GPT-4o-mini vs Mistral Small 3
GPT-4o-mini and Mistral Small 3 tie on the Artificial Analysis Intelligence Index at 6.7, and Mistral Small 3 costs 7.5x less per output token ($0.08 vs $0.60 per million). Updated October 21, 2026; 8 benchmarks have a result for both.
GPT-4o-mini or Mistral Small 3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4o-mini for a larger context window (128K against 33K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or GPQA Diamond (Artificial Analysis run), where it leads.
- Shared results
- 8
- GPT-4o-mini only
- 21
- Mistral Small 3 only
- 28
- Like-for-like categories
- 6 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
Tied at 6.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-4o-mini has a GPQA Diamond result, 44.2%.
Directional only
Math
AIME
No call
Only GPT-4o-mini has a AIME result, 11.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4o-mini has a MMLU Pro result, 62.7%.
Directional only
Long documents
Listed context window
GPT-4o-mini
GPT-4o-mini takes 128K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3
GPT-4o-mini $0.0004, Mistral Small 3 $0.0001 per turn.
List prices
At a glance
- Coding index
- GPT-4o-mini not benchmarked, Mistral Small 3 not benchmarked.
- Widest category
- Math, 10.4 points apart on average over 2 shared benchmarks.
- Widest single gap
- AA Math Index: GPT-4o-mini 14.7 against Mistral Small 3 4.3, 10.4 points apart on a 0 to 100 scale.
- Output price
- GPT-4o-mini $0.60 against Mistral Small 3 $0.08 per million output tokens, 7.5x apart.
- Context window
- GPT-4o-mini takes 128K tokens, Mistral Small 3 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 | GPT-4o-mini | Bars | Mistral Small 3 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 0 | 1 tie | |
| Reasoning | 1 | 1 | ||
| Math | 2 | 0 | ||
| Knowledge | 0 | 1 | ||
| General | 1 | 0 | ||
| All shared boards | 4 | 3 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | GPT-4o-mini | Mistral Small 3 | Leader |
|---|---|---|---|
| AA Coding Index | 11.4 | Not measured | Only GPT-4o-mini measured |
| LiveCodeBench (Vals AI) | 26.4% | Not measured | Only GPT-4o-mini measured |
| LiveCodeBench (Artificial Analysis run) | 23.4% | 25.2% | Mistral Small 3 |
| LMArena Text: coding | Not measured | 1246 | Only Mistral Small 3 measured |
| LMArena Text: software and IT | Not measured | 1248 | Only Mistral Small 3 measured |
| SciCode | 1.5% | Not measured | Only GPT-4o-mini measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index00
| Benchmark | GPT-4o-mini | Mistral Small 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 6.7 | Tie |
| Epoch Capabilities Index | 126.5 | Not measured | Only GPT-4o-mini measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-4o-mini | Mistral Small 3 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 19.6% | Only Mistral Small 3 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-4o-mini | Mistral Small 3 | Leader |
|---|---|---|---|
| GPQA Diamond | 44.2% | Not measured | Only GPT-4o-mini measured |
| MMMU Pro (Vals AI) | 56.6% | Not measured | Only GPT-4o-mini measured |
| GPQA Diamond (Artificial Analysis run) | 42.6% | 46.2% | Mistral Small 3 |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 3.8% | GPT-4o-mini |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: hard prompts | Not measured | 1233 | Only Mistral Small 3 measured |
| LMArena Text: expert | Not measured | 1202 | Only Mistral Small 3 measured |
| LMArena Text: hard prompts in English | Not measured | 1243 | Only Mistral Small 3 measured |
| Kagi LLM Benchmark | 28.8% | Not measured | Only GPT-4o-mini measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-4o-mini | Mistral Small 3 | Leader |
|---|---|---|---|
| AIME | 11.5% | Not measured | Only GPT-4o-mini measured |
| MATH 500 (Vals AI) | 72.6% | Not measured | Only GPT-4o-mini measured |
| MGSM (Vals AI) | 86.2% | Not measured | Only GPT-4o-mini measured |
| AA Math Index | 14.7 | 4.3 | GPT-4o-mini |
| AIME 2025 (Artificial Analysis run) | 14.7% | 4.3% | GPT-4o-mini |
| GSM8K | 91.3% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: math | Not measured | 1240 | Only Mistral Small 3 measured |
