Nova Pro 1.0 vs Mistral Large
Updated October 21, 2026. 33 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Nova Pro 1.0 has the edge where output tokens cost 1.9x less, and where the context window is larger, 300K against 128K tokens.
- Shared results
- 33
- Nova Pro 1.0 only
- 9
- Mistral Large only
- 11
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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 5.8.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Mistral Large has a GPQA Diamond result, 47.7%.
Directional only
Math
AIME
No call
Only Mistral Large has a AIME result, 9.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Large has a MMLU Pro result, 69.7%.
Directional only
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 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nova Pro 1.0
Nova Pro 1.0 $0.0024, Mistral Large $0.0050 per turn.
List prices
At a glance
- Coding index
- Nova Pro 1.0 not benchmarked, Mistral Large not benchmarked.
- Widest category
- Knowledge, 5.9 points apart on average over 6 shared benchmarks.
- Widest single gap
- MMLU Pro (Artificial Analysis run): Nova Pro 1.0 69.1% against Mistral Large 51.5%, 17.6 points apart on a 0 to 100 scale.
- Output price
- Nova Pro 1.0 $3.20 against Mistral Large $6.00 per million output tokens, 1.9x apart.
- Context window
- Nova Pro 1.0 takes 300K tokens, Mistral Large 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 | Nova Pro 1.0 | Bars | Mistral Large | Ties |
|---|---|---|---|---|
| Coding | 1 | 2 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 3 | ||
| Math | 1 | 1 | ||
| Knowledge | 4 | 2 | ||
| General | 4 | 12 | ||
| All shared boards | 13 | 20 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index12
| Benchmark | Nova Pro 1.0 | Mistral Large | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | Not measured | 37.1% | Only Mistral Large measured |
| LiveCodeBench (Artificial Analysis run) | 23.3% | 17.8% | Nova Pro 1.0 |
| Terminal-Bench Hard (Artificial Analysis run) | 6.1% | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: coding | 1270 | 1275 | Mistral Large |
| LMArena Text: software and IT | 1271 | 1274 | Mistral Large |
| Neither model has a result on the other 33 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Nova Pro 1.0 | Mistral Large | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.0 | 5.8 | Nova Pro 1.0 |
| Epoch Capabilities Index | Not measured | 122.1 | Only Mistral Large measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Pro 1.0 | Mistral Large | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 14.0% | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | Nova Pro 1.0 | Mistral Large | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 47.7% | Only Mistral Large measured |
| GPQA Diamond (Artificial Analysis run) | 49.9% | 35.1% | Nova Pro 1.0 |
| Humanity's Last Exam (Artificial Analysis run) | 3.2% | 3.5% | Mistral Large |
| LMArena Text: hard prompts | 1246 | 1257 | Mistral Large |
| LMArena Text: expert | 1211 | 1208 | Nova Pro 1.0 |
| LMArena Text: hard prompts in English | 1259 | 1268 | Mistral Large |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Nova Pro 1.0 | Mistral Large | Leader |
|---|---|---|---|
| AIME | Not measured | 9.2% | Only Mistral Large measured |
| MATH 500 (Vals AI) | Not measured | 74.4% | Only Mistral Large measured |
| MGSM (Vals AI) | Not measured | 87.2% | Only Mistral Large measured |
| AA Math Index | 7.0 | Not measured | Only Nova Pro 1.0 measured |
| AIME 2025 (Artificial Analysis run) | 7.0% | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: math | 1252 | 1261 | Mistral Large |
| LMArena Text: mathematical work | 1261 | 1257 | Nova Pro 1.0 |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index42
| Benchmark | Nova Pro 1.0 | Mistral Large | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 69.7% | Only Mistral Large measured |
| TaxEval (Vals AI) | Not measured | 63.8% | Only Mistral Large measured |
| MedQA (Vals AI) | Not measured | 76.2% | Only Mistral Large measured |
| MMLU Pro (Artificial Analysis run) | 69.1% | 51.5% | Nova Pro 1.0 |
| MMLU | 82.0% | 68.8% | Nova Pro 1.0 |
| LMArena Text: science | 1255 | 1260 | Mistral Large |
| LMArena Text: medicine and healthcare | 1260 | 1255 | Nova Pro 1.0 |
| LMArena Text: legal and government | 1281 | 1275 | Nova Pro 1.0 |
| LMArena Text: business and finance | 1229 | 1238 | Mistral Large |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Pro 1.0 | Mistral Large | 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 index412
| Benchmark | Nova Pro 1.0 | Mistral Large | Leader |
|---|---|---|---|
| IFBench | 38.1% | Not measured | Only Nova Pro 1.0 measured |
| Long context reasoning (AA-LCR) | 21.0% | Not measured | Only Nova Pro 1.0 measured |
| DTBench | Not measured | 60.8% | Only Mistral Large measured |
| LMArena Text | 1259 | 1265 | Mistral Large |
| LMArena Text: instruction following | 1235 | 1249 | Mistral Large |
| LMArena Text: creative writing | 1212 | 1242 | Mistral Large |
| LMArena Vision | 980 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: English | 1276 | 1284 | Mistral Large |
| LMArena Text: non-English | 1233 | 1235 | Mistral Large |
| LMArena Text: Chinese | 1244 | 1239 | Nova Pro 1.0 |
| LMArena Text: German | 1243 | 1242 | Nova Pro 1.0 |
| LMArena Text: Japanese | 1200 | 1170 | Nova Pro 1.0 |
| LMArena Text: Korean | 1203 | 1202 | Nova Pro 1.0 |
| LMArena Text: French | 1271 | 1325 | Mistral Large |
| LMArena Text: Spanish | 1182 | 1268 | Mistral Large |
| LMArena Text: Russian | 1240 | 1252 | Mistral Large |
| LMArena Text: Polish | Not measured | 1157 | Only Mistral Large measured |
| LMArena Text: multi-turn | 1246 | 1260 | Mistral Large |
| LMArena Text: longer queries | 1255 | 1261 | Mistral Large |
| LMArena Text: writing and language | 1247 | 1261 | Mistral Large |
| LMArena Text: entertainment and media | 1210 | 1230 | Mistral Large |
| LMArena Vision: English | 987 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Pro 1.0 | Mistral Large | 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
Nova Pro 1.0 costs less
Repository review
50K input + 3K output tokens
Nova Pro 1.0 costs less
Agent loop
200K input + 10K output tokens
Nova Pro 1.0 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 Large |
|---|---|---|
| Maker | Amazon | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | December 5, 2024 | February 26, 2024 |
| Context window | 300K | 128K |
| Input $/Mtok | $0.80 | $2.00 |
| Output $/Mtok | $3.20 | $6.00 |
| 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 Large for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Nova Pro 1.0 has the edge where output tokens cost 1.9x less, and where the context window is larger, 300K against 128K tokens.
Which is cheaper, Nova Pro 1.0 or Mistral Large?
Nova Pro 1.0 costs $0.80 per million input tokens and $3.20 per million output tokens; Mistral Large costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Nova Pro 1.0 or Mistral Large?
Nova Pro 1.0, with 300K tokens against 128K.
How many benchmarks is the Nova Pro 1.0 vs Mistral Large comparison based on?
33 benchmarks have a result for both models as of October 21, 2026. Nova Pro 1.0's coding index rests on 0 independent benchmarks and Mistral Large's on 0. Where only one model has a result, the page says so instead of naming a winner.