Excel Modeling Benchmark (Vals AI) | 45.4% | Not measured | Only GPT-5.4 Mini measured |
| τ²-Bench Telecom | 83.3% | 17.8% | GPT-5.4 Mini |
| DeepResearch Bench | 36.3% | Not measured | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index110
| Benchmark | GPT-5.4 Mini | Llama 4 Maverick | Leader |
|---|---|---|---|
| GPQA Diamond | 83.1% | 69.4% | GPT-5.4 Mini |
| MMMU Pro (Vals AI) | 79.3% | 71.7% | GPT-5.4 Mini |
| GPQA Diamond (Artificial Analysis run) | 87.5% | 67.1% | GPT-5.4 Mini |
| Humanity's Last Exam (Artificial Analysis run) | 28.1% | 4.9% | GPT-5.4 Mini |
| GPQA Diamond (Epoch AI run) | 86.9% | Not measured | Only GPT-5.4 Mini measured |
| ARC-AGI | 63.7% | 4.4% | GPT-5.4 Mini |
| ARC-AGI-2 | 18.9% | 0.0% | GPT-5.4 Mini |
| SimpleBench | Not measured | 27.7% | Only Llama 4 Maverick measured |
| Chess puzzles | 23.0% | Not measured | Only GPT-5.4 Mini measured |
| Mystery game puzzles | 11.0% | Not measured | Only GPT-5.4 Mini measured |
| LMArena Text: hard prompts | 1424 | 1281 | GPT-5.4 Mini |
| LMArena Text: expert | 1435 | 1259 | GPT-5.4 Mini |
| LMArena Text: hard prompts in English | 1420 | 1295 | GPT-5.4 Mini |
| LMArena Vision: diagrams | 1266 | 1134 | GPT-5.4 Mini |
| LMArena Vision: homework | 1285 | 1164 | GPT-5.4 Mini |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-5.4 Mini | Llama 4 Maverick | Leader |
|---|---|---|---|
| AIME | 95.6% | 25.2% | GPT-5.4 Mini |
| MATH 500 (Vals AI) | Not measured | 85.2% | Only Llama 4 Maverick measured |
| MGSM (Vals AI) | Not measured | 92.4% | Only Llama 4 Maverick measured |
| AA Math Index | Not measured | 19.3 | Only Llama 4 Maverick measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 19.3% | Only Llama 4 Maverick measured |
| OTIS Mock AIME | 88.9% | Not measured | Only GPT-5.4 Mini measured |
| FrontierMath, tiers 1 to 3 | 51.2% | Not measured | Only GPT-5.4 Mini measured |
| FrontierMath, tier 4 | 9.8% | Not measured | Only GPT-5.4 Mini measured |
| ProofBench | 21.0% | Not measured | Only GPT-5.4 Mini measured |
| LMArena Text: math | 1418 | 1299 | GPT-5.4 Mini |
| LMArena Text: mathematical work | 1429 | 1295 | GPT-5.4 Mini |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | GPT-5.4 Mini | Llama 4 Maverick | Leader |
|---|---|---|---|
| MMLU Pro | 84.5% | 79.4% | GPT-5.4 Mini |
| LegalBench (Vals AI) | Not measured | 77.8% | Only Llama 4 Maverick measured |
| CaseLaw (Vals AI) | 51.7% | Not measured | Only GPT-5.4 Mini measured |
| CorpFin (Vals AI) | 60.9% | 49.7% | GPT-5.4 Mini |
| TaxEval (Vals AI) | 71.2% | 66.6% | GPT-5.4 Mini |
| MortgageTax (Vals AI) | 63.5% | 58.5% | GPT-5.4 Mini |
| MedQA (Vals AI) | Not measured | 43.3% | Only Llama 4 Maverick measured |
| MedCode (Vals AI) | Not measured | 36.5% | Only Llama 4 Maverick measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 80.9% | Only Llama 4 Maverick measured |
| SimpleQA Verified | 29.4% | Not measured | Only GPT-5.4 Mini measured |
| GeoBench | Not measured | 52.0% | Only Llama 4 Maverick measured |
| LMArena Text: science | 1417 | 1288 | GPT-5.4 Mini |
| LMArena Text: medicine and healthcare | 1395 | 1275 | GPT-5.4 Mini |
| LMArena Text: legal and government | 1414 | 1286 | GPT-5.4 Mini |
| LMArena Text: business and finance | 1418 | 1260 | GPT-5.4 Mini |
| Neither model has a result on the other 2 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.4 Mini | Llama 4 Maverick | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 871 | Only Llama 4 Maverick measured |
| Design Arena: UI components | Not measured | 899 | Only Llama 4 Maverick measured |
| Design Arena: game dev | Not measured | 838 | Only Llama 4 Maverick measured |
| Design Arena: data viz | Not measured | 882 | Only Llama 4 Maverick measured |
| Design Arena: 3D | Not measured | 901 | Only Llama 4 Maverick measured |
| Design Arena: all code categories | Not measured | 880 | Only Llama 4 Maverick measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index280
