Kimi K2 0905 vs Mistral Small 3.2 24B
Mistral Small 3.2 24B costs 8.3x less per output token than Kimi K2 0905 ($0.30 vs $2.50 per million). Updated October 22, 2026; 2 benchmarks have a result for both.
Kimi K2 0905 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 Kimi K2 0905 for a larger context window (262K against 256K tokens).
- Shared results
- 2
- Kimi K2 0905 only
- 15
- Mistral Small 3.2 24B only
- 3
- 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 Kimi K2 0905 has a AA Intelligence Index result, 15.3.
Directional only
Web design
Design Arena: websites
Kimi K2 0905
Kimi K2 0905 leads, 1088 against 896.
Same board, both measured
Long documents
Listed context window
Kimi K2 0905
Kimi K2 0905 takes 262K tokens against 256K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3.2 24B
Kimi K2 0905 $0.0019, Mistral Small 3.2 24B $0.0003 per turn.
List prices
At a glance
- Coding index
- Kimi K2 0905 not benchmarked, Mistral Small 3.2 24B not benchmarked.
- Widest category
- Web design, 23.9 points apart on average over 2 shared benchmarks.
- Widest single gap
- Design Arena: websites: Kimi K2 0905 1088 against Mistral Small 3.2 24B 896, 24.0 points apart on a 0 to 100 scale.
- Output price
- Kimi K2 0905 $2.50 against Mistral Small 3.2 24B $0.30 per million output tokens, 8.3x apart.
- Context window
- Kimi K2 0905 takes 262K 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 | Kimi K2 0905 | Bars | Mistral Small 3.2 24B | Ties |
|---|---|---|---|---|
| Web design | 2 | 0 | ||
| All shared boards | 2 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards, none shared
| Benchmark | Kimi K2 0905 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 61.0% | Not measured | Only Kimi K2 0905 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 23.5% | Not measured | Only Kimi K2 0905 measured |
| WeirdML | 36.7% | Not measured | Only Kimi K2 0905 measured |
| ALE-Bench | 267.1 | Not measured | Only Kimi K2 0905 measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Kimi K2 0905 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| AA Intelligence Index | 15.3 | Not measured | Only Kimi K2 0905 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 | Kimi K2 0905 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 73.4% | Not measured | Only Kimi K2 0905 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 | Kimi K2 0905 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 76.7% | Not measured | Only Kimi K2 0905 measured |
| Humanity's Last Exam (Artificial Analysis run) | 6.4% | Not measured | Only Kimi K2 0905 measured |
| Kagi LLM Benchmark | 52.2% | Not measured | Only Kimi K2 0905 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 | Kimi K2 0905 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| AA Math Index | 57.3 | Not measured | Only Kimi K2 0905 measured |
| AIME 2025 (Artificial Analysis run) | 57.3% | Not measured | Only Kimi K2 0905 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 | Kimi K2 0905 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 81.9% | Not measured | Only Kimi K2 0905 measured |
| Neither model has a result on the other 17 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K2 0905 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| Design Arena: websites | 1088 | 896 | Kimi K2 0905 |
| 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 | 1098 | 907 | Kimi K2 0905 |
| Neither model has a result on the other 4 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Kimi K2 0905 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| IFBench | 41.7% | Not measured | Only Kimi K2 0905 measured |
| Long context reasoning (AA-LCR) | 53.0% | Not measured | Only Kimi K2 0905 measured |
| Fiction.LiveBench | 66.7% | Not measured | Only Kimi K2 0905 measured |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Kimi K2 0905 | 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 | MoonshotAI Kimi K2 0905 | Mistral Small 3.2 24B |
|---|---|---|
| Maker | Moonshot AI | Mistral AI |
| Weights | Open weights | Open weights |
| Released | September 4, 2025 | June 20, 2025 |
| Context window | 262K | 256K |
| Input $/Mtok | $0.60 | $0.10 |
| Output $/Mtok | $2.50 | $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 Kimi K2 0905 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 Kimi K2 0905 for a larger context window (262K against 256K tokens).
Which is cheaper, Kimi K2 0905 or Mistral Small 3.2 24B?
Kimi K2 0905 costs $0.60 per million input tokens and $2.50 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, Kimi K2 0905 or Mistral Small 3.2 24B?
Kimi K2 0905, with 262K tokens against 256K.
How many benchmarks is the Kimi K2 0905 vs Mistral Small 3.2 24B comparison based on?
2 benchmarks have a result for both models as of October 22, 2026. Kimi K2 0905'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.