GPT-4 vs GPT-4o-mini
Updated October 21, 2026. 10 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
GPT-4 has the edge where what matters is Epoch Capabilities Index or GPQA Diamond (Artificial Analysis run), where it leads.
- Shared results
- 10
- GPT-4 only
- 35
- GPT-4o-mini only
- 17
- Like-for-like categories
- 6 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, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Tied at 6.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-4o-mini has a GPQA Diamond result, 44.2%.
Directional only
Math
AIME
No call
Only GPT-4o-mini has a AIME result, 11.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4o-mini has a MMLU Pro result, 62.7%.
Directional only
Long documents
Listed context window
GPT-4o-mini
GPT-4o-mini takes 128K tokens against 8K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4o-mini
GPT-4 $0.060, GPT-4o-mini $0.0004 per turn.
List prices
At a glance
- Coding index
- GPT-4 not benchmarked, GPT-4o-mini not benchmarked.
- Widest category
- Reasoning, 7.7 points apart on average over 1 shared benchmark.
- Widest single gap
- MMLU Pro (Artificial Analysis run): GPT-4 56.2% against GPT-4o-mini 64.8%, 8.6 points apart on a 0 to 100 scale.
- Output price
- GPT-4 $60.00 against GPT-4o-mini $0.60 per million output tokens, 100.0x apart.
- Context window
- GPT-4 takes 8K tokens, GPT-4o-mini 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 | GPT-4 | Bars | GPT-4o-mini | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 0 | 1 | 1 tie | |
| Reasoning | 0 | 1 | ||
| Math | 1 | 0 | ||
| Knowledge | 1 | 1 | ||
| General | 3 | 0 | ||
| All shared boards | 6 | 3 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | GPT-4 | GPT-4o-mini | Leader |
|---|---|---|---|
| SWE-bench Verified | 22.4% | Not measured | Only GPT-4 measured |
| SWE-bench Lite | 39.7% | Not measured | Only GPT-4 measured |
| SWE-bench (full test set) | 12.5% | Not measured | Only GPT-4 measured |
| AA Coding Index | 13.1 | 11.4 | GPT-4 |
| LiveCodeBench (Vals AI) | Not measured | 26.4% | Only GPT-4o-mini measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 23.4% | Only GPT-4o-mini measured |
| LMArena Text: coding | 1209 | Not measured | Only GPT-4 measured |
| LMArena Text: software and IT | 1195 | Not measured | Only GPT-4 measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4 | GPT-4o-mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 6.7 | Tie |
| Epoch Capabilities Index | 125.7 | 126.5 | GPT-4o-mini |
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4 | GPT-4o-mini | Leader |
|---|---|---|---|
| Neither model has a result on 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4 | GPT-4o-mini | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 44.2% | Only GPT-4o-mini measured |
| MMMU Pro (Vals AI) | Not measured | 56.6% | Only GPT-4o-mini measured |
| GPQA Diamond (Artificial Analysis run) | 34.9% | 42.6% | GPT-4o-mini |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 4.2% | Only GPT-4o-mini measured |
| ARC-AGI-2 | Not measured | 0.0% | Only GPT-4o-mini measured |
| BIG-Bench Hard | 75.1% | Not measured | Only GPT-4 measured |
| LMArena Text: hard prompts | 1200 | Not measured | Only GPT-4 measured |
| LMArena Text: expert | 1149 | Not measured | Only GPT-4 measured |
| LMArena Text: hard prompts in English | 1209 | Not measured | Only GPT-4 measured |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-4 | GPT-4o-mini | Leader |
|---|---|---|---|
| AIME | Not measured | 11.5% | Only GPT-4o-mini measured |
| MATH 500 (Vals AI) | Not measured | 72.6% | Only GPT-4o-mini measured |
| MGSM (Vals AI) | Not measured | 86.2% | Only GPT-4o-mini measured |
| AA Math Index | Not measured | 14.7 | Only GPT-4o-mini measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 14.7% | Only GPT-4o-mini measured |
| GSM8K | 92.0% | 91.3% | GPT-4 |
| LMArena Text: math | 1230 | Not measured | Only GPT-4 measured |
