GPT-4o (2024-08-06) vs Kimi K2.5
Kimi K2.5 leads GPT-4o (2024-08-06) on the Artificial Analysis Intelligence Index, 23.5 to 7.7, and Kimi K2.5 costs 3.5x less per output token ($2.85 vs $10.00 per million). Updated October 22, 2026; 46 benchmarks have a result for both.
GPT-4o (2024-08-06) or Kimi K2.5: which to pick
Only Kimi K2.5 has a coding score, 38.6 on the Vibe Coding Index; GPT-4o (2024-08-06) has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 46
- GPT-4o (2024-08-06) only
- 12
- Kimi K2.5 only
- 53
- Like-for-like categories
- 7 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
Only Kimi K2.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Kimi K2.5
Kimi K2.5 leads, 23.5 against 7.7.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Kimi K2.5 has a GPQA Diamond result, 84.1%.
Directional only
Math
AIME
Kimi K2.5
Kimi K2.5 leads, 95.6% against 14.0%.
Same board, both measured
Knowledge
MMLU Pro
Kimi K2.5
Kimi K2.5 leads, 85.9% against 74.1%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Kimi K2.5 has a Design Arena: websites result, 1248.
Directional only
Long documents
Listed context window
Kimi K2.5
Kimi K2.5 takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2.5
GPT-4o (2024-08-06) $0.0075, Kimi K2.5 $0.0020 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Kimi K2.5 has the number, $0.24.
Directional only
At a glance
- Coding index
- GPT-4o (2024-08-06) not benchmarked, Kimi K2.5 38.6 from 3 benchmarks.
- Widest category
- Agentic work, 67.0 points apart on average over 1 shared benchmark.
- Widest single gap
- AIME: GPT-4o (2024-08-06) 14.0% against Kimi K2.5 95.6%, 81.7 points apart on a 0 to 100 scale.
- Output price
- GPT-4o (2024-08-06) $10.00 against Kimi K2.5 $2.85 per million output tokens, 3.5x apart.
- Context window
- GPT-4o (2024-08-06) takes 128K tokens, Kimi K2.5 262K.
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-4o (2024-08-06) | Bars | Kimi K2.5 | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 7 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 10 | ||
| General | 0 | 21 | ||
| All shared boards | 0 | 46 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | GPT-4o (2024-08-06) | Kimi K2.5 | Leader |
|---|---|---|---|
| Aider polyglot | 23.1% | Not measured | Only GPT-4o (2024-08-06) measured |
| SWE-bench Verified | Not measured | 70.8% | Only Kimi K2.5 measured |
| SWE-bench Lite | 21.7% | Not measured | Only GPT-4o (2024-08-06) measured |
| SWE-bench Multilingual | Not measured | 67.3% | Only Kimi K2.5 measured |
| LMArena WebDev | Not measured | 1437 | Only Kimi K2.5 measured |
| AA Coding Index | Not measured | 46.8 | Only Kimi K2.5 measured |
| LiveCodeBench (Vals AI) | Not measured | 83.9% | Only Kimi K2.5 measured |
| SWE-bench Verified (Vals AI) | Not measured | 70.0% | Only Kimi K2.5 measured |
| Vibe Code Bench (Vals AI) | Not measured | 17.5% | Only Kimi K2.5 measured |
| Code migration (Vals AI) | Not measured | 7.0% | Only Kimi K2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 42.0% | Only Kimi K2.5 measured |
| LiveCodeBench (Artificial Analysis run) | 31.7% | Not measured | Only GPT-4o (2024-08-06) measured |
| Terminal-Bench Hard (Artificial Analysis run) | 8.3% | 34.8% | Kimi K2.5 |
| Terminal-Bench | Not measured | 43.2% | Only Kimi K2.5 measured |
| WeirdML | Not measured | 45.6% | Only Kimi K2.5 measured |
| ALE-Bench | Not measured | 821.6 | Only Kimi K2.5 measured |
| LMArena Text: coding | 1283 | 1483 | Kimi K2.5 |
| LMArena Text: software and IT | 1278 | 1471 | Kimi K2.5 |
| LMArena WebDev: React | Not measured | 1429 | Only Kimi K2.5 measured |
| LMArena WebDev: HTML | Not measured | 1426 | Only Kimi K2.5 measured |
| LMArena WebDev: from an image | Not measured | 1439 | Only Kimi K2.5 measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o (2024-08-06) | Kimi K2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.7 | 23.5 | Kimi K2.5 |
