GLM-5.2 vs Kimi K2.7-Code
Released within days of each other in June 2026, GLM-5.2 and Kimi K2.7-Code are two of the highest-value open-weights coding models to evaluate for agentic engineering. GLM-5.2 brings stronger public benchmark coverage and a 1M-token context route. Kimi K2.7-Code brings Moonshot's MCP-first evidence, multimodal input, and lower direct input pricing.
Pick GLM-5.2 for public benchmark confidence and long-context coding: the seed tracks SWE-bench Pro and Terminal-Bench 2.1 rows for GLM-5.2, while Kimi K2.7-Code has no public SWE-bench or Terminal-Bench submission. Pick Kimi K2.7-Code for MCP-heavy workflows, image/video input, and cheaper direct input tokens: Moonshot reports MCP Mark Verified at 81.1, and Kimi's direct input price is $0.95/M versus GLM's currently provider-dependent metered routes.
Decision scorecard
Local evidence first| Signal | GLM-5.2 | Kimi K2.7-Code |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | reasoning-heavy apps, tool-calling agents, and long-context analysis | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 262k |
| Cheapest output | $4.40/1M tokens | $3.07/1M tokens |
| Provider routes | 1 tracked | 2 tracked |
| Shared benchmarks | CursorBench leader | 5 shared |
Decision tradeoffs
- GLM-5.2 holds a shared-benchmark lead on CursorBench, ahead by 5.3 points.
- GLM-5.2 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5.2 uniquely exposes Code execution in local model data.
- Local decision data tags GLM-5.2 for Coding, RAG, and Agents.
- Kimi K2.7-Code has the lower cheapest tracked output price at $3.07/1M tokens.
- Kimi K2.7-Code has broader tracked provider coverage for fallback and procurement flexibility.
- Kimi K2.7-Code uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Kimi K2.7-Code for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GLM-5.2
$2,220
Cheapest tracked route/tier: OpenRouter
Kimi K2.7-Code
$1,257
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $963. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Kimi K2.7-Code is $1.33/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Code execution before moving production traffic.
- Kimi K2.7-Code adds Vision and Multimodal in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GLM-5.2 is $1.33/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
- GLM-5.2 adds Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-06-13 | 2026-06-12 |
| Context window | 1m | 262k |
| Parameters | 753B total, 40B active | 1T |
| Architecture | Mixture of Experts | Mixture of Experts |
| License | MITOSI-approved | MITOSI-approved |
| Openness | Open source | Open source |
| Weights | Available | Available |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: permitted | Commercial use: permitted |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | GLM-5.2 | Kimi K2.7-Code |
|---|---|---|
| Input price | $1.40/1M tokens | $0.61/1M tokens |
| Output price | $4.40/1M tokens | $3.07/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5.2 | Kimi K2.7-Code |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GLM-5.2 | Kimi K2.7-Code |
|---|---|---|
| CursorBench | 55.0 | 49.7 |
| CursorBench | 54.6 | 49.7 |
| GeneBench-Pro | 4.6 | 2.3 |
| CursorBench | 51.5 | 49.7 |
| MCP-Atlas | 76.8 | 76.0 |
Deep dive
The public benchmark comparison is one-sided because Kimi K2.7-Code skipped SWE-bench and Terminal-Bench submissions at launch. GLM-5.2 is the safer pick when a team needs standard leaderboard evidence for repository repair or terminal-agent workflows.
Kimi's evidence is narrower but relevant to MCP-centered agents. Its seeded rows include Kimi Code Bench v2, Program Bench, MLS Bench Lite, MCP Atlas, and MCP Mark Verified; those should not be collapsed into SWE-bench-style claims.
The infrastructure decision is real. GLM-5.2 has a 1M-token route for long-context work, while Kimi K2.7-Code has a 262K context window with multimodal input and a HighSpeed provider variant for latency-sensitive uses.
FAQ
Which has a larger context window, GLM-5.2 or Kimi K2.7-Code?
GLM-5.2 supports 1m tokens, while Kimi K2.7-Code supports 262k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, GLM-5.2 or Kimi K2.7-Code?
Kimi K2.7-Code is cheaper on tracked token pricing. GLM-5.2 costs $1.40/1M input and $4.40/1M output tokens. Kimi K2.7-Code costs $0.61/1M input and $3.07/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5.2 or Kimi K2.7-Code open source?
GLM-5.2 is listed under MIT. Kimi K2.7-Code 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 vision, GLM-5.2 or Kimi K2.7-Code?
Kimi K2.7-Code has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, GLM-5.2 or Kimi K2.7-Code?
Kimi K2.7-Code has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GLM-5.2 and Kimi K2.7-Code?
GLM-5.2 is available on OpenRouter. Kimi K2.7-Code is available on Moonshot AI Kimi and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
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Last reviewed: 2026-06-25. Data sourced from public model cards and provider documentation.