GPT-5.1-Codex vs Kimi K2 0711
Updated October 21, 2026. 19 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Kimi K2 0711 for coding: it scores 64.7 on the Vibe Coding Index against 50.5 for GPT-5.1-Codex.
Pick GPT-5.1-Codex when the context window is larger, 400K against 131K tokens, or when what matters is LiveCodeBench (Vals AI) or LiveCodeBench (Artificial Analysis run), where it leads.
- Shared results
- 19
- GPT-5.1-Codex only
- 7
- Kimi K2 0711 only
- 17
- Like-for-like categories
- 8 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, four public coding benchmarks
Kimi K2 0711
Kimi K2 0711 scores 64.7 against 50.5.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-5.1-Codex
GPT-5.1-Codex leads, 23.7 against 12.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Kimi K2 0711 has a GPQA Diamond result, 71.5%.
Directional only
Math
AIME
No call
Only Kimi K2 0711 has a AIME result, 62.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K2 0711 has a MMLU Pro result, 79.4%.
Directional only
Web design
Design Arena: websites
GPT-5.1-Codex
GPT-5.1-Codex leads, 1162 against 1050.
Same board, both measured
Long documents
Listed context window
GPT-5.1-Codex
GPT-5.1-Codex takes 400K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2 0711
GPT-5.1-Codex $0.0063, Kimi K2 0711 $0.0017 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.1-Codex has the number, $0.892.
Directional only
At a glance
- Coding index
- GPT-5.1-Codex 50.5 from 2 benchmarks, Kimi K2 0711 64.7 from 2 benchmarks.
- Widest category
- Math, 38.7 points apart on average over 2 shared benchmarks.
- Widest single gap
- AA Math Index: GPT-5.1-Codex 95.7 against Kimi K2 0711 57.0, 38.7 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex $10.00 against Kimi K2 0711 $2.30 per million output tokens, 4.3x apart.
- Context window
- GPT-5.1-Codex takes 400K tokens, Kimi K2 0711 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.
| Category | GPT-5.1-Codex | Bars | Kimi K2 0711 | Ties |
|---|---|---|---|---|
| Coding | 4 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 5 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 18 | 1 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index41
| Benchmark | GPT-5.1-Codex | Kimi K2 0711 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 59.1% | Only Kimi K2 0711 measured |
| SWE-bench Verified | 66.0% | 71.2% | Kimi K2 0711 |
| LMArena WebDev | 1337 | Not measured | Only GPT-5.1-Codex measured |
| LiveCodeBench (Vals AI) | 85.5% | 70.5% | GPT-5.1-Codex |
| Vibe Code Bench (Vals AI) | 13.1% | Not measured | Only GPT-5.1-Codex measured |
| LiveCodeBench (Artificial Analysis run) | 84.9% | 55.6% | GPT-5.1-Codex |
| Terminal-Bench Hard (Artificial Analysis run) | 34.8% | 15.9% | GPT-5.1-Codex |
| Terminal-Bench | 57.8% | 27.8% | GPT-5.1-Codex |
| GSO-Bench | Not measured | 4.9% | Only Kimi K2 0711 measured |
| WeirdML | Not measured | 39.4% | Only Kimi K2 0711 measured |
| ALE-Bench | 1244.9 | Not measured | Only GPT-5.1-Codex measured |
| LMArena WebDev: HTML | 1346 | Not measured | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex | Kimi K2 0711 | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.7 | 12.7 | GPT-5.1-Codex |
| Epoch Capabilities Index | Not measured | 140.0 | Only Kimi K2 0711 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex | Kimi K2 0711 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1018 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: agents building full-stack apps | 1086 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: agents building mobile apps | 1191 | Not measured | Only GPT-5.1-Codex measured |
| τ²-Bench Telecom | 83.0% | 61.1% | GPT-5.1-Codex |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1-Codex | Kimi K2 0711 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 71.5% | Only Kimi K2 0711 measured |
