Model Comparison

GLM-5 vs Kimi K2.6

Kimi K2.6 significantly outperforms across most benchmarks. GLM-5 is 1.1x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

GLM-5 outperforms in 0 benchmarks, while Kimi K2.6 is better at 3 benchmarks (BrowseComp, SWE-Bench Verified, Terminal-Bench 2.0).

Kimi K2.6 significantly outperforms across most benchmarks.

Mon Apr 20 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GLM-5 costs less

For input processing, GLM-5 ($1.00/1M tokens) is 1.1x more expensive than Kimi K2.6 ($0.95/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 1.3x cheaper than Kimi K2.6 ($4.00/1M tokens).

In conclusion, Kimi K2.6 is more expensive than GLM-5.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Mon Apr 20 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerUnknown Organization
Moonshot AI
Kimi K2.6
Input tokens$0.95
Output tokens$4.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

256.0B diff

Kimi K2.6 has 256.0B more parameters than GLM-5, making it 34.4% larger.

Zhipu AI
GLM-5
744.0Bparameters
Moonshot AI
Kimi K2.6
1000.0Bparameters
744.0B
GLM-5
1000.0B
Kimi K2.6

Context Window

Maximum input and output token capacity

Kimi K2.6 accepts 262,144 input tokens compared to GLM-5's 200,000 tokens. Kimi K2.6 can generate longer responses up to 262,144 tokens, while GLM-5 is limited to 128,000 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Moonshot AI
Kimi K2.6
Input262,144 tokens
Output262,144 tokens
Mon Apr 20 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Kimi K2.6 supports multimodal inputs, whereas GLM-5 does not.

Kimi K2.6 can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5

Text
Images
Audio
Video

Kimi K2.6

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Kimi K2.6 uses Modified MIT License.

License differences may affect how you can use these models in commercial or open-source projects.

GLM-5

MIT

Open weights

Kimi K2.6

Modified MIT License

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Kimi K2.6 was released on 2026-04-20.

Kimi K2.6 is 2 months newer than GLM-5.

GLM-5

Feb 11, 2026

2 months ago

Kimi K2.6

Apr 20, 2026

0 days ago

2mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

GLM-5 is available from ZAI. Kimi K2.6 is available from Moonshot AI, Novita.

GLM-5

z logo
Unknown Organization
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M

Kimi K2.6

moonshot logo
Unknown Organization
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
novita logo
Novita
Input Price:Input: $0.95/1MOutput Price:Output: $4.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Zhipu AI
Less expensive output tokens
Moonshot AI
Larger context window (262,144 tokens)
Supports multimodal inputs
Less expensive input tokens
Higher BrowseComp score (86.3% vs 75.9%)
Higher SWE-Bench Verified score (80.2% vs 77.8%)
Higher Terminal-Bench 2.0 score (66.7% vs 56.2%)

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Moonshot AI
Kimi K2.6

FAQ

Common questions about GLM-5 vs Kimi K2.6

Kimi K2.6 significantly outperforms across most benchmarks. GLM-5 is made by Zhipu AI and Kimi K2.6 is made by Moonshot AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. Kimi K2.6 scores V*: 96.9%, AIME 2026: 96.4%, MathVision: 93.2%, HMMT Feb 26: 92.7%, GPQA: 90.5%.
Kimi K2.6 is 1.1x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via z. Kimi K2.6 costs $0.95/M input and $4.00/M output via moonshot.
GLM-5 supports 200K tokens and Kimi K2.6 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (200K vs 262K), input pricing ($1.00 vs $0.95/M), multimodal support (no vs yes), licensing (MIT vs Modified MIT License). See the full comparison above for benchmark-by-benchmark results.
GLM-5 is developed by Zhipu AI and Kimi K2.6 is developed by Moonshot AI.