Kimi K2 0905 vs o4 Mini High
Kimi K2 0905 costs 1.8x less per output token than o4 Mini High ($2.50 vs $4.40 per million). Updated October 21, 2026; 1 benchmarks have a result for both.
Kimi K2 0905 or o4 Mini High: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Kimi K2 0905 for output tokens 1.8x cheaper ($2.50 vs $4.40 per million) and a larger context window (262K against 200K tokens).
- Shared results
- 1
- Kimi K2 0905 only
- 16
- o4 Mini High only
- 1
- 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
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 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2 0905
Kimi K2 0905 $0.0019, o4 Mini High $0.0033 per turn.
List prices
At a glance
- Coding index
- Kimi K2 0905 not benchmarked, o4 Mini High not benchmarked.
- Widest category
- Coding, 18.6 points apart on average over 1 shared benchmark.
- Widest single gap
- ALE-Bench: Kimi K2 0905 267.1 against o4 Mini High 826.2, 18.6 points apart on a 0 to 100 scale.
- Output price
- Kimi K2 0905 $2.50 against o4 Mini High $4.40 per million output tokens, 1.8x apart.
- Context window
- Kimi K2 0905 takes 262K tokens, o4 Mini High 200K.
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 | o4 Mini High | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Kimi K2 0905 | o4 Mini High | 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 | 826.2 | o4 Mini High |
| 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 | o4 Mini High | 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 index2 boards, none shared
| Benchmark | Kimi K2 0905 | o4 Mini High | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 73.4% | Not measured | Only Kimi K2 0905 measured |
| GDPval | Not measured | 25.3% | Only o4 Mini High measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Kimi K2 0905 | o4 Mini High | 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 | o4 Mini High | 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 | o4 Mini High | 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 designDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Kimi K2 0905 | o4 Mini High | 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 index3 boards, none shared
| Benchmark | Kimi K2 0905 | o4 Mini High | 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 | o4 Mini High | 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
Kimi K2 0905 costs less
Repository review
50K input + 3K output tokens
Kimi K2 0905 costs less
Agent loop
200K input + 10K output tokens
Kimi K2 0905 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 | OpenAI o4 Mini High |
|---|---|---|
| Maker | Moonshot AI | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | September 4, 2025 | April 16, 2025 |
| Context window | 262K | 200K |
| Input $/Mtok | $0.60 | $1.10 |
| Output $/Mtok | $2.50 | $4.40 |
| 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 o4 Mini High for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Kimi K2 0905 for output tokens 1.8x cheaper ($2.50 vs $4.40 per million) and a larger context window (262K against 200K tokens).
Which is cheaper, Kimi K2 0905 or o4 Mini High?
Kimi K2 0905 costs $0.60 per million input tokens and $2.50 per million output tokens; o4 Mini High costs $1.10 and $4.40. Cost per solved task is known for neither of them.
Which has the bigger context window, Kimi K2 0905 or o4 Mini High?
Kimi K2 0905, with 262K tokens against 200K.
How many benchmarks is the Kimi K2 0905 vs o4 Mini High comparison based on?
1 benchmarks have a result for both models as of October 21, 2026. Kimi K2 0905's coding index rests on 0 independent benchmarks and o4 Mini High's on 0. Where only one model has a result, the page says so instead of naming a winner.