| LMArena Text: mathematical work | Not measured | 1243 | Only Mistral Small 3 measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o-mini | Mistral Small 3 | Leader |
|---|---|---|---|
| MMLU Pro | 62.7% | Not measured | Only GPT-4o-mini measured |
| CorpFin (Vals AI) | 45.5% | Not measured | Only GPT-4o-mini measured |
| TaxEval (Vals AI) | 60.5% | Not measured | Only GPT-4o-mini measured |
| MortgageTax (Vals AI) | 54.5% | Not measured | Only GPT-4o-mini measured |
| MedQA (Vals AI) | 72.4% | Not measured | Only GPT-4o-mini measured |
| MMLU Pro (Artificial Analysis run) | 64.8% | 65.2% | Mistral Small 3 |
| MMLU | 81.8% | Not measured | Only GPT-4o-mini measured |
| LMArena Text: science | Not measured | 1235 | Only Mistral Small 3 measured |
| LMArena Text: medicine and healthcare | Not measured | 1215 | Only Mistral Small 3 measured |
| LMArena Text: legal and government | Not measured | 1219 | Only Mistral Small 3 measured |
| LMArena Text: business and finance | Not measured | 1205 | Only Mistral Small 3 measured |
| Neither model has a result on the other 7 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o-mini | Mistral Small 3 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-4o-mini | Mistral Small 3 | Leader |
|---|---|---|---|
| IFBench | 31.0% | 26.4% | GPT-4o-mini |
| Long context reasoning (AA-LCR) | Not measured | 0.0% | Only Mistral Small 3 measured |
| DTBench | 54.4% | Not measured | Only GPT-4o-mini measured |
| LMCA | 10.4% | Not measured | Only GPT-4o-mini measured |
| PIQA | 88.7% | Not measured | Only GPT-4o-mini measured |
| LMArena Text | Not measured | 1234 | Only Mistral Small 3 measured |
| LMArena Text: instruction following | Not measured | 1214 | Only Mistral Small 3 measured |
| LMArena Text: creative writing | Not measured | 1194 | Only Mistral Small 3 measured |
| LMArena Text: English | Not measured | 1256 | Only Mistral Small 3 measured |
| LMArena Text: non-English | Not measured | 1198 | Only Mistral Small 3 measured |
| LMArena Text: Chinese | Not measured | 1204 | Only Mistral Small 3 measured |
| LMArena Text: German | Not measured | 1211 | Only Mistral Small 3 measured |
| LMArena Text: Japanese | Not measured | 1111 | Only Mistral Small 3 measured |
| LMArena Text: Korean | Not measured | 1188 | Only Mistral Small 3 measured |
| LMArena Text: French | Not measured | 1204 | Only Mistral Small 3 measured |
| LMArena Text: Russian | Not measured | 1216 | Only Mistral Small 3 measured |
| LMArena Text: multi-turn | Not measured | 1217 | Only Mistral Small 3 measured |
| LMArena Text: longer queries | Not measured | 1246 | Only Mistral Small 3 measured |
| LMArena Text: writing and language | Not measured | 1214 | Only Mistral Small 3 measured |
| LMArena Text: entertainment and media | Not measured | 1184 | Only Mistral Small 3 measured |
| Neither model has a result on the other 26 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o-mini | Mistral Small 3 | 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 costs less
Repository review
50K input + 3K output tokens
Mistral Small 3 costs less
Agent loop
200K input + 10K output tokens
Mistral Small 3 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-mini | Mistral Small 3 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | July 18, 2024 | January 30, 2025 |
| Context window | 128K | 33K |
| Input $/Mtok | $0.15 | $0.05 |
| Output $/Mtok | $0.60 | $0.08 |
| 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-mini better than Mistral Small 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o-mini for a larger context window (128K against 33K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or GPQA Diamond (Artificial Analysis run), where it leads.
Which is cheaper, GPT-4o-mini or Mistral Small 3?
GPT-4o-mini costs $0.15 per million input tokens and $0.60 per million output tokens; Mistral Small 3 costs $0.05 and $0.08. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o-mini or Mistral Small 3?
GPT-4o-mini, with 128K tokens against 33K.
How many benchmarks is the GPT-4o-mini vs Mistral Small 3 comparison based on?
8 benchmarks have a result for both models as of October 21, 2026. GPT-4o-mini's coding index rests on 0 independent benchmarks and Mistral Small 3's on 0. Where only one model has a result, the page says so instead of naming a winner.