GPT-5.4 Mini vs Mistral Small 3.1 24B
Mistral Small 3.1 24B costs 8.1x less per output token than GPT-5.4 Mini ($0.555 vs $4.50 per million). Updated October 21, 2026; 37 benchmarks have a result for both.
GPT-5.4 Mini or Mistral Small 3.1 24B: which to pick
Only GPT-5.4 Mini has a coding score, 35.8 on the Vibe Coding Index; Mistral Small 3.1 24B has none, so the two cannot be ranked on coding.
Pick Mistral Small 3.1 24B for output tokens 8.1x cheaper ($0.555 vs $4.50 per million).
- Shared results
- 37
- GPT-5.4 Mini only
- 52
- Mistral Small 3.1 24B only
- 1
- 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
Only GPT-5.4 Mini has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-5.4 Mini has a AA Intelligence Index result, 24.1.
Directional only
Agentic work
AA Agentic Index
No call
Only GPT-5.4 Mini has a AA Agentic Index result, 17.9.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.4 Mini has a GPQA Diamond result, 83.1%.
Directional only
Math
AIME
No call
Only GPT-5.4 Mini has a AIME result, 95.6%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.4 Mini has a MMLU Pro result, 84.5%.
Directional only
Long documents
Listed context window
GPT-5.4 Mini
GPT-5.4 Mini takes 400K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3.1 24B
GPT-5.4 Mini $0.0030, Mistral Small 3.1 24B $0.0006 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.4 Mini has the number, $0.70.
Directional only
At a glance
- Coding index
- GPT-5.4 Mini 35.8 from 5 benchmarks, Mistral Small 3.1 24B not benchmarked.
- Widest category
- Math, 26.2 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMArena Text: Chinese: GPT-5.4 Mini 1446 against Mistral Small 3.1 24B 1253, 32.3 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 Mini $4.50 against Mistral Small 3.1 24B $0.555 per million output tokens, 8.1x apart.
- Context window
- GPT-5.4 Mini takes 400K tokens, Mistral Small 3.1 24B 128K.
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-5.4 Mini | Bars | Mistral Small 3.1 24B | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 24 | 0 | ||
| All shared boards | 37 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | GPT-5.4 Mini | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| LMArena WebDev | 1397 | Not measured | Only GPT-5.4 Mini measured |
| AA Coding Index | 56.1 | Not measured | Only GPT-5.4 Mini measured |
| LiveCodeBench (Vals AI) | 81.5% | Not measured | Only GPT-5.4 Mini measured |
| SWE-bench Verified (Vals AI) | 73.0% | Not measured | Only GPT-5.4 Mini measured |
| Terminal-Bench 4 (Vals AI) | 2.5% | Not measured | Only GPT-5.4 Mini measured |
| Vibe Code Bench (Vals AI) | 48.0% | Not measured | Only GPT-5.4 Mini measured |
| Code migration (Vals AI) | 12.9% | Not measured | Only GPT-5.4 Mini measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only GPT-5.4 Mini measured |
| Terminal-Bench 2.1 (Vals AI) | 54.7% | Not measured | Only GPT-5.4 Mini measured |
| SciCode | 52.1% | Not measured | Only GPT-5.4 Mini measured |
| Terminal-Bench Hard (Artificial Analysis run) | 52.3% | Not measured | Only GPT-5.4 Mini measured |
| FrontierCode | 27.0% | Not measured | Only GPT-5.4 Mini measured |
| WeirdML | 60.3% | Not measured | Only GPT-5.4 Mini measured |
| ALE-Bench | 1188.6 | Not measured | Only GPT-5.4 Mini measured |
| LMArena Text: coding | 1438 | 1309 | GPT-5.4 Mini |
| LMArena Text: software and IT | 1436 | 1301 | GPT-5.4 Mini |
| LMArena WebDev: React | 1386 | Not measured | Only GPT-5.4 Mini measured |
