Ling 3.0 Flash vs Kimi K2.7 Code
Kimi K2.7 Code leads Ling 3.0 Flash on coding, 53.4 to 29.6 on the Vibe Coding Index, and Ling 3.0 Flash costs 32.9x less per output token ($0.1215 vs $4.00 per million). Updated October 21, 2026; 13 benchmarks have a result for both.
Ling 3.0 Flash or Kimi K2.7 Code: which to pick
Pick Kimi K2.7 Code for coding: it scores 53.4 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash.
Pick Ling 3.0 Flash for output tokens 32.9x cheaper ($0.1215 vs $4.00 per million) and a lower cost per solved task ($0.05 against $0.35).
- Shared results
- 13
- Ling 3.0 Flash only
- 11
- Kimi K2.7 Code only
- 38
- Like-for-like categories
- 5 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
Kimi K2.7 Code
Kimi K2.7 Code scores 53.4 against 29.6.
2 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
Kimi K2.7 Code
Kimi K2.7 Code leads, 25.8 against 20.1.
Same board, both measured
Agentic work
AA Agentic Index
Kimi K2.7 Code
Kimi K2.7 Code leads, 21.0 against 19.3.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Ling 3.0 Flash has a GPQA Diamond result, 84.8%.
Directional only
Knowledge
MMLU Pro
No call
Only Ling 3.0 Flash has a MMLU Pro result, 82.0%.
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
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
Ling 3.0 Flash $0.0001, Kimi K2.7 Code $0.0029 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Ling 3.0 Flash
Ling 3.0 Flash $0.05, Kimi K2.7 Code $0.35.
Published attempt cost and pass rate
At a glance
- Coding index
- Ling 3.0 Flash 29.6 from 2 benchmarks, Kimi K2.7 Code 53.4 from 4 benchmarks.
- Widest category
- Coding, 17.4 points apart on average over 8 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Ling 3.0 Flash 2.9% against Kimi K2.7 Code 47.2%, 44.3 points apart on a 0 to 100 scale.
- Output price
- Ling 3.0 Flash $0.1215 against Kimi K2.7 Code $4.00 per million output tokens, 32.9x apart.
- Context window
- Both take 262K tokens.
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 | Ling 3.0 Flash | Bars | Kimi K2.7 Code | Ties |
|---|---|---|---|---|
| Coding | 1 | 7 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 1 | ||
| All shared boards | 1 | 12 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index17
| Benchmark | Ling 3.0 Flash | Kimi K2.7 Code | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1474 | Only Kimi K2.7 Code measured |
| AA Coding Index | 50.6 | 60.8 | Kimi K2.7 Code |
| LiveCodeBench (Vals AI) | 84.0% | 82.0% | Ling 3.0 Flash |
| SWE-bench Verified (Vals AI) | 65.2% | 78.2% | Kimi K2.7 Code |
| Vibe Code Bench (Vals AI) | 2.9% | 47.2% | Kimi K2.7 Code |
| Code migration (Vals AI) | 0.0% | 25.4% | Kimi K2.7 Code |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Kimi K2.7 Code measured |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | 67.0% | Kimi K2.7 Code |
| SkillsBench (Vals AI) | 27.9% | 50.0% | Kimi K2.7 Code |
| SciCode | 42.0% | 47.8% | Kimi K2.7 Code |
| 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 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 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ling 3.0 Flash | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.1 | 25.8 | Kimi K2.7 Code |
| Epoch Capabilities Index | Not measured | 150.1 | Only Kimi K2.7 Code measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ling 3.0 Flash | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Agentic Index | 19.3 | 21.0 | Kimi K2.7 Code |
| 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 |
| Finance Agent (Vals AI) | 30.3% | Not measured | Only Ling 3.0 Flash measured |
| Legal Research Bench (Vals AI) | 0.0% | Not measured | Only Ling 3.0 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 25.0% | Not measured | Only Ling 3.0 Flash 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 26 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Ling 3.0 Flash | Kimi K2.7 Code | Leader |
|---|---|---|---|
| GPQA Diamond | 84.8% | Not measured | Only Ling 3.0 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 85.5% | 89.6% | Kimi K2.7 Code |
| Humanity's Last Exam (Artificial Analysis run) | 23.7% | 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 |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Ling 3.0 Flash | 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 |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Ling 3.0 Flash | Kimi K2.7 Code | Leader |
|---|---|---|---|
| MMLU Pro | 82.0% | Not measured | Only Ling 3.0 Flash measured |
| LegalBench (Vals AI) | 79.7% | Not measured | Only Ling 3.0 Flash measured |
| CorpFin (Vals AI) | 61.9% | Not measured | Only Ling 3.0 Flash measured |
| TaxEval (Vals AI) | 70.7% | Not measured | Only Ling 3.0 Flash measured |
| MedCode (Vals AI) | 32.3% | Not measured | Only Ling 3.0 Flash measured |
| SimpleQA Verified | Not measured | 36.5% | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Ling 3.0 Flash | 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 | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ling 3.0 Flash | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 50.7% | Not measured | Only Ling 3.0 Flash measured |
| MedScribe (Vals AI) | 80.9% | Not measured | Only Ling 3.0 Flash measured |
| IFBench | Not measured | 63.1% | Only Kimi K2.7 Code measured |
| Long context reasoning (AA-LCR) | 73.0% | 79.3% | Kimi K2.7 Code |
| Surface Evolver Bench | Not measured | 48.8% | Only Kimi K2.7 Code 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 | Ling 3.0 Flash | 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
Ling 3.0 Flash costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash costs less
Agent loop
200K input + 10K output tokens
Ling 3.0 Flash 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 | inclusionAI Ling 3.0 Flash | MoonshotAI Kimi K2.7 Code |
|---|---|---|
| Maker | inclusionAI | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | July 23, 2026 | June 12, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.0405 | $0.95 |
| Output $/Mtok | $0.1215 | $4.00 |
| Coding index | 29.6 | 53.4 |
| Independent measurements behind it | 2 | 4 |
| Cost per solved task | $0.05 | $0.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ling 3.0 Flash better than Kimi K2.7 Code for coding?
Pick Kimi K2.7 Code for coding: it scores 53.4 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash. Pick Ling 3.0 Flash for output tokens 32.9x cheaper ($0.1215 vs $4.00 per million) and a lower cost per solved task ($0.05 against $0.35).
Which is cheaper, Ling 3.0 Flash or Kimi K2.7 Code?
Ling 3.0 Flash costs $0.0405 per million input tokens and $0.1215 per million output tokens; Kimi K2.7 Code costs $0.95 and $4.00. Per solved SWE-bench Verified task, Ling 3.0 Flash costs $0.05 and Kimi K2.7 Code $0.35.
Which has the bigger context window, Ling 3.0 Flash or Kimi K2.7 Code?
Neither: both take 262K tokens.
How many benchmarks is the Ling 3.0 Flash vs Kimi K2.7 Code comparison based on?
13 benchmarks have a result for both models as of October 21, 2026. Ling 3.0 Flash's coding index rests on 2 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.