GLM 4.6V vs Kimi K2 Thinking
Updated October 21, 2026. 11 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
GLM 4.6V has the edge where output tokens cost 2.8x less, and where what matters is LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
- Shared results
- 11
- GLM 4.6V only
- 27
- Kimi K2 Thinking only
- 19
- Like-for-like categories
- 7 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Kimi K2 Thinking
Kimi K2 Thinking leads, 22.0 against 11.2.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Kimi K2 Thinking has a GPQA Diamond result, 78.5%.
Directional only
Math
AIME
No call
Only Kimi K2 Thinking has a AIME result, 85.4%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K2 Thinking has a MMLU Pro result, 81.1%.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K2 Thinking has a Design Arena: websites result, 1113.
Directional only
Long documents
Listed context window
Kimi K2 Thinking
Kimi K2 Thinking takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 4.6V
GLM 4.6V $0.0008, Kimi K2 Thinking $0.0019 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Kimi K2 Thinking has the number, $0.61.
Directional only
At a glance
- Coding index
- GLM 4.6V not benchmarked, Kimi K2 Thinking not benchmarked.
- Widest category
- Agentic work, 61.4 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: GLM 4.6V 31.6% against Kimi K2 Thinking 93.0%, 61.4 points apart on a 0 to 100 scale.
- Output price
- GLM 4.6V $0.90 against Kimi K2 Thinking $2.50 per million output tokens, 2.8x apart.
- Context window
- GLM 4.6V takes 131K tokens, Kimi K2 Thinking 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 | GLM 4.6V | Bars | Kimi K2 Thinking | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 11 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GLM 4.6V | Kimi K2 Thinking | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 63.4% | Only Kimi K2 Thinking measured |
| LiveCodeBench (Vals AI) | Not measured | 63.1% | Only Kimi K2 Thinking measured |
| SWE-bench Verified (Vals AI) | Not measured | 60.2% | Only Kimi K2 Thinking measured |
| LiveCodeBench (Artificial Analysis run) | 41.1% | 85.3% | Kimi K2 Thinking |
| Terminal-Bench Hard (Artificial Analysis run) | 14.4% | 31.1% | Kimi K2 Thinking |
| Terminal-Bench | Not measured | 35.7% | Only Kimi K2 Thinking measured |
| WeirdML | Not measured | 42.8% | Only Kimi K2 Thinking measured |
| ALE-Bench | Not measured | 597.5 | Only Kimi K2 Thinking measured |
| LMArena Text: coding | 1389 | Not measured | Only GLM 4.6V measured |
| LMArena Text: software and IT | 1391 | Not measured | Only GLM 4.6V measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 4.6V | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.2 | 22.0 | Kimi K2 Thinking |
| Epoch Capabilities Index | Not measured | 145.8 | Only Kimi K2 Thinking measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 4.6V | Kimi K2 Thinking | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 31.6% | 93.0% | Kimi K2 Thinking |
| METR time horizons | Not measured | 59.2% | Only Kimi K2 Thinking measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 4.6V | Kimi K2 Thinking | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 78.5% | Only Kimi K2 Thinking measured |
| GPQA Diamond (Artificial Analysis run) | 71.9% | 83.8% | Kimi K2 Thinking |
| Humanity's Last Exam (Artificial Analysis run) | 9.6% | 23.8% | Kimi K2 Thinking |
| LMArena Text: hard prompts | 1367 | Not measured | Only GLM 4.6V measured |
| LMArena Text: expert | 1371 | Not measured | Only GLM 4.6V measured |
| LMArena Text: hard prompts in English | 1391 | Not measured | Only GLM 4.6V measured |
| LMArena Vision: diagrams | 1182 | Not measured | Only GLM 4.6V measured |
| LMArena Vision: homework | 1155 | Not measured | Only GLM 4.6V measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 4.6V | Kimi K2 Thinking | Leader |
|---|---|---|---|
| AIME | Not measured | 85.4% | Only Kimi K2 Thinking measured |
| MGSM (Vals AI) | Not measured | 90.2% | Only Kimi K2 Thinking measured |
| AA Math Index | 85.3 | 94.7 | Kimi K2 Thinking |
| AIME 2025 (Artificial Analysis run) | 85.3% | 94.7% | Kimi K2 Thinking |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GLM 4.6V | Kimi K2 Thinking | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 81.1% | Only Kimi K2 Thinking measured |
