GPT-4o (2024-05-13) vs Mistral Small 3
GPT-4o (2024-05-13) leads Mistral Small 3 on the Artificial Analysis Intelligence Index, 7.3 to 6.7, and Mistral Small 3 costs 187.5x less per output token ($0.08 vs $15.00 per million). Updated October 22, 2026; 31 benchmarks have a result for both.
GPT-4o (2024-05-13) or Mistral Small 3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4o (2024-05-13) for a larger context window (128K against 33K tokens) and work measured by Humanity's Last Exam (Artificial Analysis run), where it leads.
- Shared results
- 31
- GPT-4o (2024-05-13) only
- 13
- Mistral Small 3 only
- 5
- Like-for-like categories
- 6 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 (2024-05-13)
GPT-4o (2024-05-13) leads, 7.3 against 6.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-4o (2024-05-13) has a GPQA Diamond result, 50.2%.
Directional only
Long documents
Listed context window
GPT-4o (2024-05-13)
GPT-4o (2024-05-13) takes 128K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3
GPT-4o (2024-05-13) $0.013, Mistral Small 3 $0.0001 per turn.
List prices
At a glance
- Coding index
- GPT-4o (2024-05-13) not benchmarked, Mistral Small 3 not benchmarked.
- Widest category
- General, 13.2 points apart on average over 15 shared benchmarks.
- Widest single gap
- LMArena Text: Japanese: GPT-4o (2024-05-13) 1257 against Mistral Small 3 1111, 24.3 points apart on a 0 to 100 scale.
- Output price
- GPT-4o (2024-05-13) $15.00 against Mistral Small 3 $0.08 per million output tokens, 187.5x apart.
- Context window
- GPT-4o (2024-05-13) takes 128K tokens, Mistral Small 3 33K.
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-4o (2024-05-13) | Bars | Mistral Small 3 | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 4 | 1 | ||
| Math | 2 | 0 | ||
| Knowledge | 5 | 0 | ||
| General | 15 | 0 | ||
| All shared boards | 30 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | GPT-4o (2024-05-13) | Mistral Small 3 | Leader |
|---|---|---|---|
| AA Coding Index | 24.2 | Not measured | Only GPT-4o (2024-05-13) measured |
| LiveCodeBench (Artificial Analysis run) | 33.4% | 25.2% | GPT-4o (2024-05-13) |
| LMArena Text: coding | 1297 | 1246 | GPT-4o (2024-05-13) |
| LMArena Text: software and IT | 1297 | 1248 | GPT-4o (2024-05-13) |
| Neither model has a result on the other 39 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-4o (2024-05-13) | Mistral Small 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.3 | 6.7 | GPT-4o (2024-05-13) |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-4o (2024-05-13) | Mistral Small 3 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 19.6% | Only Mistral Small 3 measured |
| METR time horizons | 40.8% | Not measured | Only GPT-4o (2024-05-13) measured |
| BALROG | 32.3% | Not measured | Only GPT-4o (2024-05-13) measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | GPT-4o (2024-05-13) | Mistral Small 3 | Leader |
|---|---|---|---|
| GPQA Diamond | 50.2% | Not measured | Only GPT-4o (2024-05-13) measured |
| GPQA Diamond (Artificial Analysis run) | 52.6% | 46.2% | GPT-4o (2024-05-13) |
| Humanity's Last Exam (Artificial Analysis run) | 1.8% | 3.8% | Mistral Small 3 |
| GPQA Diamond (Epoch AI run) | 48.9% | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: hard prompts | 1281 | 1233 | GPT-4o (2024-05-13) |
| LMArena Text: expert | 1250 | 1202 | GPT-4o (2024-05-13) |
| LMArena Text: hard prompts in English | 1293 | 1243 | GPT-4o (2024-05-13) |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-4o (2024-05-13) | Mistral Small 3 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 4.3 | Only Mistral Small 3 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 4.3% | Only Mistral Small 3 measured |
| OTIS Mock AIME | 6.3% | Not measured | Only GPT-4o (2024-05-13) measured |
| MATH level 5 | 51.0% | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: math | 1284 | 1240 | GPT-4o (2024-05-13) |
