GPT-4o (2024-08-06) vs Mistral Small 3.1 24B
Mistral Small 3.1 24B costs 18.0x less per output token than GPT-4o (2024-08-06) ($0.555 vs $10.00 per million). Updated October 23, 2026; 30 benchmarks have a result for both.
GPT-4o (2024-08-06) or Mistral Small 3.1 24B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4o (2024-08-06) for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 30
- GPT-4o (2024-08-06) only
- 28
- Mistral Small 3.1 24B only
- 8
- Like-for-like categories
- 5 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
No call
Only GPT-4o (2024-08-06) has a AA Intelligence Index result, 7.7.
Directional only
Math
AIME
No call
Only GPT-4o (2024-08-06) has a AIME result, 14.0%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4o (2024-08-06) has a MMLU Pro result, 74.1%.
Directional only
Long documents
Listed context window
No call
Both take 128K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3.1 24B
GPT-4o (2024-08-06) $0.0075, Mistral Small 3.1 24B $0.0006 per turn.
List prices
At a glance
- Coding index
- GPT-4o (2024-08-06) not benchmarked, Mistral Small 3.1 24B not benchmarked.
- Widest category
- General, 4.3 points apart on average over 19 shared benchmarks.
- Widest single gap
- LMArena Vision: Chinese: GPT-4o (2024-08-06) 1009 against Mistral Small 3.1 24B 1155, 24.3 points apart on a 0 to 100 scale.
- Output price
- GPT-4o (2024-08-06) $10.00 against Mistral Small 3.1 24B $0.555 per million output tokens, 18.0x apart.
- Context window
- Both take 128K tokens.
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 (2024-08-06) | Bars | Mistral Small 3.1 24B | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Reasoning | 0 | 3 | ||
| Math | 2 | 0 | ||
| Knowledge | 2 | 2 | ||
| General | 12 | 7 | ||
| All shared boards | 16 | 14 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GPT-4o (2024-08-06) | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| Aider polyglot | 23.1% | Not measured | Only GPT-4o (2024-08-06) measured |
| SWE-bench Lite | 21.7% | Not measured | Only GPT-4o (2024-08-06) measured |
| LiveCodeBench (Artificial Analysis run) | 31.7% | Not measured | Only GPT-4o (2024-08-06) measured |
| Terminal-Bench Hard (Artificial Analysis run) | 8.3% | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text: coding | 1283 | 1309 | Mistral Small 3.1 24B |
| LMArena Text: software and IT | 1278 | 1301 | Mistral Small 3.1 24B |
| Neither model has a result on the other 37 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-4o (2024-08-06) | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.7 | Not measured | Only GPT-4o (2024-08-06) measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-4o (2024-08-06) | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 28.9% | Not measured | Only GPT-4o (2024-08-06) measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-4o (2024-08-06) | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| MMMU Pro (Vals AI) | 64.0% | Not measured | Only GPT-4o (2024-08-06) measured |
| GPQA Diamond (Artificial Analysis run) | 52.1% | Not measured | Only GPT-4o (2024-08-06) measured |
| Humanity's Last Exam (Artificial Analysis run) | 2.3% | Not measured | Only GPT-4o (2024-08-06) measured |
| GPQA Diamond (Epoch AI run) | 49.2% | Not measured | Only GPT-4o (2024-08-06) measured |
| SimpleBench | 17.8% | Not measured | Only GPT-4o (2024-08-06) measured |
| Chess puzzles | 6.0% | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text: hard prompts | 1264 | 1278 | Mistral Small 3.1 24B |
| LMArena Text: expert | 1241 | 1257 | Mistral Small 3.1 24B |
| LMArena Text: hard prompts in English | 1277 | 1290 | Mistral Small 3.1 24B |
| LMArena Vision: diagrams | Not measured | 1119 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: homework | Not measured | 1158 | Only Mistral Small 3.1 24B measured |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-4o (2024-08-06) | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| AIME | 14.0% | Not measured | Only GPT-4o (2024-08-06) measured |
| MATH 500 (Vals AI) | 75.2% | Not measured | Only GPT-4o (2024-08-06) measured |
| MGSM (Vals AI) | 90.7% | Not measured | Only GPT-4o (2024-08-06) measured |
| OTIS Mock AIME | 6.4% | Not measured | Only GPT-4o (2024-08-06) measured |
| FrontierMath, tiers 1 to 3 | 0.4% | Not measured | Only GPT-4o (2024-08-06) measured |
| MATH level 5 | 53.3% | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text: math | 1285 | 1261 | GPT-4o (2024-08-06) |
| LMArena Text: mathematical work | 1283 | 1271 | GPT-4o (2024-08-06) |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | GPT-4o (2024-08-06) | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| MMLU Pro | 74.1% | Not measured | Only GPT-4o (2024-08-06) measured |
