GPT-4 Turbo vs Mistral Small 3.1 24B
Mistral Small 3.1 24B costs 54.1x less per output token than GPT-4 Turbo ($0.555 vs $30.00 per million). Updated October 22, 2026; 31 benchmarks have a result for both.
GPT-4 Turbo 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-4 Turbo for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 31
- GPT-4 Turbo only
- 11
- Mistral Small 3.1 24B only
- 7
- 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-4 Turbo has a AA Intelligence Index result, 7.0.
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-4 Turbo $0.025, Mistral Small 3.1 24B $0.0006 per turn.
List prices
At a glance
- Coding index
- GPT-4 Turbo not benchmarked, Mistral Small 3.1 24B not benchmarked.
- Widest category
- Coding, 6.2 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMArena Vision: Chinese: GPT-4 Turbo 1045 against Mistral Small 3.1 24B 1155, 18.3 points apart on a 0 to 100 scale.
- Output price
- GPT-4 Turbo $30.00 against Mistral Small 3.1 24B $0.555 per million output tokens, 54.1x 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-4 Turbo | Bars | Mistral Small 3.1 24B | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Reasoning | 0 | 3 | ||
| Math | 1 | 1 | ||
| Knowledge | 0 | 4 | ||
| General | 5 | 15 | ||
| All shared boards | 6 | 25 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| AA Coding Index | 21.5 | Not measured | Only GPT-4 Turbo measured |
| LiveCodeBench (Artificial Analysis run) | 29.1% | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: coding | 1268 | 1309 | Mistral Small 3.1 24B |
| LMArena Text: software and IT | 1267 | 1301 | Mistral Small 3.1 24B |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.0 | Not measured | Only GPT-4 Turbo measured |
| Epoch Capabilities Index | 127.3 | Not measured | Only GPT-4 Turbo measured |
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| Neither model has a result on 41 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| Humanity's Last Exam (Artificial Analysis run) | 3.1% | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: hard prompts | 1251 | 1278 | Mistral Small 3.1 24B |
| LMArena Text: expert | 1223 | 1257 | Mistral Small 3.1 24B |
| LMArena Text: hard prompts in English | 1266 | 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 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| LMArena Text: math | 1272 | 1261 | GPT-4 Turbo |
| LMArena Text: mathematical work | 1268 | 1271 | Mistral Small 3.1 24B |
| Neither model has a result on the other 11 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 80.5% | Not measured | Only GPT-4 Turbo measured |
| MedQA (Vals AI) | 82.0% | Not measured | Only GPT-4 Turbo measured |
| MMLU Pro (Artificial Analysis run) | 69.4% | Not measured | Only GPT-4 Turbo measured |
| MMLU | 81.3% | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: science | 1256 | 1265 | Mistral Small 3.1 24B |
| LMArena Text: medicine and healthcare | 1239 | 1267 | Mistral Small 3.1 24B |
| LMArena Text: legal and government | 1265 | 1271 | Mistral Small 3.1 24B |
| LMArena Text: business and finance | 1222 | 1257 | Mistral Small 3.1 24B |
| Neither model has a result on the other 10 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4 Turbo | 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 index515
| Benchmark | GPT-4 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| DTBench | 61.6% | Not measured | Only GPT-4 Turbo measured |
| LMCA | 9.8% | Not measured | Only GPT-4 Turbo measured |
| LMArena Text | 1272 | 1277 | Mistral Small 3.1 24B |
| LMArena Text: instruction following | 1249 | 1263 | Mistral Small 3.1 24B |
| LMArena Text: creative writing | 1268 | 1252 | GPT-4 Turbo |
| LMArena Vision | 1090 | 1136 | Mistral Small 3.1 24B |
| LMArena Text: English | 1291 | 1295 | Mistral Small 3.1 24B |
| LMArena Text: non-English | 1245 | 1255 | Mistral Small 3.1 24B |
| LMArena Text: Chinese | 1242 | 1253 | Mistral Small 3.1 24B |
| LMArena Text: German | 1259 | 1266 | Mistral Small 3.1 24B |
| LMArena Text: Japanese | 1194 | 1208 | Mistral Small 3.1 24B |
| LMArena Text: Korean | 1187 | 1207 | Mistral Small 3.1 24B |
| LMArena Text: French | 1276 | 1273 | GPT-4 Turbo |
| LMArena Text: Spanish | 1260 | 1284 | Mistral Small 3.1 24B |
| LMArena Text: Russian | 1259 | 1263 | Mistral Small 3.1 24B |
| LMArena Text: Polish | 1302 | 1242 | GPT-4 Turbo |
| LMArena Text: multi-turn | 1267 | 1270 | Mistral Small 3.1 24B |
| LMArena Text: longer queries | 1254 | 1299 | Mistral Small 3.1 24B |
| LMArena Text: writing and language | 1279 | 1268 | GPT-4 Turbo |
| LMArena Text: entertainment and media | 1258 | 1250 | GPT-4 Turbo |
| LMArena Vision: English | 1097 | 1157 | Mistral Small 3.1 24B |
| LMArena Vision: Chinese | 1045 | 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 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4 Turbo | 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-4 Turbo | Mistral Small 3.1 24B |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | April 9, 2024 | March 17, 2025 |
| Context window | 128K | 128K |
| Input $/Mtok | $10.00 | $0.351 |
| Output $/Mtok | $30.00 | $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-4 Turbo 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-4 Turbo for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, GPT-4 Turbo or Mistral Small 3.1 24B?
GPT-4 Turbo costs $10.00 per million input tokens and $30.00 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-4 Turbo or Mistral Small 3.1 24B?
Neither: both take 128K tokens.
How many benchmarks is the GPT-4 Turbo vs Mistral Small 3.1 24B comparison based on?
31 benchmarks have a result for both models as of October 22, 2026. GPT-4 Turbo'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.