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Nova Premier 1.0 vs Mistral Large

Updated October 21, 2026. 5 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Nova Premier 1.0Amazon
Coding
No data
Overall
9.2
Output $/M
$12.50
5
Mistral LargeMistral AI
Coding
No data
Overall
5.8
Output $/M
$6.00
0
vs boards won of 5 shared

Decision reading

Neither model has a coding score yet, so the two cannot be ranked on coding.

Nova Premier 1.0 has the edge where the context window is larger, 1M against 128K tokens.

Shared results
5
Nova Premier 1.0 only
8
Mistral Large only
39
Like-for-like categories
4 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.

At a glance

Coding index
Nova Premier 1.0 not benchmarked, Mistral Large not benchmarked.
Widest category
Knowledge, 21.8 points apart on average over 1 shared benchmark.
Widest single gap
GPQA Diamond (Artificial Analysis run): Nova Premier 1.0 56.9% against Mistral Large 35.1%, 21.8 points apart on a 0 to 100 scale.
Output price
Nova Premier 1.0 $12.50 against Mistral Large $6.00 per million output tokens, 2.1x apart.
Context window
Nova Premier 1.0 takes 1M 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.

Boards won, where both have a result
CategoryNova Premier 1.0BarsMistral LargeTies
Coding10
Intelligence10
Reasoning20
Knowledge10
All shared boards50
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for Nova Premier 1.0 and Mistral Large
BenchmarkNova Premier 1.0Mistral LargeLeader
LiveCodeBench (Vals AI)Not measured37.1%Only Mistral Large measured
LiveCodeBench (Artificial Analysis run)31.7%17.8%Nova Premier 1.0
Terminal-Bench Hard (Artificial Analysis run)6.8%Not measuredOnly Nova Premier 1.0 measured
ALE-Bench147.4Not measuredOnly Nova Premier 1.0 measured
LMArena Text: codingNot measured1275Only Mistral Large measured
LMArena Text: software and ITNot measured1274Only Mistral Large measured
Neither model has a result on the other 32 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Nova Premier 1.0 and Mistral Large
BenchmarkNova Premier 1.0Mistral LargeLeader
AA Intelligence Index9.25.8Nova Premier 1.0
Epoch Capabilities IndexNot measured122.1Only Mistral Large measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Agentic work benchmarks for Nova Premier 1.0 and Mistral Large
BenchmarkNova Premier 1.0Mistral LargeLeader
τ²-Bench Telecom38.3%Not measuredOnly Nova Premier 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 index20
Reasoning benchmarks for Nova Premier 1.0 and Mistral Large
BenchmarkNova Premier 1.0Mistral LargeLeader
GPQA DiamondNot measured47.7%Only Mistral Large measured
GPQA Diamond (Artificial Analysis run)56.9%35.1%Nova Premier 1.0
Humanity's Last Exam (Artificial Analysis run)4.2%3.5%Nova Premier 1.0
LMArena Text: hard promptsNot measured1257Only Mistral Large measured
LMArena Text: expertNot measured1208Only Mistral Large measured
LMArena Text: hard prompts in EnglishNot measured1268Only Mistral Large measured
Neither model has a result on the other 15 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Math benchmarks for Nova Premier 1.0 and Mistral Large
BenchmarkNova Premier 1.0Mistral LargeLeader
AIMENot measured9.2%Only Mistral Large measured
MATH 500 (Vals AI)Not measured74.4%Only Mistral Large measured
MGSM (Vals AI)Not measured87.2%Only Mistral Large measured
AA Math Index17.3Not measuredOnly Nova Premier 1.0 measured
AIME 2025 (Artificial Analysis run)17.3%Not measuredOnly Nova Premier 1.0 measured
LMArena Text: mathNot measured1261Only Mistral Large measured
LMArena Text: mathematical workNot measured1257Only Mistral Large measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for Nova Premier 1.0 and Mistral Large
BenchmarkNova Premier 1.0Mistral LargeLeader
MMLU ProNot measured69.7%Only Mistral Large measured
TaxEval (Vals AI)Not measured63.8%Only Mistral Large measured
MedQA (Vals AI)Not measured76.2%Only Mistral Large measured