| LMArena Text: mathematical work | 1228 | Not measured | Only GPT-4 measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-4 | GPT-4o-mini | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 62.7% | Only GPT-4o-mini measured |
| CorpFin (Vals AI) | Not measured | 45.5% | Only GPT-4o-mini measured |
| TaxEval (Vals AI) | Not measured | 60.5% | Only GPT-4o-mini measured |
| MortgageTax (Vals AI) | Not measured | 54.5% | Only GPT-4o-mini measured |
| MedQA (Vals AI) | Not measured | 72.4% | Only GPT-4o-mini measured |
| MMLU Pro (Artificial Analysis run) | 56.2% | 64.8% | GPT-4o-mini |
| MMLU | 86.4% | 81.8% | GPT-4 |
| AI2 Reasoning Challenge | 96.3% | Not measured | Only GPT-4 measured |
| LMArena Text: science | 1177 | Not measured | Only GPT-4 measured |
| LMArena Text: medicine and healthcare | 1145 | Not measured | Only GPT-4 measured |
| LMArena Text: legal and government | 1191 | Not measured | Only GPT-4 measured |
| LMArena Text: business and finance | 1145 | Not measured | Only GPT-4 measured |
| Neither model has a result on the other 5 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4 | GPT-4o-mini | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-4 | GPT-4o-mini | Leader |
|---|---|---|---|
| IFBench | 33.2% | 31.0% | GPT-4 |
| DTBench | 62.7% | 54.4% | GPT-4 |
| LMCA | 17.1% | 10.4% | GPT-4 |
| HellaSwag | 95.3% | Not measured | Only GPT-4 measured |
| WinoGrande | 87.5% | Not measured | Only GPT-4 measured |
| PIQA | Not measured | 88.7% | Only GPT-4o-mini measured |
| LMArena Text | 1206 | Not measured | Only GPT-4 measured |
| LMArena Text: instruction following | 1201 | Not measured | Only GPT-4 measured |
| LMArena Text: creative writing | 1191 | Not measured | Only GPT-4 measured |
| LMArena Text: English | 1220 | Not measured | Only GPT-4 measured |
| LMArena Text: non-English | 1194 | Not measured | Only GPT-4 measured |
| LMArena Text: Chinese | 1184 | Not measured | Only GPT-4 measured |
| LMArena Text: German | 1198 | Not measured | Only GPT-4 measured |
| LMArena Text: Japanese | 1137 | Not measured | Only GPT-4 measured |
| LMArena Text: Korean | 1087 | Not measured | Only GPT-4 measured |
| LMArena Text: French | 1220 | Not measured | Only GPT-4 measured |
| LMArena Text: Spanish | 1197 | Not measured | Only GPT-4 measured |
| LMArena Text: Russian | 1195 | Not measured | Only GPT-4 measured |
| LMArena Text: Polish | 1265 | Not measured | Only GPT-4 measured |
| LMArena Text: multi-turn | 1206 | Not measured | Only GPT-4 measured |
| LMArena Text: longer queries | 1190 | Not measured | Only GPT-4 measured |
| LMArena Text: writing and language | 1219 | Not measured | Only GPT-4 measured |
| LMArena Text: entertainment and media | 1184 | Not measured | Only GPT-4 measured |
| Neither model has a result on the other 23 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4 | GPT-4o-mini | 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
GPT-4o-mini costs less
Repository review
50K input + 3K output tokens
GPT-4o-mini costs less
Agent loop
200K input + 10K output tokens
GPT-4o-mini 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-4 | OpenAI GPT-4o-mini |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | May 28, 2023 | July 18, 2024 |
| Context window | 8K | 128K |
| Input $/Mtok | $30.00 | $0.15 |
| Output $/Mtok | $60.00 | $0.60 |
| 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 GPT-4 better than GPT-4o-mini for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. GPT-4 has the edge where what matters is Epoch Capabilities Index or GPQA Diamond (Artificial Analysis run), where it leads.
Which is cheaper, GPT-4 or GPT-4o-mini?
GPT-4 costs $30.00 per million input tokens and $60.00 per million output tokens; GPT-4o-mini costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4 or GPT-4o-mini?
GPT-4o-mini, with 128K tokens against 8K.
How many benchmarks is the GPT-4 vs GPT-4o-mini comparison based on?
10 benchmarks have a result for both models as of October 21, 2026. GPT-4's coding index rests on 0 independent benchmarks and GPT-4o-mini's on 0. Where only one model has a result, the page says so instead of naming a winner.