GPT-4 Turbo vs Kimi K2.7 Code
Updated October 21, 2026. 4 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; GPT-4 Turbo has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 4
- GPT-4 Turbo only
- 38
- Kimi K2.7 Code only
- 47
- Like-for-like categories
- 3 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
Only Kimi K2.7 Code has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Kimi K2.7 Code
Kimi K2.7 Code leads, 25.8 against 7.0.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Kimi K2.7 Code has a AA Agentic Index result, 21.0.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K2.7 Code has a Design Arena: websites result, 1264.
Directional only
Long documents
Listed context window
Kimi K2.7 Code
Kimi K2.7 Code takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2.7 Code
GPT-4 Turbo $0.025, Kimi K2.7 Code $0.0029 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Kimi K2.7 Code has the number, $0.35.
Directional only
At a glance
- Coding index
- GPT-4 Turbo not benchmarked, Kimi K2.7 Code 53.4 from 4 benchmarks.
- Widest category
- Coding, 39.3 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Coding Index: GPT-4 Turbo 21.5 against Kimi K2.7 Code 60.8, 39.3 points apart on a 0 to 100 scale.
- Output price
- GPT-4 Turbo $30.00 against Kimi K2.7 Code $4.00 per million output tokens, 7.5x apart.
- Context window
- GPT-4 Turbo takes 128K tokens, Kimi K2.7 Code 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-4 Turbo | Bars | Kimi K2.7 Code | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 0 | 1 | ||
| All shared boards | 0 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | GPT-4 Turbo | Kimi K2.7 Code | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1474 | Only Kimi K2.7 Code measured |
| AA Coding Index | 21.5 | 60.8 | Kimi K2.7 Code |
| LiveCodeBench (Vals AI) | Not measured | 82.0% | Only Kimi K2.7 Code measured |
| SWE-bench Verified (Vals AI) | Not measured | 78.2% | Only Kimi K2.7 Code measured |
| Vibe Code Bench (Vals AI) | Not measured | 47.2% | Only Kimi K2.7 Code measured |
| Code migration (Vals AI) | Not measured | 25.4% | Only Kimi K2.7 Code measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Kimi K2.7 Code measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.0% | Only Kimi K2.7 Code measured |
| SkillsBench (Vals AI) | Not measured | 50.0% | Only Kimi K2.7 Code measured |
| LiveCodeBench (Artificial Analysis run) | 29.1% | Not measured | Only GPT-4 Turbo measured |
| SciCode | Not measured | 47.8% | Only Kimi K2.7 Code measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 44.7% | Only Kimi K2.7 Code measured |
| FrontierCode | Not measured | 30.1% | Only Kimi K2.7 Code measured |
| WeirdML | Not measured | 54.1% | Only Kimi K2.7 Code measured |
| ALE-Bench | Not measured | 886.2 | Only Kimi K2.7 Code measured |
| LMArena Text: coding | 1268 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: software and IT | 1267 | Not measured | Only GPT-4 Turbo measured |
| LMArena WebDev: React | Not measured | 1475 | Only Kimi K2.7 Code measured |
| LMArena WebDev: HTML | Not measured | 1451 | Only Kimi K2.7 Code measured |
| LMArena WebDev: from an image | Not measured | 1513 | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4 Turbo | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.0 | 25.8 | Kimi K2.7 Code |
| Epoch Capabilities Index | 127.3 | 150.1 | Kimi K2.7 Code |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | GPT-4 Turbo | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 21.0 | Only Kimi K2.7 Code measured |
| Design Arena: agents building web apps | Not measured | 1176 | Only Kimi K2.7 Code measured |
| Design Arena: agents building full-stack apps | Not measured | 1175 | Only Kimi K2.7 Code measured |
| Design Arena: agents building mobile apps | Not measured | 1143 | Only Kimi K2.7 Code measured |
| Design Arena: agents building Android apps | Not measured | 1137 | Only Kimi K2.7 Code measured |
| Design Arena: agents building Godot games | Not measured | 1147 | Only Kimi K2.7 Code measured |
| Design Arena: agents building games | Not measured | 1131 | Only Kimi K2.7 Code measured |
| Design Arena: HTML slides | Not measured | 1201 | Only Kimi K2.7 Code measured |
| Design Arena: PowerPoint slides | Not measured | 1154 | Only Kimi K2.7 Code measured |
| τ²-Bench Telecom | Not measured | 90.1% | Only Kimi K2.7 Code measured |
| APEX-Agents | Not measured | 37.6% | Only Kimi K2.7 Code measured |
| Vending-Bench 2 | Not measured | $5,083 | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 27 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4 Turbo | Kimi K2.7 Code | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.6% | Only Kimi K2.7 Code measured |
| Humanity's Last Exam (Artificial Analysis run) | 3.1% | 35.0% | Kimi K2.7 Code |
| GPQA Diamond (Epoch AI run) | Not measured | 87.9% | Only Kimi K2.7 Code measured |
| SimpleBench | Not measured | 57.9% | Only Kimi K2.7 Code measured |
| Chess puzzles | Not measured | 14.0% | Only Kimi K2.7 Code measured |
| LMArena Text: hard prompts | 1251 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: expert | 1223 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: hard prompts in English | 1266 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | GPT-4 Turbo | Kimi K2.7 Code | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 95.6% | Only Kimi K2.7 Code measured |
