Model Comparison

GLM-5 vs Kimi K2-Thinking-0905

GLM-5 significantly outperforms across most benchmarks. Kimi K2-Thinking-0905 is 1.8x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

GLM-5 outperforms in 2 benchmarks (BrowseComp, SWE-Bench Verified), while Kimi K2-Thinking-0905 is better at 0 benchmarks.

GLM-5 significantly outperforms across most benchmarks.

Sun May 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Kimi K2-Thinking-0905 costs less

For input processing, GLM-5 ($1.00/1M tokens) is 2.1x more expensive than Kimi K2-Thinking-0905 ($0.47/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 1.6x more expensive than Kimi K2-Thinking-0905 ($2.00/1M tokens).

In conclusion, GLM-5 is more expensive than Kimi K2-Thinking-0905.*

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

Lowest available price from all providers
Sun May 17 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerFriendliAI
Moonshot AI
Kimi K2-Thinking-0905
Input tokens$0.47
Output tokens$2.00
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

256.0B diff

Kimi K2-Thinking-0905 has 256.0B more parameters than GLM-5, making it 34.4% larger.

Zhipu AI
GLM-5
744.0Bparameters
Moonshot AI
Kimi K2-Thinking-0905
1.0Tparameters
744.0B
GLM-5
1000.0B
Kimi K2-Thinking-0905

Context Window

Maximum input and output token capacity

Kimi K2-Thinking-0905 accepts 262,144 input tokens compared to GLM-5's 200,000 tokens. Kimi K2-Thinking-0905 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-Thinking-0905
Input262,144 tokens
Output262,144 tokens
Sun May 17 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

GLM-5

MIT

Open weights

Kimi K2-Thinking-0905

MIT

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Kimi K2-Thinking-0905 was released on 2025-09-05.

GLM-5 is 5 months newer than Kimi K2-Thinking-0905.

GLM-5

Feb 11, 2026

3 months ago

5mo newer
Kimi K2-Thinking-0905

Sep 5, 2025

8 months ago

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 FriendliAI, ZAI. Kimi K2-Thinking-0905 is available from DeepInfra, Novita, Fireworks.

GLM-5

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

Kimi K2-Thinking-0905

deepinfra logo
Deepinfra
Input Price:Input: $0.47/1MOutput Price:Output: $2.00/1M
novita logo
Novita
Input Price:Input: $0.48/1MOutput Price:Output: $2.00/1M
fireworks logo
Fireworks
Input Price:Input: $0.60/1MOutput Price:Output: $2.50/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Zhipu AI
Higher BrowseComp score (75.9% vs 60.2%)
Higher SWE-Bench Verified score (77.8% vs 71.3%)
Moonshot AI
Larger context window (262,144 tokens)
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Moonshot AI
Kimi K2-Thinking-0905

FAQ

Common questions about GLM-5 vs Kimi K2-Thinking-0905.

Which is better, GLM-5 or Kimi K2-Thinking-0905?

GLM-5 significantly outperforms across most benchmarks. GLM-5 is made by Zhipu AI and Kimi K2-Thinking-0905 is made by Moonshot AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GLM-5 compare to Kimi K2-Thinking-0905 in benchmarks?

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-Thinking-0905 scores AIME 2025: 100.0%, HMMT 2025: 97.5%, MMLU-Redux: 94.4%, FRAMES: 87.0%, MMLU-Pro: 84.6%.

Is GLM-5 cheaper than Kimi K2-Thinking-0905?

Kimi K2-Thinking-0905 is 2.1x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via friendli. Kimi K2-Thinking-0905 costs $0.47/M input and $2.00/M output via deepinfra.

What are the context window sizes for GLM-5 and Kimi K2-Thinking-0905?

GLM-5 supports 200K tokens and Kimi K2-Thinking-0905 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-5 and Kimi K2-Thinking-0905?

Key differences include context window (200K vs 262K), input pricing ($1.00 vs $0.47/M). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Kimi K2-Thinking-0905?

GLM-5 is developed by Zhipu AI and Kimi K2-Thinking-0905 is developed by Moonshot AI.