Kimi K2 Thinking vs GLM 5.2

This comparison does not currently contain a protocol-matched coding benchmark for both Kimi K2 Thinking and GLM 5.2, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Kimi K2 Thinking is $0.60 and GLM 5.2 is $0.75 per million tokens, so Kimi K2 Thinking is cheaper on this metric. Kimi K2 Thinking is $2.50 and GLM 5.2 is $2.40 per million tokens, so GLM 5.2 is cheaper on this metric.

GLM 5.2 has the larger sourced context window. Kimi K2 Thinking supports 262,144 tokens and GLM 5.2 supports 1,048,576 tokens.

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Both models have the same sourced self-hosting status: supported. Kimi K2 Thinking is open weight; GLM 5.2 is open weight.

Kimi K2 Thinking is not documented with image input; GLM 5.2 is not documented with image input. This reflects supported input modalities, not vision quality.

Kimi K2 Thinking has a sourced maximum output of 131,072 tokens; GLM 5.2's maximum output is not reported. A larger limit cannot be determined.

Kimi K2 Thinking: reasoning and tool calling. GLM 5.2: reasoning and tool calling. Feature support does not establish relative quality.

Kimi K2 Thinking has 2 sourced provider routes; GLM 5.2 has 5, so GLM 5.2 has broader tracked availability.

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.