| Epoch Capabilities Index | Not measured | 148.1 | Only Kimi K2.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o (2024-08-06) | Kimi K2.5 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1136 | Only Kimi K2.5 measured |
| Design Arena: agents building full-stack apps | Not measured | 1114 | Only Kimi K2.5 measured |
| Design Arena: agents building mobile apps | Not measured | 1147 | Only Kimi K2.5 measured |
| Design Arena: agents building Android apps | Not measured | 1118 | Only Kimi K2.5 measured |
| Design Arena: agents building Godot games | Not measured | 1219 | Only Kimi K2.5 measured |
| Finance Agent (Vals AI) | Not measured | 35.8% | Only Kimi K2.5 measured |
| Legal Research Bench (Vals AI) | Not measured | 15.9% | Only Kimi K2.5 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 28.5% | Only Kimi K2.5 measured |
| τ²-Bench Telecom | 28.9% | 95.9% | Kimi K2.5 |
| OSWorld | Not measured | 63.3% | Only Kimi K2.5 measured |
| Vending-Bench 2 | Not measured | $1,198 | Only Kimi K2.5 measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | GPT-4o (2024-08-06) | Kimi K2.5 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 84.1% | Only Kimi K2.5 measured |
| MMMU Pro (Vals AI) | 64.0% | 84.3% | Kimi K2.5 |
| GPQA Diamond (Artificial Analysis run) | 52.1% | 87.9% | Kimi K2.5 |
| Humanity's Last Exam (Artificial Analysis run) | 2.3% | 30.7% | Kimi K2.5 |
| GPQA Diamond (Epoch AI run) | 49.2% | Not measured | Only GPT-4o (2024-08-06) measured |
| ARC-AGI | Not measured | 65.3% | Only Kimi K2.5 measured |
| ARC-AGI-2 | Not measured | 11.8% | Only Kimi K2.5 measured |
| SimpleBench | 17.8% | 46.8% | Kimi K2.5 |
| Chess puzzles | 6.0% | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text: hard prompts | 1264 | 1453 | Kimi K2.5 |
| LMArena Text: expert | 1241 | 1466 | Kimi K2.5 |
| LMArena Text: hard prompts in English | 1277 | 1460 | Kimi K2.5 |
| LMArena Vision: diagrams | Not measured | 1282 | Only Kimi K2.5 measured |
| LMArena Vision: homework | Not measured | 1297 | Only Kimi K2.5 measured |
| Kagi LLM Benchmark | Not measured | 78.5% | Only Kimi K2.5 measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | GPT-4o (2024-08-06) | Kimi K2.5 | Leader |
|---|---|---|---|
| AIME | 14.0% | 95.6% | Kimi K2.5 |
| MATH 500 (Vals AI) | 75.2% | Not measured | Only GPT-4o (2024-08-06) measured |
| MGSM (Vals AI) | 90.7% | Not measured | Only GPT-4o (2024-08-06) measured |
| OTIS Mock AIME | 6.4% | Not measured | Only GPT-4o (2024-08-06) measured |
| FrontierMath, tiers 1 to 3 | 0.4% | Not measured | Only GPT-4o (2024-08-06) measured |
| MATH level 5 | 53.3% | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text: math | 1285 | 1470 | Kimi K2.5 |
| LMArena Text: mathematical work | 1283 | 1473 | Kimi K2.5 |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index010
| Benchmark | GPT-4o (2024-08-06) | Kimi K2.5 | Leader |
|---|---|---|---|
| MMLU Pro | 74.1% | 85.9% | Kimi K2.5 |
| LegalBench (Vals AI) | 80.1% | Not measured | Only GPT-4o (2024-08-06) measured |
| CaseLaw (Vals AI) | Not measured | 58.7% | Only Kimi K2.5 measured |
| CorpFin (Vals AI) | 39.4% | 68.3% | Kimi K2.5 |
| TaxEval (Vals AI) | 71.1% | 74.2% | Kimi K2.5 |
| MortgageTax (Vals AI) | 61.0% | 66.5% | Kimi K2.5 |
| MedQA (Vals AI) | 88.2% | 94.4% | Kimi K2.5 |
| MedCode (Vals AI) | Not measured | 39.3% | Only Kimi K2.5 measured |
| SimpleQA Verified | 26.0% | 34.3% | Kimi K2.5 |
| MMLU | 84.3% | Not measured | Only GPT-4o (2024-08-06) measured |
| LMArena Text: science | 1274 | 1459 | Kimi K2.5 |
| LMArena Text: medicine and healthcare | 1252 | 1448 | Kimi K2.5 |
| LMArena Text: legal and government | 1275 | 1441 | Kimi K2.5 |
| LMArena Text: business and finance | 1232 | 1427 | Kimi K2.5 |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-4o (2024-08-06) | Kimi K2.5 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1248 | Only Kimi K2.5 measured |
| Design Arena: UI components | Not measured | 1234 | Only Kimi K2.5 measured |
| Design Arena: game dev | Not measured | 1206 | Only Kimi K2.5 measured |
