Nova Pro 1.0 vs Mistral Small 3
Nova Pro 1.0 leads Mistral Small 3 on the Artificial Analysis Intelligence Index, 7.0 to 6.7, and Mistral Small 3 costs 40.0x less per output token ($0.08 vs $3.20 per million). Updated October 22, 2026; 36 benchmarks have a result for both.
Nova Pro 1.0 or Mistral Small 3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nova Pro 1.0 for a larger context window (300K against 33K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or τ²-Bench Telecom, where it leads.
- Shared results
- 36
- Nova Pro 1.0 only
- 6
- Mistral Small 3 only
- 0
- Like-for-like categories
- 7 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
Nova Pro 1.0
Nova Pro 1.0 leads, 7.0 against 6.7.
Same board, both measured
Web design
Design Arena: websites
No call
Only Nova Pro 1.0 has a Design Arena: websites result, 796.
Directional only
Long documents
Listed context window
Nova Pro 1.0
Nova Pro 1.0 takes 300K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3
Nova Pro 1.0 $0.0024, Mistral Small 3 $0.0001 per turn.
List prices
At a glance
- Coding index
- Nova Pro 1.0 not benchmarked, Mistral Small 3 not benchmarked.
- Widest category
- General, 6.7 points apart on average over 17 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): Nova Pro 1.0 21.0% against Mistral Small 3 0.0%, 21.0 points apart on a 0 to 100 scale.
- Output price
- Nova Pro 1.0 $3.20 against Mistral Small 3 $0.08 per million output tokens, 40.0x apart.
- Context window
- Nova Pro 1.0 takes 300K 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 | Nova Pro 1.0 | Bars | Mistral Small 3 | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 4 | 1 | ||
| Math | 4 | 0 | ||
| Knowledge | 5 | 0 | ||
| General | 17 | 0 | ||
| All shared boards | 33 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
| Benchmark | Nova Pro 1.0 | Mistral Small 3 | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 23.3% | 25.2% | Mistral Small 3 |
| Terminal-Bench Hard (Artificial Analysis run) | 6.1% | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: coding | 1270 | 1246 | Nova Pro 1.0 |
| LMArena Text: software and IT | 1271 | 1248 | Nova Pro 1.0 |
| Neither model has a result on the other 35 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Nova Pro 1.0 | Mistral Small 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.0 | 6.7 | Nova Pro 1.0 |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Pro 1.0 | Mistral Small 3 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 14.0% | 19.6% | Mistral Small 3 |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | Nova Pro 1.0 | Mistral Small 3 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 49.9% | 46.2% | Nova Pro 1.0 |
| Humanity's Last Exam (Artificial Analysis run) | 3.2% | 3.8% | Mistral Small 3 |
| LMArena Text: hard prompts | 1246 | 1233 | Nova Pro 1.0 |
| LMArena Text: expert | 1211 | 1202 | Nova Pro 1.0 |
| LMArena Text: hard prompts in English | 1259 | 1243 | Nova Pro 1.0 |
| Neither model has a result on the other 17 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Nova Pro 1.0 | Mistral Small 3 | Leader |
|---|---|---|---|
| AA Math Index | 7.0 | 4.3 | Nova Pro 1.0 |
| AIME 2025 (Artificial Analysis run) | 7.0% | 4.3% | Nova Pro 1.0 |
| LMArena Text: math | 1252 | 1240 | Nova Pro 1.0 |
| LMArena Text: mathematical work | 1261 | 1243 | Nova Pro 1.0 |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Nova Pro 1.0 | Mistral Small 3 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 69.1% | 65.2% | Nova Pro 1.0 |
| MMLU | 82.0% | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: science | 1255 | 1235 | Nova Pro 1.0 |
| LMArena Text: medicine and healthcare | 1260 | 1215 | Nova Pro 1.0 |
| LMArena Text: legal and government | 1281 | 1219 | Nova Pro 1.0 |
| LMArena Text: business and finance | 1229 | 1205 | Nova Pro 1.0 |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Pro 1.0 | Mistral Small 3 | Leader |
|---|---|---|---|
| Design Arena: websites | 796 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index170
| Benchmark | Nova Pro 1.0 | Mistral Small 3 | Leader |
|---|---|---|---|
| IFBench | 38.1% | 26.4% | Nova Pro 1.0 |
| Long context reasoning (AA-LCR) | 21.0% | 0.0% | Nova Pro 1.0 |
| LMArena Text | 1259 | 1234 | Nova Pro 1.0 |
| LMArena Text: instruction following | 1235 | 1214 | Nova Pro 1.0 |
| LMArena Text: creative writing | 1212 | 1194 | Nova Pro 1.0 |
| LMArena Vision | 980 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: English | 1276 | 1256 | Nova Pro 1.0 |
| LMArena Text: non-English | 1233 | 1198 | Nova Pro 1.0 |
| LMArena Text: Chinese | 1244 | 1204 | Nova Pro 1.0 |
| LMArena Text: German | 1243 | 1211 | Nova Pro 1.0 |
| LMArena Text: Japanese | 1200 | 1111 | Nova Pro 1.0 |
| LMArena Text: Korean | 1203 | 1188 | Nova Pro 1.0 |
| LMArena Text: French | 1271 | 1204 | Nova Pro 1.0 |
| LMArena Text: Spanish | 1182 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Russian | 1240 | 1216 | Nova Pro 1.0 |
| LMArena Text: multi-turn | 1246 | 1217 | Nova Pro 1.0 |
| LMArena Text: longer queries | 1255 | 1246 | Nova Pro 1.0 |
| LMArena Text: writing and language | 1247 | 1214 | Nova Pro 1.0 |
| LMArena Text: entertainment and media | 1210 | 1184 | Nova Pro 1.0 |
| LMArena Vision: English | 987 | Not measured | Only Nova Pro 1.0 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 | Nova Pro 1.0 | 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 | Amazon Nova Pro 1.0 | Mistral Small 3 |
|---|---|---|
| Maker | Amazon | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | December 5, 2024 | January 30, 2025 |
| Context window | 300K | 33K |
| Input $/Mtok | $0.80 | $0.05 |
| Output $/Mtok | $3.20 | $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 Nova Pro 1.0 better than Mistral Small 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Pro 1.0 for a larger context window (300K against 33K tokens) and work measured by LiveCodeBench (Artificial Analysis run) or τ²-Bench Telecom, where it leads.
Which is cheaper, Nova Pro 1.0 or Mistral Small 3?
Nova Pro 1.0 costs $0.80 per million input tokens and $3.20 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, Nova Pro 1.0 or Mistral Small 3?
Nova Pro 1.0, with 300K tokens against 33K.
How many benchmarks is the Nova Pro 1.0 vs Mistral Small 3 comparison based on?
36 benchmarks have a result for both models as of October 22, 2026. Nova Pro 1.0'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.