Nova Premier 1.0 vs Mistral Small 3.2 24B
Mistral Small 3.2 24B costs 41.7x less per output token than Nova Premier 1.0 ($0.30 vs $12.50 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
Nova Premier 1.0 or Mistral Small 3.2 24B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Nova Premier 1.0 for a larger context window (1M against 256K tokens) and work measured by Design Arena: websites, where it leads.
- Shared results
- 1
- Nova Premier 1.0 only
- 13
- Mistral Small 3.2 24B only
- 4
- Like-for-like categories
- 1 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
Only Nova Premier 1.0 has a AA Intelligence Index result, 9.2.
Directional only
Web design
Design Arena: websites
Mistral Small 3.2 24B
Mistral Small 3.2 24B leads, 896 against 835.
Same board, both measured
Long documents
Listed context window
Nova Premier 1.0
Nova Premier 1.0 takes 1M tokens against 256K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3.2 24B
Nova Premier 1.0 $0.0088, Mistral Small 3.2 24B $0.0003 per turn.
List prices
At a glance
- Coding index
- Nova Premier 1.0 not benchmarked, Mistral Small 3.2 24B not benchmarked.
- Widest category
- Web design, 7.6 points apart on average over 1 shared benchmark.
- Widest single gap
- Design Arena: websites: Nova Premier 1.0 835 against Mistral Small 3.2 24B 896, 7.6 points apart on a 0 to 100 scale.
- Output price
- Nova Premier 1.0 $12.50 against Mistral Small 3.2 24B $0.30 per million output tokens, 41.7x apart.
- Context window
- Nova Premier 1.0 takes 1M tokens, Mistral Small 3.2 24B 256K.
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 Premier 1.0 | Bars | Mistral Small 3.2 24B | Ties |
|---|---|---|---|---|
| Web design | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards, none shared
| Benchmark | Nova Premier 1.0 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 31.7% | Not measured | Only Nova Premier 1.0 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.8% | Not measured | Only Nova Premier 1.0 measured |
| ALE-Bench | 147.4 | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Premier 1.0 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Premier 1.0 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 38.3% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Nova Premier 1.0 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 56.9% | Not measured | Only Nova Premier 1.0 measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | Not measured | Only Nova Premier 1.0 measured |
| Kagi LLM Benchmark | 44.8% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Nova Premier 1.0 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| AA Math Index | 17.3 | Not measured | Only Nova Premier 1.0 measured |
| AIME 2025 (Artificial Analysis run) | 17.3% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Nova Premier 1.0 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 73.3% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 17 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Premier 1.0 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| Design Arena: websites | 835 | 896 | Mistral Small 3.2 24B |
| Design Arena: UI components | Not measured | 907 | Only Mistral Small 3.2 24B measured |
| Design Arena: game dev | Not measured | 889 | Only Mistral Small 3.2 24B measured |
| Design Arena: data viz | Not measured | 929 | Only Mistral Small 3.2 24B measured |
| Design Arena: all code categories | Not measured | 907 | Only Mistral Small 3.2 24B measured |
| Neither model has a result on the other 4 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Nova Premier 1.0 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| IFBench | 36.2% | Not measured | Only Nova Premier 1.0 measured |
| Long context reasoning (AA-LCR) | 34.3% | Not measured | Only Nova Premier 1.0 measured |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Premier 1.0 | Mistral Small 3.2 24B | 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 3.2 24B costs less
Repository review
50K input + 3K output tokens
Mistral Small 3.2 24B costs less
Agent loop
200K input + 10K output tokens
Mistral Small 3.2 24B 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 Premier 1.0 | Mistral Small 3.2 24B |
|---|---|---|
| Maker | Amazon | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | October 31, 2025 | June 20, 2025 |
| Context window | 1M | 256K |
| Input $/Mtok | $2.50 | $0.10 |
| Output $/Mtok | $12.50 | $0.30 |
| 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 Premier 1.0 better than Mistral Small 3.2 24B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Nova Premier 1.0 for a larger context window (1M against 256K tokens) and work measured by Design Arena: websites, where it leads.
Which is cheaper, Nova Premier 1.0 or Mistral Small 3.2 24B?
Nova Premier 1.0 costs $2.50 per million input tokens and $12.50 per million output tokens; Mistral Small 3.2 24B costs $0.10 and $0.30. Cost per solved task is known for neither of them.
Which has the bigger context window, Nova Premier 1.0 or Mistral Small 3.2 24B?
Nova Premier 1.0, with 1M tokens against 256K.
How many benchmarks is the Nova Premier 1.0 vs Mistral Small 3.2 24B comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. Nova Premier 1.0's coding index rests on 0 independent benchmarks and Mistral Small 3.2 24B's on 0. Where only one model has a result, the page says so instead of naming a winner.