Model Comparison
GLM-4.7-Flash vs Kimi K2 InstructWhich is better in 2026?
GLM-4.7-Flash significantly outperforms across most benchmarks. GLM-4.7-Flash is 3.3x cheaper per token.
Verdict: GLM-4.7-Flash vs Kimi K2 Instruct — which is better?
GLM-4.7-Flash (by Zhipu AI) and Kimi K2 Instruct (by Moonshot AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
GLM-4.7-Flash outperforms in 3 benchmarks (AIME 2025, GPQA, Humanity's Last Exam), while Kimi K2 Instruct is better at 0 benchmarks. GLM-4.7-Flash significantly outperforms across most benchmarks.
On price, GLM-4.7-Flash is roughly 3.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K2 Instruct also accepts a larger context window (200,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose GLM-4.7-Flash if…
- you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
- cost matters — it's about 3.3x cheaper per token
- you want the most recent training data — it shipped Jan 2026
Choose Kimi K2 Instruct if…
- you process long inputs — it offers a 200,000 token context window
Performance Benchmarks
Comparative analysis across standard metrics
GLM-4.7-Flash outperforms in 3 benchmarks (AIME 2025, GPQA, Humanity's Last Exam), while Kimi K2 Instruct is better at 0 benchmarks.
GLM-4.7-Flash significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-4.7-Flash ($0.07/1M tokens) is 7.1x cheaper than Kimi K2 Instruct ($0.50/1M tokens).
For output processing, GLM-4.7-Flash ($0.40/1M tokens) is 1.3x cheaper than Kimi K2 Instruct ($0.50/1M tokens).
In conclusion, Kimi K2 Instruct is more expensive than GLM-4.7-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2 Instruct has 970.0B more parameters than GLM-4.7-Flash, making it 3233.3% larger.
Context Window
Maximum input and output token capacity
Kimi K2 Instruct accepts 200,000 input tokens compared to GLM-4.7-Flash's 128,000 tokens. Kimi K2 Instruct can generate longer responses up to 200,000 tokens, while GLM-4.7-Flash is limited to 16,384 tokens.
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
GLM-4.7-Flash was released on 2026-01-19, while Kimi K2 Instruct was released on 2025-07-11.
GLM-4.7-Flash is 6 months newer than Kimi K2 Instruct.
Jan 19, 2026
6 months ago
6mo newerJul 11, 2025
1.0 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-4.7-Flash is available from ZAI. Kimi K2 Instruct is available from Fireworks, Novita.
GLM-4.7-Flash
Kimi K2 Instruct
Outputs Comparison
Key Takeaways
GLM-4.7-Flash
View detailsZhipu AI
Kimi K2 Instruct
View detailsMoonshot AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GLM-4.7-Flash and Kimi K2 Instruct side-by-side, then vote on the output you prefer.
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FAQ
Common questions about GLM-4.7-Flash vs Kimi K2 Instruct.