| GPQA Diamond (Artificial Analysis run) | 86.0% | 76.6% | GPT-5.1-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 25.7% | 7.4% | GPT-5.1-Codex |
| SimpleBench | Not measured | 26.3% | Only Kimi K2 0711 measured |
| Neither model has a result on the other 17 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1-Codex | Kimi K2 0711 | Leader |
|---|---|---|---|
| AIME | Not measured | 62.7% | Only Kimi K2 0711 measured |
| MATH 500 (Vals AI) | Not measured | 94.2% | Only Kimi K2 0711 measured |
| MGSM (Vals AI) | Not measured | 91.0% | Only Kimi K2 0711 measured |
| AA Math Index | 95.7 | 57.0 | GPT-5.1-Codex |
| AIME 2025 (Artificial Analysis run) | 95.7% | 57.0% | GPT-5.1-Codex |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex | Kimi K2 0711 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 79.4% | Only Kimi K2 0711 measured |
| LegalBench (Vals AI) | Not measured | 81.5% | Only Kimi K2 0711 measured |
| CorpFin (Vals AI) | Not measured | 50.4% | Only Kimi K2 0711 measured |
| TaxEval (Vals AI) | Not measured | 70.2% | Only Kimi K2 0711 measured |
| MedQA (Vals AI) | Not measured | 84.0% | Only Kimi K2 0711 measured |
| MMLU Pro (Artificial Analysis run) | 86.0% | 82.4% | GPT-5.1-Codex |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | GPT-5.1-Codex | Kimi K2 0711 | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | 1050 | GPT-5.1-Codex |
| Design Arena: UI components | 1237 | 1030 | GPT-5.1-Codex |
| Design Arena: game dev | 1138 | 974 | GPT-5.1-Codex |
| Design Arena: data viz | 1213 | 1018 | GPT-5.1-Codex |
| Design Arena: all code categories | 1153 | 1034 | GPT-5.1-Codex |
| Neither model has a result on the other 4 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1-Codex | Kimi K2 0711 | Leader |
|---|---|---|---|
| IFBench | 70.0% | 41.5% | GPT-5.1-Codex |
| Long context reasoning (AA-LCR) | 69.3% | 53.0% | GPT-5.1-Codex |
| Fiction.LiveBench | Not measured | 61.1% | Only Kimi K2 0711 measured |
| Creative writing (Lech Mazur) | Not measured | 85.6% | Only Kimi K2 0711 measured |
| CL-bench | Not measured | 11.9% | Only Kimi K2 0711 measured |
| Neither model has a result on the other 41 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1-Codex | Kimi K2 0711 | 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 0711 costs less
Repository review
50K input + 3K output tokens
Kimi K2 0711 costs less
Agent loop
200K input + 10K output tokens
Kimi K2 0711 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 | OpenAI GPT-5.1-Codex | MoonshotAI Kimi K2 0711 |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | November 13, 2025 | July 11, 2025 |
| Context window | 400K | 131K |
| Input $/Mtok | $1.25 | $0.57 |
| Output $/Mtok | $10.00 | $2.30 |
| Coding index | 50.5 | 64.7 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $0.892 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex better than Kimi K2 0711 for coding?
Pick Kimi K2 0711 for coding: it scores 64.7 on the Vibe Coding Index against 50.5 for GPT-5.1-Codex. Pick GPT-5.1-Codex when the context window is larger, 400K against 131K tokens, or when what matters is LiveCodeBench (Vals AI) or LiveCodeBench (Artificial Analysis run), where it leads.
Which is cheaper, GPT-5.1-Codex or Kimi K2 0711?
GPT-5.1-Codex costs $1.25 per million input tokens and $10.00 per million output tokens; Kimi K2 0711 costs $0.57 and $2.30. Cost per solved task is known for GPT-5.1-Codex only.
Which has the bigger context window, GPT-5.1-Codex or Kimi K2 0711?
GPT-5.1-Codex, with 400K tokens against 131K.
How many benchmarks is the GPT-5.1-Codex vs Kimi K2 0711 comparison based on?
19 benchmarks have a result for both models as of October 21, 2026. GPT-5.1-Codex's coding index rests on 2 independent benchmarks and Kimi K2 0711's on 2. Where only one model has a result, the page says so instead of naming a winner.