Mistral Small 3.1 24B vs Qwen2.5 72B Instruct
Qwen2.5 72B Instruct costs 1.4x less per output token than Mistral Small 3.1 24B ($0.40 vs $0.555 per million). Updated October 22, 2026; 27 benchmarks have a result for both.
Mistral Small 3.1 24B or Qwen2.5 72B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Small 3.1 24B for a larger context window (128K against 33K tokens) and work measured by LMArena Text: math or LMArena Text: mathematical work, where it leads.
- Shared results
- 27
- Mistral Small 3.1 24B only
- 11
- Qwen2.5 72B Instruct only
- 26
- 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 Qwen2.5 72B Instruct has a AA Intelligence Index result, 7.7.
Directional only
Long documents
Listed context window
Mistral Small 3.1 24B
Mistral Small 3.1 24B takes 128K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 72B Instruct
Mistral Small 3.1 24B $0.0006, Qwen2.5 72B Instruct $0.0006 per turn.
List prices
At a glance
- Coding index
- Mistral Small 3.1 24B not benchmarked, Qwen2.5 72B Instruct not benchmarked.
- Widest category
- Math, 3.4 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMArena Text: entertainment and media: Mistral Small 3.1 24B 1250 against Qwen2.5 72B Instruct 1211, 6.5 points apart on a 0 to 100 scale.
- Output price
- Mistral Small 3.1 24B $0.555 against Qwen2.5 72B Instruct $0.40 per million output tokens, 1.4x apart.
- Context window
- Mistral Small 3.1 24B takes 128K tokens, Qwen2.5 72B Instruct 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 | Mistral Small 3.1 24B | Bars | Qwen2.5 72B Instruct | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Reasoning | 3 | 0 | ||
| Math | 0 | 2 | ||
| Knowledge | 2 | 2 | ||
| General | 12 | 4 | ||
| All shared boards | 19 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Mistral Small 3.1 24B | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 27.6% | Only Qwen2.5 72B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 4.5% | Only Qwen2.5 72B Instruct measured |
| WeirdML | Not measured | 16.0% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: coding | 1309 | 1292 | Mistral Small 3.1 24B |
| LMArena Text: software and IT | 1301 | 1292 | Mistral Small 3.1 24B |
| Neither model has a result on the other 34 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Small 3.1 24B | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 7.7 | Only Qwen2.5 72B Instruct measured |
| Epoch Capabilities Index | Not measured | 129.0 | Only Qwen2.5 72B Instruct measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Mistral Small 3.1 24B | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 34.5% | Only Qwen2.5 72B Instruct measured |
| METR time horizons | Not measured | 35.8% | Only Qwen2.5 72B Instruct measured |
| BALROG | Not measured | 16.2% | Only Qwen2.5 72B Instruct measured |
| TheAgentCompany | Not measured | 5.7% | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Mistral Small 3.1 24B | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 49.1% | Only Qwen2.5 72B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 3.6% | Only Qwen2.5 72B Instruct measured |
| GPQA Diamond (Epoch AI run) | Not measured | 49.1% | Only Qwen2.5 72B Instruct measured |
| BIG-Bench Hard | Not measured | 79.8% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: hard prompts | 1278 | 1271 | Mistral Small 3.1 24B |
| LMArena Text: expert | 1257 | 1245 | Mistral Small 3.1 24B |
| LMArena Text: hard prompts in English | 1290 | 1279 | Mistral Small 3.1 24B |
| LMArena Vision: diagrams | 1119 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: homework | 1158 | Not measured | Only Mistral Small 3.1 24B measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Small 3.1 24B | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 14.0 | Only Qwen2.5 72B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 14.0% | Only Qwen2.5 72B Instruct measured |
| OTIS Mock AIME | Not measured | 8.1% | Only Qwen2.5 72B Instruct measured |
| MATH level 5 | Not measured | 63.2% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: math | 1261 | 1283 | Qwen2.5 72B Instruct |
| LMArena Text: mathematical work | 1271 | 1290 | Qwen2.5 72B Instruct |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Mistral Small 3.1 24B | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 72.0% | Only Qwen2.5 72B Instruct measured |
| MMLU | Not measured | 85.3% | Only Qwen2.5 72B Instruct measured |
