Kimi K2 0905 vs Mistral Nemo
Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
- Coding
- No data
- Overall
- 15.3
- Output $/M
- $2.50
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.15
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Kimi K2 0905 has the edge where the context window is larger, 262K against 131K tokens.
- Shared results
- 0
- Kimi K2 0905 only
- 16
- Mistral Nemo only
- 3
- Like-for-like categories
- 0 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
No call
Only Kimi K2 0905 has a AA Intelligence Index result, 15.3.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K2 0905 has a Design Arena: websites result, 1089.
Directional only
Long documents
Listed context window
Kimi K2 0905
Kimi K2 0905 takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Nemo
Kimi K2 0905 $0.0019, Mistral Nemo $0.0002 per turn.
List prices
At a glance
- Coding index
- Kimi K2 0905 not benchmarked, Mistral Nemo not benchmarked.
- Widest category
- No category has a result for both models.
- Widest single gap
- No benchmark has a result for both models.
- Output price
- Kimi K2 0905 $2.50 against Mistral Nemo $0.15 per million output tokens, 16.7x apart.
- Context window
- Kimi K2 0905 takes 262K tokens, Mistral Nemo 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.
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards, none shared
| Benchmark | Kimi K2 0905 | Mistral Nemo | 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 34 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Kimi K2 0905 | Mistral Nemo | Leader |
|---|---|---|---|
| AA Intelligence Index | 15.3 | Not measured | Only Kimi K2 0905 measured |
| Epoch Capabilities Index | Not measured | 118.7 | Only Mistral Nemo measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Kimi K2 0905 | Mistral Nemo | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 73.4% | Not measured | Only Kimi K2 0905 measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Kimi K2 0905 | Mistral Nemo | 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 |
| 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 Nemo | 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 index2 boards, none shared
| Benchmark | Kimi K2 0905 | Mistral Nemo | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 81.9% | Not measured | Only Kimi K2 0905 measured |
| MMLU | Not measured | 65.3% | Only Mistral Nemo measured |
| Neither model has a result on the other 15 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Kimi K2 0905 | Mistral Nemo | Leader |
|---|---|---|---|
| Design Arena: websites | 1089 | Not measured | Only Kimi K2 0905 measured |
| Design Arena: all code categories | 1098 | Not measured | Only Kimi K2 0905 measured |
| Neither model has a result on the other 7 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Kimi K2 0905 | Mistral Nemo | 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 |
| DTBench | Not measured | 48.6% | Only Mistral Nemo measured |
| Fiction.LiveBench | 66.7% | Not measured | Only Kimi K2 0905 measured |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Kimi K2 0905 | Mistral Nemo | 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 Nemo costs less
Repository review
50K input + 3K output tokens
Mistral Nemo costs less
Agent loop
200K input + 10K output tokens
Mistral Nemo 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 Nemo |
|---|---|---|
| Maker | Moonshot AI | Mistral AI |
| Weights | Open weights | Open weights |
| Released | September 4, 2025 | July 19, 2024 |
| Context window | 262K | 131K |
| Input $/Mtok | $0.60 | $0.15 |
| Output $/Mtok | $2.50 | $0.15 |
| 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 Nemo for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Kimi K2 0905 has the edge where the context window is larger, 262K against 131K tokens.
Which is cheaper, Kimi K2 0905 or Mistral Nemo?
Kimi K2 0905 costs $0.60 per million input tokens and $2.50 per million output tokens; Mistral Nemo costs $0.15 and $0.15. Cost per solved task is known for neither of them.
Which has the bigger context window, Kimi K2 0905 or Mistral Nemo?
Kimi K2 0905, with 262K tokens against 131K.
How many benchmarks is the Kimi K2 0905 vs Mistral Nemo comparison based on?
0 benchmarks have a result for both models as of October 21, 2026. Kimi K2 0905's coding index rests on 0 independent benchmarks and Mistral Nemo's on 0. Where only one model has a result, the page says so instead of naming a winner.