| Design Arena: data viz | Not measured | 1219 | Only Kimi K2.5 measured |
| Design Arena: 3D | Not measured | 1204 | Only Kimi K2.5 measured |
| Design Arena: all code categories | Not measured | 1236 | Only Kimi K2.5 measured |
| Design Arena: SVG | Not measured | 1149 | Only Kimi K2.5 measured |
| Design Arena: ASCII art | Not measured | 1166 | Only Kimi K2.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index021
| Benchmark | GPT-4o (2024-08-06) | Kimi K2.5 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 49.9% | Only Kimi K2.5 measured |
| MedScribe (Vals AI) | Not measured | 76.4% | Only Kimi K2.5 measured |
| IFBench | 36.0% | 70.2% | Kimi K2.5 |
| Long context reasoning (AA-LCR) | 41.0% | 78.0% | Kimi K2.5 |
| Fiction.LiveBench | Not measured | 86.1% | Only Kimi K2.5 measured |
| CL-bench | Not measured | 19.3% | Only Kimi K2.5 measured |
| CL-bench Life | Not measured | 13.2% | Only Kimi K2.5 measured |
| LMArena Text | 1283 | 1445 | Kimi K2.5 |
| LMArena Text: instruction following | 1267 | 1431 | Kimi K2.5 |
| LMArena Text: creative writing | 1274 | 1422 | Kimi K2.5 |
| LMArena Vision | 1065 | 1269 | Kimi K2.5 |
| LMArena Text: English | 1297 | 1453 | Kimi K2.5 |
| LMArena Text: non-English | 1262 | 1433 | Kimi K2.5 |
| LMArena Text: Chinese | 1254 | 1494 | Kimi K2.5 |
| LMArena Text: German | 1257 | 1441 | Kimi K2.5 |
| LMArena Text: Japanese | 1234 | 1423 | Kimi K2.5 |
| LMArena Text: Korean | 1218 | 1412 | Kimi K2.5 |
| LMArena Text: French | 1263 | 1454 | Kimi K2.5 |
| LMArena Text: Spanish | 1269 | 1450 | Kimi K2.5 |
| LMArena Text: Russian | 1272 | 1435 | Kimi K2.5 |
| LMArena Text: Polish | Not measured | 1445 | Only Kimi K2.5 measured |
| LMArena Text: multi-turn | 1279 | 1444 | Kimi K2.5 |
| LMArena Text: longer queries | 1283 | 1445 | Kimi K2.5 |
| LMArena Text: writing and language | 1290 | 1425 | Kimi K2.5 |
| LMArena Text: entertainment and media | 1267 | 1417 | Kimi K2.5 |
| LMArena Vision: English | 1072 | 1274 | Kimi K2.5 |
| LMArena Vision: Chinese | 1009 | 1328 | Kimi K2.5 |
| LMArena Vision: reading text | Not measured | 1276 | Only Kimi K2.5 measured |
| LMArena Vision: humor | Not measured | 1284 | Only Kimi K2.5 measured |
| LMArena Vision: captioning | Not measured | 1257 | Only Kimi K2.5 measured |
| LMArena Vision: recognizing things | Not measured | 1285 | Only Kimi K2.5 measured |
| LMArena Vision: creative writing | Not measured | 1269 | Only Kimi K2.5 measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o (2024-08-06) | Kimi K2.5 | 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 K2.5 costs less
Repository review
50K input + 3K output tokens
Kimi K2.5 costs less
Agent loop
200K input + 10K output tokens
Kimi K2.5 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-4o (2024-08-06) | MoonshotAI Kimi K2.5 |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | August 6, 2024 | January 27, 2026 |
| Context window | 128K | 262K |
| Input $/Mtok | $2.50 | $0.532 |
| Output $/Mtok | $10.00 | $2.85 |
| Coding index | Not benchmarked | 38.6 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | $0.24 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o (2024-08-06) better than Kimi K2.5 for coding?
Only Kimi K2.5 has a coding score, 38.6 on the Vibe Coding Index; GPT-4o (2024-08-06) has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-4o (2024-08-06) or Kimi K2.5?
GPT-4o (2024-08-06) costs $2.50 per million input tokens and $10.00 per million output tokens; Kimi K2.5 costs $0.532 and $2.85. Cost per solved task is known for Kimi K2.5 only.
Which has the bigger context window, GPT-4o (2024-08-06) or Kimi K2.5?
Kimi K2.5, with 262K tokens against 128K.
How many benchmarks is the GPT-4o (2024-08-06) vs Kimi K2.5 comparison based on?
46 benchmarks have a result for both models as of October 22, 2026. GPT-4o (2024-08-06)'s coding index rests on 0 independent benchmarks and Kimi K2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.