| AI2 Reasoning Challenge | Not measured | 94.5% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: science | 1265 | 1275 | Qwen2.5 72B Instruct |
| LMArena Text: medicine and healthcare | 1267 | 1258 | Mistral Small 3.1 24B |
| LMArena Text: legal and government | 1271 | 1288 | Qwen2.5 72B Instruct |
| LMArena Text: business and finance | 1257 | 1253 | Mistral Small 3.1 24B |
| Neither model has a result on the other 11 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Small 3.1 24B | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index124
| Benchmark | Mistral Small 3.1 24B | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| IFBench | Not measured | 36.9% | Only Qwen2.5 72B Instruct measured |
| DTBench | Not measured | 62.9% | Only Qwen2.5 72B Instruct measured |
| LMCA | Not measured | 13.4% | Only Qwen2.5 72B Instruct measured |
| HellaSwag | Not measured | 84.8% | Only Qwen2.5 72B Instruct measured |
| WinoGrande | Not measured | 82.3% | Only Qwen2.5 72B Instruct measured |
| PIQA | Not measured | 82.6% | Only Qwen2.5 72B Instruct measured |
| LMArena Text | 1277 | 1269 | Mistral Small 3.1 24B |
| LMArena Text: instruction following | 1263 | 1254 | Mistral Small 3.1 24B |
| LMArena Text: creative writing | 1252 | 1221 | Mistral Small 3.1 24B |
| LMArena Vision | 1136 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Text: English | 1295 | 1283 | Mistral Small 3.1 24B |
| LMArena Text: non-English | 1255 | 1252 | Mistral Small 3.1 24B |
| LMArena Text: Chinese | 1253 | 1273 | Qwen2.5 72B Instruct |
| LMArena Text: German | 1266 | 1234 | Mistral Small 3.1 24B |
| LMArena Text: Japanese | 1208 | 1180 | Mistral Small 3.1 24B |
| LMArena Text: Korean | 1207 | 1188 | Mistral Small 3.1 24B |
| LMArena Text: French | 1273 | 1280 | Qwen2.5 72B Instruct |
| LMArena Text: Spanish | 1284 | 1255 | Mistral Small 3.1 24B |
| LMArena Text: Russian | 1263 | 1264 | Qwen2.5 72B Instruct |
| LMArena Text: Polish | 1242 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Text: multi-turn | 1270 | 1272 | Qwen2.5 72B Instruct |
| LMArena Text: longer queries | 1299 | 1281 | Mistral Small 3.1 24B |
| LMArena Text: writing and language | 1268 | 1247 | Mistral Small 3.1 24B |
| LMArena Text: entertainment and media | 1250 | 1211 | Mistral Small 3.1 24B |
| LMArena Vision: English | 1157 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: Chinese | 1155 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: reading text | 1132 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: humor | 1142 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: captioning | 1153 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: recognizing things | 1155 | Not measured | Only Mistral Small 3.1 24B measured |
| LMArena Vision: creative writing | 1123 | Not measured | Only Mistral Small 3.1 24B measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Small 3.1 24B | Qwen2.5 72B Instruct | 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
Qwen2.5 72B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 72B Instruct 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 | Mistral Small 3.1 24B | Qwen2.5 72B Instruct |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | Open weights | Open weights |
| Released | March 17, 2025 | September 19, 2024 |
| Context window | 128K | 33K |
| Input $/Mtok | $0.351 | $0.36 |
| Output $/Mtok | $0.555 | $0.40 |
| 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 Mistral Small 3.1 24B better than Qwen2.5 72B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Small 3.1 24B for a larger context window (128K against 33K tokens) and work measured by LMArena Text: math or LMArena Text: mathematical work, where it leads.
Which is cheaper, Mistral Small 3.1 24B or Qwen2.5 72B Instruct?
Mistral Small 3.1 24B costs $0.351 per million input tokens and $0.555 per million output tokens; Qwen2.5 72B Instruct costs $0.36 and $0.40. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Small 3.1 24B or Qwen2.5 72B Instruct?
Mistral Small 3.1 24B, with 128K tokens against 33K.
How many benchmarks is the Mistral Small 3.1 24B vs Qwen2.5 72B Instruct comparison based on?
27 benchmarks have a result for both models as of October 22, 2026. Mistral Small 3.1 24B's coding index rests on 0 independent benchmarks and Qwen2.5 72B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.