| FrontierMath, tiers 1 to 3 | Not measured | 54.0% | Only Kimi K2.7 Code measured |
| FrontierMath, tier 4 | Not measured | 12.2% | Only Kimi K2.7 Code measured |
| LMArena Text: math | 1272 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: mathematical work | 1268 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | GPT-4 Turbo | Kimi K2.7 Code | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 80.5% | Not measured | Only GPT-4 Turbo measured |
| MedQA (Vals AI) | 82.0% | Not measured | Only GPT-4 Turbo measured |
| MMLU Pro (Artificial Analysis run) | 69.4% | Not measured | Only GPT-4 Turbo measured |
| SimpleQA Verified | Not measured | 36.5% | Only Kimi K2.7 Code measured |
| MMLU | 81.3% | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: science | 1256 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: medicine and healthcare | 1239 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: legal and government | 1265 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: business and finance | 1222 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-4 Turbo | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1264 | Only Kimi K2.7 Code measured |
| Design Arena: UI components | Not measured | 1259 | Only Kimi K2.7 Code measured |
| Design Arena: game dev | Not measured | 1220 | Only Kimi K2.7 Code measured |
| Design Arena: data viz | Not measured | 1227 | Only Kimi K2.7 Code measured |
| Design Arena: 3D | Not measured | 1241 | Only Kimi K2.7 Code measured |
| Design Arena: all code categories | Not measured | 1253 | Only Kimi K2.7 Code measured |
| Design Arena: SVG | Not measured | 1176 | Only Kimi K2.7 Code measured |
| Design Arena: ASCII art | Not measured | 1196 | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index25 boards, none shared
| Benchmark | GPT-4 Turbo | Kimi K2.7 Code | Leader |
|---|---|---|---|
| IFBench | Not measured | 63.1% | Only Kimi K2.7 Code measured |
| Long context reasoning (AA-LCR) | Not measured | 79.3% | Only Kimi K2.7 Code measured |
| DTBench | 61.6% | Not measured | Only GPT-4 Turbo measured |
| LMCA | 9.8% | Not measured | Only GPT-4 Turbo measured |
| Surface Evolver Bench | Not measured | 48.8% | Only Kimi K2.7 Code measured |
| LMArena Text | 1272 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: instruction following | 1249 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: creative writing | 1268 | Not measured | Only GPT-4 Turbo measured |
| LMArena Vision | 1090 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: English | 1291 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: non-English | 1245 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Chinese | 1242 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: German | 1259 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Japanese | 1194 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Korean | 1187 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: French | 1276 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Spanish | 1260 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Russian | 1259 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: Polish | 1302 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: multi-turn | 1267 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: longer queries | 1254 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: writing and language | 1279 | Not measured | Only GPT-4 Turbo measured |
| LMArena Text: entertainment and media | 1258 | Not measured | Only GPT-4 Turbo measured |
| LMArena Vision: English | 1097 | Not measured | Only GPT-4 Turbo measured |
| LMArena Vision: Chinese | 1045 | Not measured | Only GPT-4 Turbo measured |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4 Turbo | Kimi K2.7 Code | 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 K2.7 Code costs less
Repository review
50K input + 3K output tokens
Kimi K2.7 Code costs less
Agent loop
200K input + 10K output tokens
Kimi K2.7 Code 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-4 Turbo | MoonshotAI Kimi K2.7 Code |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | April 9, 2024 | June 12, 2026 |
| Context window | 128K | 262K |
| Input $/Mtok | $10.00 | $0.95 |
| Output $/Mtok | $30.00 | $4.00 |
| Coding index | Not benchmarked | 53.4 |
| Independent measurements behind it | 0 | 4 |
| Cost per solved task | Not computable | $0.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4 Turbo better than Kimi K2.7 Code for coding?
Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; GPT-4 Turbo has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-4 Turbo or Kimi K2.7 Code?
GPT-4 Turbo costs $10.00 per million input tokens and $30.00 per million output tokens; Kimi K2.7 Code costs $0.95 and $4.00. Cost per solved task is known for Kimi K2.7 Code only.
Which has the bigger context window, GPT-4 Turbo or Kimi K2.7 Code?
Kimi K2.7 Code, with 262K tokens against 128K.
How many benchmarks is the GPT-4 Turbo vs Kimi K2.7 Code comparison based on?
4 benchmarks have a result for both models as of October 21, 2026. GPT-4 Turbo's coding index rests on 0 independent benchmarks and Kimi K2.7 Code's on 4. Where only one model has a result, the page says so instead of naming a winner.