| LMArena Text: mathematical work | 1284 | 1243 | GPT-4o (2024-05-13) |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-4o (2024-05-13) | Mistral Small 3 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 74.0% | 65.2% | GPT-4o (2024-05-13) |
| MMLU | 84.2% | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: science | 1295 | 1235 | GPT-4o (2024-05-13) |
| LMArena Text: medicine and healthcare | 1278 | 1215 | GPT-4o (2024-05-13) |
| LMArena Text: legal and government | 1314 | 1219 | GPT-4o (2024-05-13) |
| LMArena Text: business and finance | 1262 | 1205 | GPT-4o (2024-05-13) |
| Neither model has a result on the other 14 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o (2024-05-13) | Mistral Small 3 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index150
| Benchmark | GPT-4o (2024-05-13) | Mistral Small 3 | Leader |
|---|---|---|---|
| IFBench | Not measured | 26.4% | Only Mistral Small 3 measured |
| Long context reasoning (AA-LCR) | Not measured | 0.0% | Only Mistral Small 3 measured |
| LMArena Text | 1300 | 1234 | GPT-4o (2024-05-13) |
| LMArena Text: instruction following | 1278 | 1214 | GPT-4o (2024-05-13) |
| LMArena Text: creative writing | 1291 | 1194 | GPT-4o (2024-05-13) |
| LMArena Vision | 1137 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: English | 1312 | 1256 | GPT-4o (2024-05-13) |
| LMArena Text: non-English | 1283 | 1198 | GPT-4o (2024-05-13) |
| LMArena Text: Chinese | 1277 | 1204 | GPT-4o (2024-05-13) |
| LMArena Text: German | 1283 | 1211 | GPT-4o (2024-05-13) |
| LMArena Text: Japanese | 1257 | 1111 | GPT-4o (2024-05-13) |
| LMArena Text: Korean | 1234 | 1188 | GPT-4o (2024-05-13) |
| LMArena Text: French | 1304 | 1204 | GPT-4o (2024-05-13) |
| LMArena Text: Spanish | 1292 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: Russian | 1285 | 1216 | GPT-4o (2024-05-13) |
| LMArena Text: Polish | 1365 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Text: multi-turn | 1302 | 1217 | GPT-4o (2024-05-13) |
| LMArena Text: longer queries | 1288 | 1246 | GPT-4o (2024-05-13) |
| LMArena Text: writing and language | 1298 | 1214 | GPT-4o (2024-05-13) |
| LMArena Text: entertainment and media | 1289 | 1184 | GPT-4o (2024-05-13) |
| LMArena Vision: English | 1147 | Not measured | Only GPT-4o (2024-05-13) measured |
| LMArena Vision: Chinese | 1132 | Not measured | Only GPT-4o (2024-05-13) measured |
| Neither model has a result on the other 26 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o (2024-05-13) | Mistral Small 3 | 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
Mistral Small 3 costs less
Repository review
50K input + 3K output tokens
Mistral Small 3 costs less
Agent loop
200K input + 10K output tokens
Mistral Small 3 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-4o (2024-05-13) | Mistral Small 3 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | May 13, 2024 | January 30, 2025 |
| Context window | 128K | 33K |
| Input $/Mtok | $5.00 | $0.05 |
| Output $/Mtok | $15.00 | $0.08 |
| 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-4o (2024-05-13) better than Mistral Small 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o (2024-05-13) for a larger context window (128K against 33K tokens) and work measured by Humanity's Last Exam (Artificial Analysis run), where it leads.
Which is cheaper, GPT-4o (2024-05-13) or Mistral Small 3?
GPT-4o (2024-05-13) costs $5.00 per million input tokens and $15.00 per million output tokens; Mistral Small 3 costs $0.05 and $0.08. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o (2024-05-13) or Mistral Small 3?
GPT-4o (2024-05-13), with 128K tokens against 33K.
How many benchmarks is the GPT-4o (2024-05-13) vs Mistral Small 3 comparison based on?
31 benchmarks have a result for both models as of October 22, 2026. GPT-4o (2024-05-13)'s coding index rests on 0 independent benchmarks and Mistral Small 3's on 0. Where only one model has a result, the page says so instead of naming a winner.