MMLU Pro (Artificial Analysis run)73.3%51.5%Nova Premier 1.0
MMLUNot measured68.8%Only Mistral Large measured
LMArena Text: scienceNot measured1260Only Mistral Large measured
LMArena Text: medicine and healthcareNot measured1255Only Mistral Large measured
LMArena Text: legal and governmentNot measured1275Only Mistral Large measured
LMArena Text: business and financeNot measured1238Only Mistral Large measured
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
Web design benchmarks for Nova Premier 1.0 and Mistral Large
BenchmarkNova Premier 1.0Mistral LargeLeader
Design Arena: websites835Not measuredOnly Nova Premier 1.0 measured
Neither model has a result on the other 8 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
General benchmarks for Nova Premier 1.0 and Mistral Large
BenchmarkNova Premier 1.0Mistral LargeLeader
IFBench36.2%Not measuredOnly Nova Premier 1.0 measured
Long context reasoning (AA-LCR)34.3%Not measuredOnly Nova Premier 1.0 measured
DTBenchNot measured60.8%Only Mistral Large measured
LMArena TextNot measured1265Only Mistral Large measured
LMArena Text: instruction followingNot measured1249Only Mistral Large measured
LMArena Text: creative writingNot measured1242Only Mistral Large measured
LMArena Text: EnglishNot measured1284Only Mistral Large measured
LMArena Text: non-EnglishNot measured1235Only Mistral Large measured
LMArena Text: ChineseNot measured1239Only Mistral Large measured
LMArena Text: GermanNot measured1242Only Mistral Large measured
LMArena Text: JapaneseNot measured1170Only Mistral Large measured
LMArena Text: KoreanNot measured1202Only Mistral Large measured
LMArena Text: FrenchNot measured1325Only Mistral Large measured
LMArena Text: SpanishNot measured1268Only Mistral Large measured
LMArena Text: RussianNot measured1252Only Mistral Large measured
LMArena Text: PolishNot measured1157Only Mistral Large measured
LMArena Text: multi-turnNot measured1260Only Mistral Large measured
LMArena Text: longer queriesNot measured1261Only Mistral Large measured
LMArena Text: writing and languageNot measured1261Only Mistral Large measured
LMArena Text: entertainment and mediaNot measured1230Only Mistral Large 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
Image generation benchmarks for Nova Premier 1.0 and Mistral Large
BenchmarkNova Premier 1.0Mistral LargeLeader
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 Premier 1.0$0.0088Fits in one request
Mistral Large$0.0050Fits in one request

Mistral Large costs less

Repository review

50K input + 3K output tokens

Nova Premier 1.0$0.163Fits in one request
Mistral Large$0.118Fits in one request

Mistral Large costs less

Agent loop

200K input + 10K output tokens

Nova Premier 1.0$0.625Fits in one request
Mistral Large$0.460Exceeds the context window

Mistral Large 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.

Specifications of Nova Premier 1.0 and Mistral Large
SpecificationAmazon Nova Premier 1.0Mistral Large
MakerAmazonMistral AI
WeightsNo public weights listedNo public weights listed
ReleasedOctober 31, 2025February 26, 2024
Context window1M128K
Input $/Mtok$2.50$2.00
Output $/Mtok$12.50$6.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Nova Premier 1.0 better than Mistral Large for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Nova Premier 1.0 has the edge where the context window is larger, 1M against 128K tokens.

Which is cheaper, Nova Premier 1.0 or Mistral Large?

Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 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 Premier 1.0 or Mistral Large?

Nova Premier 1.0, with 1M tokens against 128K.

How many benchmarks is the Nova Premier 1.0 vs Mistral Large comparison based on?

5 benchmarks have a result for both models as of October 21, 2026. Nova Premier 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.

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