GLM-5 vs Kimi K2 Instruct
GLM-5 (2026) and Kimi K2 Instruct (2025) are frontier-tier reasoning models from Zhipu AI and Moonshot AI. GLM-5 ships a 200k-token context window, while Kimi K2 Instruct ships a 131k-token context window. On pricing, Kimi K2 Instruct costs $0.57/1M input tokens versus $0.60/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
GLM-5 is safer overall; choose Kimi K2 Instruct when provider fit matters.
Decision scorecard
Local evidence first| Signal | GLM-5 | Kimi K2 Instruct |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | reasoning-heavy apps and provider-routed production |
| Decision fit | Coding, RAG, and Agents | RAG, Long context, and Classification |
| Context window | 200k | 131k |
| Cheapest output | $2.08/1M tokens | $2.30/1M tokens |
| Provider routes | 7 tracked | 5 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- GLM-5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5 has the lower cheapest tracked output price at $2.08/1M tokens.
- GLM-5 has broader tracked provider coverage for fallback and route flexibility.
- GLM-5 uniquely exposes JSON / Tool use in local model data.
- Local decision data tags GLM-5 for Coding, RAG, and Agents.
- Local decision data tags Kimi K2 Instruct for RAG, Long context, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GLM-5
$1,000
Cheapest tracked route/tier: OpenRouter
Kimi K2 Instruct
$1,031
Cheapest tracked route/tier: Vercel AI Gateway
Estimated monthly gap: $31.00. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI, Together AI, and NVIDIA NIM; start route-level A/B tests there.
- Kimi K2 Instruct is $0.22/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for JSON / Tool use before moving production traffic.
- Provider overlap exists on Fireworks AI, Together AI, and NVIDIA NIM; start route-level A/B tests there.
- GLM-5 is $0.22/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- GLM-5 adds JSON / Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-11 | 2025-09-05 |
| Context window | 200k | 131k |
| Parameters | 744B total, 40B active | 1T total, 32B active (MoE) |
| Architecture | Mixture of Experts | Decoder Only |
| License | MITOSI-approved | MITOSI-approved |
| Openness | Open source | Open source |
| Weights | Available | Unknown |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: permitted | Commercial use: permitted |
| Knowledge cutoff | 2025-11 | - |
Pricing and availability
| Pricing attribute | GLM-5 | Kimi K2 Instruct |
|---|---|---|
| Input price | $0.60/1M tokens | $0.57/1M tokens |
| Output price | $2.08/1M tokens | $2.30/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5 | Kimi K2 Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | Yes |
| JSON / Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
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Last reviewed: 2026-06-30. Data sourced from public model cards and provider documentation.