GLM-5.2 vs Kimi K2.5
Verdict
GLM-5.2 leads 10–1 across 11 shared benchmarks.
GLM-5.2 10 · Kimi K2.5 1 · higher isn't always better — see caveats.
Per-benchmark head-to-head
Reported scores — protocols may differ. How we compare
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GLM-5.2Kimi K2.5
Capabilities
Reasoning
Reasoning: GLM-5.2 leads 3–0 across 3 shared reasoning benchmarks (largest gap: ARC-AGI, 77 vs 65.33 — protocols undisclosed).
4 reproduced2 unverified
What the labs claim
Vendor claims — compare against the measured scores above. A claim is what a developer says about its own model, not an independent measurement.
GLM-5.2
Coding
“Advanced Coding with Flexible Effort: Stronger coding capabilities with multiple thinking effort levels to balance performance and latency”
huggingface.co2026
Context Handling
“We propose IndexShare, which reuses the same indexer across every four sparse attention layers, reducing per-token FLOPs by 2.9x at a 1M context length.”
huggingface.co2026
General
“Pure Open: An MIT open-source license - no regional limits, technical access without borders”
huggingface.co2026
Kimi K2.5
Agentic / Tool Use
“It seamlessly integrates vision and language understanding with advanced agentic capabilities, instant and thinking modes, as well as conversational and agentic paradigms.”
github.com2026“K2.5 transitions from single-agent scaling to a self-directed, coordinated swarm-like execution scheme.”
github.com2026
Coding
“K2.5 generates code from visual specifications (UI designs, video workflows) and autonomously orchestrates tools for visual data processing.”
github.com2026
Multimodal
“Kimi K2.5 is an open-source, native multimodal agentic model built through continual pretraining on approximately 15 trillion mixed visual and text tokens atop Kimi-K2-Base.”
github.com2026