GPT-3.5 Turbo vs Mistral Small 3.1 24B
Mistral Small 3.1 24B costs 2.7x less per output token than GPT-3.5 Turbo ($0.555 vs $1.50 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.50
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.555
GPT-3.5 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.
Compare them on price, context and the boards below.
No benchmark has tested both yet. GPT-3.5 Turbo has results on AA Coding Index, SciCode and AA Intelligence Index; Mistral Small 3.1 24B on LMArena Text: coding, LMArena Text: software and IT and LMArena Text: hard prompts. Compare them on price and context instead.
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-3.5 Turbo has a AA Intelligence Index result, 5.5.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-3.5 Turbo has a GPQA Diamond result, 30.6%.
Directional only
Long documents
Listed context window
Mistral Small 3.1 24B
Mistral Small 3.1 24B takes 128K tokens against 16K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3.1 24B
GPT-3.5 Turbo $0.0013, Mistral Small 3.1 24B $0.0006 per turn.
List prices
At a glance
- Coding index
- GPT-3.5 Turbo not benchmarked, Mistral Small 3.1 24B not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-3.5 Turbo $1.50 against Mistral Small 3.1 24B $0.555 per million output tokens, 2.7x apart.
- Context window
- GPT-3.5 Turbo takes 16K tokens, Mistral Small 3.1 24B 128K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured
| Benchmark | GPT-3.5 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| AA Coding Index | 10.7 | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: coding | Not measured | 1309 | Only Mistral Small 3.1 24B measured |
| LMArena Text: software and IT | Not measured | 1301 | Only Mistral Small 3.1 24B measured |
| SciCode | 0.0% | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 39 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-3.5 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.5 | Not measured | Only GPT-3.5 Turbo measured |
| Neither model has a result on the other 1 board here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | GPT-3.5 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| GPQA Diamond | 30.6% | Not measured | Only GPT-3.5 Turbo measured |
| GPQA Diamond (Artificial Analysis run) | 29.7% | Not measured | Only GPT-3.5 Turbo measured |
| BIG-Bench Hard | 61.6% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: hard prompts | Not measured | 1278 | Only Mistral Small 3.1 24B measured |
| LMArena Text: expert | Not measured | 1257 | Only Mistral Small 3.1 24B measured |
| LMArena Text: hard prompts in English | Not measured | 1290 | Only Mistral Small 3.1 24B measured |
| 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 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GPT-3.5 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| GSM8K | 57.8% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: math | Not measured | 1261 | Only Mistral Small 3.1 24B measured |
| LMArena Text: mathematical work | Not measured | 1271 | Only Mistral Small 3.1 24B measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | GPT-3.5 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 64.4% | Not measured | Only GPT-3.5 Turbo measured |
| MedQA (Vals AI) | 58.5% | Not measured | Only GPT-3.5 Turbo measured |
| MMLU Pro (Artificial Analysis run) | 46.2% | Not measured | Only GPT-3.5 Turbo measured |
| MMLU | 68.5% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text: science | Not measured | 1265 | Only Mistral Small 3.1 24B measured |
| LMArena Text: medicine and healthcare | Not measured | 1267 | Only Mistral Small 3.1 24B measured |
| LMArena Text: legal and government | Not measured | 1271 | Only Mistral Small 3.1 24B measured |
| LMArena Text: business and finance | Not measured | 1257 | Only Mistral Small 3.1 24B measured |
| Neither model has a result on the other 12 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index27 boards measured
| Benchmark | GPT-3.5 Turbo | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| DTBench | 48.5% | Not measured | Only GPT-3.5 Turbo measured |
| LMCA | 9.7% | Not measured | Only GPT-3.5 Turbo measured |
| LMArena Text | Not measured | 1277 | Only Mistral Small 3.1 24B measured |
| LMArena Text: instruction following | Not measured | 1263 | Only Mistral Small 3.1 24B measured |
| LMArena Text: creative writing | Not measured | 1252 | Only Mistral Small 3.1 24B measured |
| LMArena Vision | Not measured | 1136 | Only Mistral Small 3.1 24B measured |
| LMArena Text: English | Not measured | 1295 | Only Mistral Small 3.1 24B measured |
| LMArena Text: non-English | Not measured | 1255 | Only Mistral Small 3.1 24B measured |
| LMArena Text: Chinese | Not measured | 1253 | Only Mistral Small 3.1 24B measured |
| LMArena Text: German | Not measured | 1266 | Only Mistral Small 3.1 24B measured |
| LMArena Text: Japanese | Not measured | 1208 | Only Mistral Small 3.1 24B measured |
| LMArena Text: Korean | Not measured | 1207 | Only Mistral Small 3.1 24B measured |
| LMArena Text: French | Not measured | 1273 | Only Mistral Small 3.1 24B measured |
| LMArena Text: Spanish | Not measured | 1284 | Only Mistral Small 3.1 24B measured |
| LMArena Text: Russian | Not measured | 1263 | Only Mistral Small 3.1 24B measured |
| LMArena Text: Polish | Not measured | 1242 | Only Mistral Small 3.1 24B measured |
| LMArena Text: multi-turn | Not measured | 1270 | Only Mistral Small 3.1 24B measured |
| LMArena Text: longer queries | Not measured | 1299 | Only Mistral Small 3.1 24B measured |
| LMArena Text: writing and language | Not measured | 1268 | Only Mistral Small 3.1 24B measured |
| LMArena Text: entertainment and media | Not measured | 1250 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: English | Not measured | 1157 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: Chinese | Not measured | 1155 | Only Mistral Small 3.1 24B measured |
| 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 | |||
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-3.5 Turbo | Mistral Small 3.1 24B |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | May 28, 2023 | March 17, 2025 |
| Context window | 16K | 128K |
| Input $/Mtok | $0.50 | $0.351 |
| Output $/Mtok | $1.50 | $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-3.5 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. Compare them on price, context and the boards below.
Which is cheaper, GPT-3.5 Turbo or Mistral Small 3.1 24B?
GPT-3.5 Turbo costs $0.50 per million input tokens and $1.50 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-3.5 Turbo or Mistral Small 3.1 24B?
Mistral Small 3.1 24B, with 128K tokens against 16K.
Has any benchmark tested both GPT-3.5 Turbo and Mistral Small 3.1 24B?
No benchmark has tested both yet. GPT-3.5 Turbo has results on AA Coding Index, SciCode and AA Intelligence Index; Mistral Small 3.1 24B on LMArena Text: coding, LMArena Text: software and IT and LMArena Text: hard prompts. Compare them on price and context instead. Data as of October 22, 2026.