| Benchmark | GPT-5.4 Mini | Llama 4 Maverick | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 50.8% | 35.7% | GPT-5.4 Mini |
| MedScribe (Vals AI) | Not measured | 54.2% | Only Llama 4 Maverick measured |
| Vals Multimodal Index | 54.2% | Not measured | Only GPT-5.4 Mini measured |
| IFBench | 73.3% | 43.0% | GPT-5.4 Mini |
| Long context reasoning (AA-LCR) | 77.0% | 50.0% | GPT-5.4 Mini |
| DTBench | 80.0% | 61.9% | GPT-5.4 Mini |
| LMCA | 40.8% | 15.9% | GPT-5.4 Mini |
| Fiction.LiveBench | Not measured | 46.2% | Only Llama 4 Maverick measured |
| Creative writing (Lech Mazur) | Not measured | 62.0% | Only Llama 4 Maverick measured |
| LMArena Text | 1412 | 1287 | GPT-5.4 Mini |
| LMArena Text: instruction following | 1405 | 1267 | GPT-5.4 Mini |
| LMArena Text: creative writing | 1370 | 1266 | GPT-5.4 Mini |
| LMArena Vision | 1245 | 1142 | GPT-5.4 Mini |
| LMArena Text: English | 1412 | 1303 | GPT-5.4 Mini |
| LMArena Text: non-English | 1405 | 1269 | GPT-5.4 Mini |
| LMArena Text: Chinese | 1446 | 1277 | GPT-5.4 Mini |
| LMArena Text: German | 1408 | 1291 | GPT-5.4 Mini |
| LMArena Text: Japanese | 1375 | 1206 | GPT-5.4 Mini |
| LMArena Text: Korean | 1370 | 1203 | GPT-5.4 Mini |
| LMArena Text: French | 1441 | 1259 | GPT-5.4 Mini |
| LMArena Text: Spanish | 1405 | 1293 | GPT-5.4 Mini |
| LMArena Text: Russian | 1417 | 1286 | GPT-5.4 Mini |
| LMArena Text: Polish | 1415 | 1275 | GPT-5.4 Mini |
| LMArena Text: multi-turn | 1429 | 1289 | GPT-5.4 Mini |
| LMArena Text: longer queries | 1408 | 1280 | GPT-5.4 Mini |
| LMArena Text: writing and language | 1393 | 1277 | GPT-5.4 Mini |
| LMArena Text: entertainment and media | 1373 | 1250 | GPT-5.4 Mini |
| LMArena Vision: English | 1244 | 1150 | GPT-5.4 Mini |
| LMArena Vision: Chinese | 1286 | 1141 | GPT-5.4 Mini |
| LMArena Vision: reading text | 1253 | 1143 | GPT-5.4 Mini |
| LMArena Vision: humor | 1235 | 1100 | GPT-5.4 Mini |
| LMArena Vision: recognizing things | 1218 | Not measured | Only GPT-5.4 Mini measured |
| LMArena Vision: creative writing | 1222 | 1099 | GPT-5.4 Mini |
| 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 | GPT-5.4 Mini | Llama 4 Maverick | 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
Llama 4 Maverick costs less
Repository review
50K input + 3K output tokens
Llama 4 Maverick costs less
Agent loop
200K input + 10K output tokens
Llama 4 Maverick 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 | OpenAI GPT-5.4 Mini | Meta Llama 4 Maverick |
|---|---|---|
| Maker | OpenAI | Meta Llama |
| Weights | No public weights listed | Open weights |
| Released | March 17, 2026 | April 5, 2025 |
| Context window | 400K | 524K |
| Input $/Mtok | $0.75 | $0.1875 |
| Output $/Mtok | $4.50 | $0.6525 |
| Coding index | 28.2 | 18.1 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | $0.70 | $1.491 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 Mini better than Llama 4 Maverick for coding?
Pick GPT-5.4 Mini for coding: it scores 28.2 on the Vibe Coding Index against 18.1 for Llama 4 Maverick, though on 1 benchmark against 2. Pick Llama 4 Maverick when output tokens cost 6.9x less, or when the context window is larger, 524K against 400K tokens.
Which is cheaper, GPT-5.4 Mini or Llama 4 Maverick?
GPT-5.4 Mini costs $0.75 per million input tokens and $4.50 per million output tokens; Llama 4 Maverick costs $0.1875 and $0.6525. Per solved SWE-bench Verified task, GPT-5.4 Mini costs $0.70 and Llama 4 Maverick $1.491.
Which has the bigger context window, GPT-5.4 Mini or Llama 4 Maverick?
Llama 4 Maverick, with 524K tokens against 400K.
How many benchmarks is the GPT-5.4 Mini vs Llama 4 Maverick comparison based on?
62 benchmarks have a result for both models as of October 21, 2026. GPT-5.4 Mini's coding index rests on 1 independent benchmark and Llama 4 Maverick's on 2. Where only one model has a result, the page says so instead of naming a winner.