| LegalBench (Vals AI) | 80.1% | Not measured | Only GPT-4o (2024-08-06) measured |
| CorpFin (Vals AI) | 39.4% | Not measured | Only GPT-4o (2024-08-06) measured |
| TaxEval (Vals AI) | 71.1% | Not measured | Only GPT-4o (2024-08-06) measured |
| MortgageTax (Vals AI) | 61.0% | Not measured | Only GPT-4o (2024-08-06) measured |
| MedQA (Vals AI) | 88.2% | Not measured | Only GPT-4o (2024-08-06) measured |
| SimpleQA Verified | 26.0% | Not measured | Only GPT-4o (2024-08-06) measured |
| MMLU | 84.3% | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text: science | 1274 | 1265 | GPT-4o (2024-08-06) |
| LMArena Text: medicine and healthcare | 1252 | 1267 | Mistral Small 3.1 24B |
| LMArena Text: legal and government | 1275 | 1270 | GPT-4o (2024-08-06) |
| LMArena Text: business and finance | 1232 | 1257 | Mistral Small 3.1 24B |
| 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 | GPT-4o (2024-08-06) | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index127
| Benchmark | GPT-4o (2024-08-06) | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| IFBench | 36.0% | Not measured | Only GPT-4o (2024-08-06) measured |
| Long context reasoning (AA-LCR) | 41.0% | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text | 1283 | 1277 | GPT-4o (2024-08-06) |
| LMArena Text: instruction following | 1267 | 1263 | GPT-4o (2024-08-06) |
| LMArena Text: creative writing | 1274 | 1252 | GPT-4o (2024-08-06) |
| LMArena Vision | 1065 | 1136 | Mistral Small 3.1 24B |
| LMArena Text: English | 1297 | 1295 | GPT-4o (2024-08-06) |
| LMArena Text: non-English | 1262 | 1255 | GPT-4o (2024-08-06) |
| LMArena Text: Chinese | 1254 | 1253 | GPT-4o (2024-08-06) |
| LMArena Text: German | 1257 | 1266 | Mistral Small 3.1 24B |
| LMArena Text: Japanese | 1234 | 1208 | GPT-4o (2024-08-06) |
| LMArena Text: Korean | 1218 | 1206 | GPT-4o (2024-08-06) |
| LMArena Text: French | 1263 | 1273 | Mistral Small 3.1 24B |
| LMArena Text: Spanish | 1269 | 1283 | Mistral Small 3.1 24B |
| LMArena Text: Russian | 1272 | 1263 | GPT-4o (2024-08-06) |
| LMArena Text: Polish | Not measured | 1242 | Only Mistral Small 3.1 24B measured |
| LMArena Text: multi-turn | 1279 | 1270 | GPT-4o (2024-08-06) |
| LMArena Text: longer queries | 1283 | 1298 | Mistral Small 3.1 24B |
| LMArena Text: writing and language | 1290 | 1269 | GPT-4o (2024-08-06) |
| LMArena Text: entertainment and media | 1267 | 1250 | GPT-4o (2024-08-06) |
| LMArena Vision: English | 1072 | 1157 | Mistral Small 3.1 24B |
| LMArena Vision: Chinese | 1009 | 1155 | Mistral Small 3.1 24B |
| LMArena Vision: reading text | Not measured | 1132 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: humor | Not measured | 1142 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: captioning | Not measured | 1153 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: recognizing things | Not measured | 1155 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: creative writing | Not measured | 1123 | Only Mistral Small 3.1 24B measured |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o (2024-08-06) | Mistral Small 3.1 24B | 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 3.1 24B costs less
Repository review
50K input + 3K output tokens
Mistral Small 3.1 24B costs less
Agent loop
200K input + 10K output tokens
Mistral Small 3.1 24B 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 (2024-08-06) | Mistral Small 3.1 24B |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | August 6, 2024 | March 17, 2025 |
| Context window | 128K | 128K |
| Input $/Mtok | $2.50 | $0.351 |
| Output $/Mtok | $10.00 | $0.555 |
| 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 (2024-08-06) better than Mistral Small 3.1 24B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o (2024-08-06) for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, GPT-4o (2024-08-06) or Mistral Small 3.1 24B?
GPT-4o (2024-08-06) costs $2.50 per million input tokens and $10.00 per million output tokens; Mistral Small 3.1 24B costs $0.351 and $0.555. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o (2024-08-06) or Mistral Small 3.1 24B?
Neither: both take 128K tokens.
How many benchmarks is the GPT-4o (2024-08-06) vs Mistral Small 3.1 24B comparison based on?
30 benchmarks have a result for both models as of October 23, 2026. GPT-4o (2024-08-06)'s coding index rests on 0 independent benchmarks and Mistral Small 3.1 24B's on 0. Where only one model has a result, the page says so instead of naming a winner.