| LegalBench (Vals AI) | Not measured | 80.2% | Only Kimi K2 Thinking measured |
| CaseLaw (Vals AI) | Not measured | 65.7% | Only Kimi K2 Thinking measured |
| CorpFin (Vals AI) | Not measured | 60.6% | Only Kimi K2 Thinking measured |
| TaxEval (Vals AI) | Not measured | 71.7% | Only Kimi K2 Thinking measured |
| MedQA (Vals AI) | Not measured | 92.6% | Only Kimi K2 Thinking measured |
| MMLU Pro (Artificial Analysis run) | 79.9% | 84.8% | Kimi K2 Thinking |
| LMArena Text: science | 1389 | Not measured | Only GLM 4.6V measured |
| LMArena Text: medicine and healthcare | 1389 | Not measured | Only GLM 4.6V measured |
| LMArena Text: legal and government | 1393 | Not measured | Only GLM 4.6V measured |
| LMArena Text: business and finance | 1359 | Not measured | Only GLM 4.6V measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GLM 4.6V | Kimi K2 Thinking | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1113 | Only Kimi K2 Thinking measured |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GLM 4.6V | Kimi K2 Thinking | Leader |
|---|---|---|---|
| IFBench | 30.1% | 68.1% | Kimi K2 Thinking |
| Long context reasoning (AA-LCR) | 48.7% | 72.0% | Kimi K2 Thinking |
| CL-bench | Not measured | 17.6% | Only Kimi K2 Thinking measured |
| LMArena Text | 1376 | Not measured | Only GLM 4.6V measured |
| LMArena Text: instruction following | 1350 | Not measured | Only GLM 4.6V measured |
| LMArena Text: creative writing | 1347 | Not measured | Only GLM 4.6V measured |
| LMArena Vision | 1164 | Not measured | Only GLM 4.6V measured |
| LMArena Text: English | 1395 | Not measured | Only GLM 4.6V measured |
| LMArena Text: non-English | 1358 | Not measured | Only GLM 4.6V measured |
| LMArena Text: Chinese | 1425 | Not measured | Only GLM 4.6V measured |
| LMArena Text: Russian | 1339 | Not measured | Only GLM 4.6V measured |
| LMArena Text: multi-turn | 1359 | Not measured | Only GLM 4.6V measured |
| LMArena Text: longer queries | 1357 | Not measured | Only GLM 4.6V measured |
| LMArena Text: writing and language | 1347 | Not measured | Only GLM 4.6V measured |
| LMArena Text: entertainment and media | 1343 | Not measured | Only GLM 4.6V measured |
| LMArena Vision: English | 1179 | Not measured | Only GLM 4.6V measured |
| LMArena Vision: Chinese | 1217 | Not measured | Only GLM 4.6V measured |
| LMArena Vision: reading text | 1171 | Not measured | Only GLM 4.6V measured |
| LMArena Vision: creative writing | 1113 | Not measured | Only GLM 4.6V measured |
| Neither model has a result on the other 27 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GLM 4.6V | Kimi K2 Thinking | 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
GLM 4.6V costs less
Repository review
50K input + 3K output tokens
GLM 4.6V costs less
Agent loop
200K input + 10K output tokens
GLM 4.6V 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 | Z.ai GLM 4.6V | MoonshotAI Kimi K2 Thinking |
|---|---|---|
| Maker | Z.ai | Moonshot AI |
| Weights | Open weights | Open weights |
| Released | December 8, 2025 | November 6, 2025 |
| Context window | 131K | 262K |
| Input $/Mtok | $0.30 | $0.60 |
| Output $/Mtok | $0.90 | $2.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | $0.61 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 4.6V better than Kimi K2 Thinking for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. GLM 4.6V has the edge where output tokens cost 2.8x less, and where what matters is LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
Which is cheaper, GLM 4.6V or Kimi K2 Thinking?
GLM 4.6V costs $0.30 per million input tokens and $0.90 per million output tokens; Kimi K2 Thinking costs $0.60 and $2.50. Cost per solved task is known for Kimi K2 Thinking only.
Which has the bigger context window, GLM 4.6V or Kimi K2 Thinking?
Kimi K2 Thinking, with 262K tokens against 131K.
How many benchmarks is the GLM 4.6V vs Kimi K2 Thinking comparison based on?
11 benchmarks have a result for both models as of October 21, 2026. GLM 4.6V's coding index rests on 0 independent benchmarks and Kimi K2 Thinking's on 1. Where only one model has a result, the page says so instead of naming a winner.