| LMArena WebDev: HTML | 1419 | Not measured | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.4 Mini | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.1 | Not measured | Only GPT-5.4 Mini measured |
| Epoch Capabilities Index | 148.7 | Not measured | Only GPT-5.4 Mini measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-5.4 Mini | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| AA Agentic Index | 17.9 | Not measured | Only GPT-5.4 Mini measured |
| Finance Agent (Vals AI) | 45.4% | Not measured | Only GPT-5.4 Mini measured |
| Tax Agent Bench (Vals AI) | 8.8% | Not measured | Only GPT-5.4 Mini measured |
| Legal Research Bench (Vals AI) | 12.5% | Not measured | Only GPT-5.4 Mini measured |
| Excel Modeling Benchmark (Vals AI) | 45.4% | Not measured | Only GPT-5.4 Mini measured |
| τ²-Bench Telecom | 83.3% | Not measured | Only GPT-5.4 Mini measured |
| DeepResearch Bench | 36.3% | Not measured | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-5.4 Mini | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| GPQA Diamond | 83.1% | Not measured | Only GPT-5.4 Mini measured |
| MMMU Pro (Vals AI) | 79.3% | Not measured | Only GPT-5.4 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 87.5% | Not measured | Only GPT-5.4 Mini measured |
| Humanity's Last Exam (Artificial Analysis run) | 28.1% | Not measured | Only GPT-5.4 Mini measured |
| GPQA Diamond (Epoch AI run) | 86.9% | Not measured | Only GPT-5.4 Mini measured |
| ARC-AGI | 63.7% | Not measured | Only GPT-5.4 Mini measured |
| ARC-AGI-2 | 18.9% | Not measured | Only GPT-5.4 Mini measured |
| Chess puzzles | 23.0% | Not measured | Only GPT-5.4 Mini measured |
| Mystery game puzzles | 11.0% | Not measured | Only GPT-5.4 Mini measured |
| LMArena Text: hard prompts | 1424 | 1278 | GPT-5.4 Mini |
| LMArena Text: expert | 1435 | 1257 | GPT-5.4 Mini |
| LMArena Text: hard prompts in English | 1420 | 1290 | GPT-5.4 Mini |
| LMArena Vision: diagrams | 1266 | 1119 | GPT-5.4 Mini |
| LMArena Vision: homework | 1285 | 1158 | GPT-5.4 Mini |
| Kagi LLM Benchmark | 37.9% | Not measured | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 Mini | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| AIME | 95.6% | Not measured | Only GPT-5.4 Mini measured |
| OTIS Mock AIME | 88.9% | Not measured | Only GPT-5.4 Mini measured |
| FrontierMath, tiers 1 to 3 | 51.2% | Not measured | Only GPT-5.4 Mini measured |
| FrontierMath, tier 4 | 9.8% | Not measured | Only GPT-5.4 Mini measured |
| ProofBench | 21.0% | Not measured | Only GPT-5.4 Mini measured |
| LMArena Text: math | 1418 | 1261 | GPT-5.4 Mini |
| LMArena Text: mathematical work | 1429 | 1271 | GPT-5.4 Mini |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-5.4 Mini | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| MMLU Pro | 84.5% | Not measured | Only GPT-5.4 Mini measured |
| CaseLaw (Vals AI) | 51.7% | Not measured | Only GPT-5.4 Mini measured |
| CorpFin (Vals AI) | 60.9% | Not measured | Only GPT-5.4 Mini measured |
| TaxEval (Vals AI) | 71.2% | Not measured | Only GPT-5.4 Mini measured |
| MortgageTax (Vals AI) | 63.5% | Not measured | Only GPT-5.4 Mini measured |
| SimpleQA Verified | 29.4% | Not measured | Only GPT-5.4 Mini measured |
| LMArena Text: science | 1417 | 1265 | GPT-5.4 Mini |
| LMArena Text: medicine and healthcare | 1395 | 1267 | GPT-5.4 Mini |
| LMArena Text: legal and government | 1414 | 1271 | GPT-5.4 Mini |
| LMArena Text: business and finance | 1418 | 1257 | GPT-5.4 Mini |
