Nova Pro 1.0 vs Mistral Large 2407
Updated October 21, 2026. 11 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 131K tokens.
- Shared results
- 11
- Nova Pro 1.0 only
- 31
- Mistral Large 2407 only
- 6
- Like-for-like categories
- 7 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
Mistral Large 2407
Mistral Large 2407 leads, 7.6 against 7.0.
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 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nova Pro 1.0
Nova Pro 1.0 $0.0024, Mistral Large 2407 $0.0050 per turn.
List prices
At a glance
- Coding index
- Nova Pro 1.0 not benchmarked, Mistral Large 2407 not benchmarked.
- Widest category
- Agentic work, 19.0 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Nova Pro 1.0 14.0% against Mistral Large 2407 33.0%, 19.0 points apart on a 0 to 100 scale.
- Output price
- Nova Pro 1.0 $3.20 against Mistral Large 2407 $6.00 per million output tokens, 1.9x apart.
- Context window
- Nova Pro 1.0 takes 300K tokens, Mistral Large 2407 131K.
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 2407 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 2 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 2 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 8 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Nova Pro 1.0 | Mistral Large 2407 | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 23.3% | 26.7% | Mistral Large 2407 |
| Terminal-Bench Hard (Artificial Analysis run) | 6.1% | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: coding | 1270 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: software and IT | 1271 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Pro 1.0 | Mistral Large 2407 | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.0 | 7.6 | Mistral Large 2407 |
| 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 Large 2407 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 14.0% | 33.0% | Mistral Large 2407 |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Nova Pro 1.0 | Mistral Large 2407 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 49.9% | 47.2% | Nova Pro 1.0 |
| Humanity's Last Exam (Artificial Analysis run) | 3.2% | 2.9% | Nova Pro 1.0 |
| GPQA Diamond (Epoch AI run) | Not measured | 49.0% | Only Mistral Large 2407 measured |
| SimpleBench | Not measured | 22.5% | Only Mistral Large 2407 measured |
| LMArena Text: hard prompts | 1246 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: expert | 1211 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: hard prompts in English | 1259 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 14 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Nova Pro 1.0 | Mistral Large 2407 | Leader |
|---|---|---|---|
| AA Math Index | 7.0 | 0.0 | Nova Pro 1.0 |
| AIME 2025 (Artificial Analysis run) | 7.0% | 0.0% | Nova Pro 1.0 |
| OTIS Mock AIME | Not measured | 8.5% | Only Mistral Large 2407 measured |
| MATH level 5 | Not measured | 44.8% | Only Mistral Large 2407 measured |
| LMArena Text: math | 1252 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: mathematical work | 1261 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Nova Pro 1.0 | Mistral Large 2407 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 69.1% | 68.3% | Nova Pro 1.0 |
| MMLU | 82.0% | 80.0% | Nova Pro 1.0 |
| LMArena Text: science | 1255 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: medicine and healthcare | 1260 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: legal and government | 1281 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: business and finance | 1229 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Pro 1.0 | Mistral Large 2407 | 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 index20
| Benchmark | Nova Pro 1.0 | Mistral Large 2407 | Leader |
|---|---|---|---|
| IFBench | 38.1% | 31.6% | Nova Pro 1.0 |
| Long context reasoning (AA-LCR) | 21.0% | 2.0% | Nova Pro 1.0 |
| DTBench | Not measured | 61.2% | Only Mistral Large 2407 measured |
| Creative writing (Lech Mazur) | Not measured | 69.0% | Only Mistral Large 2407 measured |
| LMArena Text | 1259 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: instruction following | 1235 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: creative writing | 1212 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Vision | 980 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: English | 1276 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: non-English | 1233 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Chinese | 1244 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: German | 1243 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Japanese | 1200 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Korean | 1203 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: French | 1271 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Spanish | 1182 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Russian | 1240 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: multi-turn | 1246 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: longer queries | 1255 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: writing and language | 1247 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: entertainment and media | 1210 | Not measured | Only Nova Pro 1.0 measured |
| 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 2407 | 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 2407 |
|---|---|---|
| Maker | Amazon | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | December 5, 2024 | November 19, 2024 |
| Context window | 300K | 131K |
| 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 2407 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 131K tokens.
Which is cheaper, Nova Pro 1.0 or Mistral Large 2407?
Nova Pro 1.0 costs $0.80 per million input tokens and $3.20 per million output tokens; Mistral Large 2407 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 2407?
Nova Pro 1.0, with 300K tokens against 131K.
How many benchmarks is the Nova Pro 1.0 vs Mistral Large 2407 comparison based on?
11 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 2407's on 0. Where only one model has a result, the page says so instead of naming a winner.