GLM-5.1 vs Kimi K2 Instruct
GLM-5.1 (2026) and Kimi K2 Instruct (2025) are frontier-tier reasoning models from Zhipu AI and Moonshot AI. GLM-5.1 ships a 200k-token context window, while Kimi K2 Instruct ships a not-yet-sourced context window. On pricing, Kimi K2 Instruct costs $0.6/1M input tokens versus $0.95/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Kimi K2 Instruct is ~58% cheaper at $0.6/1M; pay for GLM-5.1 only for coding workflow support.
Specs
| Released | 2026-03-27 | 2025-01-01 |
| Context window | 200k | — |
| Parameters | 744B total, 40-44B active | — |
| Architecture | mixture of experts | decoder only |
| License | Proprietary | MIT |
| Knowledge cutoff | - | - |
Pricing and availability
| GLM-5.1 | Kimi K2 Instruct | |
|---|---|---|
| Input price | $0.95/1M tokens | $0.6/1M tokens |
| Output price | $3.15/1M tokens | $2.5/1M tokens |
| Providers |
Capabilities
| GLM-5.1 | Kimi K2 Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on function calling: GLM-5.1, tool use: GLM-5.1, and code execution: GLM-5.1. Both models share reasoning mode and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, GLM-5.1 lists $0.95/1M input and $3.15/1M output tokens, while Kimi K2 Instruct lists $0.6/1M input and $2.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Kimi K2 Instruct lower by about $0.44 per million blended tokens. Availability is 2 providers versus 3, so concentration risk also matters.
Choose GLM-5.1 when coding workflow support are central to the workload. Choose Kimi K2 Instruct when provider fit, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which is cheaper, GLM-5.1 or Kimi K2 Instruct?
Kimi K2 Instruct is cheaper on tracked token pricing. GLM-5.1 costs $0.95/1M input and $3.15/1M output tokens. Kimi K2 Instruct costs $0.6/1M input and $2.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5.1 or Kimi K2 Instruct open source?
GLM-5.1 is listed under Proprietary. Kimi K2 Instruct is listed under MIT. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for reasoning mode, GLM-5.1 or Kimi K2 Instruct?
Both GLM-5.1 and Kimi K2 Instruct expose reasoning mode. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for function calling, GLM-5.1 or Kimi K2 Instruct?
GLM-5.1 has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, GLM-5.1 or Kimi K2 Instruct?
GLM-5.1 has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GLM-5.1 and Kimi K2 Instruct?
GLM-5.1 is available on Z.ai and OpenRouter. Kimi K2 Instruct is available on Fireworks AI, Together AI, and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-27. Data sourced from public model cards and provider documentation.