| 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-5.4 Mini | 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 index240
| Benchmark | GPT-5.4 Mini | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 50.8% | Not measured | Only GPT-5.4 Mini measured |
| Vals Multimodal Index | 54.2% | Not measured | Only GPT-5.4 Mini measured |
| IFBench | 73.3% | Not measured | Only GPT-5.4 Mini measured |
| Long context reasoning (AA-LCR) | 77.0% | Not measured | Only GPT-5.4 Mini measured |
| DTBench | 80.0% | Not measured | Only GPT-5.4 Mini measured |
| LMCA | 40.8% | Not measured | Only GPT-5.4 Mini measured |
| LMArena Text | 1412 | 1277 | GPT-5.4 Mini |
| LMArena Text: instruction following | 1405 | 1263 | GPT-5.4 Mini |
| LMArena Text: creative writing | 1370 | 1252 | GPT-5.4 Mini |
| LMArena Vision | 1245 | 1136 | GPT-5.4 Mini |
| LMArena Text: English | 1412 | 1295 | GPT-5.4 Mini |
| LMArena Text: non-English | 1405 | 1255 | GPT-5.4 Mini |
| LMArena Text: Chinese | 1446 | 1253 | GPT-5.4 Mini |
| LMArena Text: German | 1408 | 1266 | GPT-5.4 Mini |
| LMArena Text: Japanese | 1375 | 1208 | GPT-5.4 Mini |
| LMArena Text: Korean | 1370 | 1207 | GPT-5.4 Mini |
| LMArena Text: French | 1441 | 1273 | GPT-5.4 Mini |
| LMArena Text: Spanish | 1405 | 1284 | GPT-5.4 Mini |
| LMArena Text: Russian | 1417 | 1263 | GPT-5.4 Mini |
| LMArena Text: Polish | 1415 | 1242 | GPT-5.4 Mini |
| LMArena Text: multi-turn | 1429 | 1270 | GPT-5.4 Mini |
| LMArena Text: longer queries | 1408 | 1299 | GPT-5.4 Mini |
| LMArena Text: writing and language | 1393 | 1268 | GPT-5.4 Mini |
| LMArena Text: entertainment and media | 1373 | 1250 | GPT-5.4 Mini |
| LMArena Vision: English | 1244 | 1157 | GPT-5.4 Mini |
| LMArena Vision: Chinese | 1286 | 1155 | GPT-5.4 Mini |
| LMArena Vision: reading text | 1253 | 1132 | GPT-5.4 Mini |
| LMArena Vision: humor | 1235 | 1142 | GPT-5.4 Mini |
| LMArena Vision: captioning | Not measured | 1153 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: recognizing things | 1218 | 1155 | GPT-5.4 Mini |
| LMArena Vision: creative writing | 1222 | 1123 | GPT-5.4 Mini |
| 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 | GPT-5.4 Mini | 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-5.4 Mini | Mistral Small 3.1 24B |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | March 17, 2026 | March 17, 2025 |
| Context window | 400K | 128K |
| Input $/Mtok | $0.75 | $0.351 |
| Output $/Mtok | $4.50 | $0.555 |
| Coding index | 35.8 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | $0.70 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 Mini better than Mistral Small 3.1 24B for coding?
Only GPT-5.4 Mini has a coding score, 35.8 on the Vibe Coding Index; Mistral Small 3.1 24B has none, so the two cannot be ranked on coding. Pick Mistral Small 3.1 24B for output tokens 8.1x cheaper ($0.555 vs $4.50 per million).
Which is cheaper, GPT-5.4 Mini or Mistral Small 3.1 24B?
GPT-5.4 Mini costs $0.75 per million input tokens and $4.50 per million output tokens; Mistral Small 3.1 24B costs $0.351 and $0.555. Cost per solved task is known for GPT-5.4 Mini only.
Which has the bigger context window, GPT-5.4 Mini or Mistral Small 3.1 24B?
GPT-5.4 Mini, with 400K tokens against 128K.
How many benchmarks is the GPT-5.4 Mini vs Mistral Small 3.1 24B comparison based on?
37 benchmarks have a result for both models as of October 21, 2026. GPT-5.4 Mini's coding index rests on 5 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.