GLM vs Kimi: Which Open-Weight Coding Model Wins in 2026?

GLM-5.1 vs Kimi K2.6 — two open-weight agentic coding models compared on price, context, multimodality, agent style and licensing. Which to point your coding agent at.

GLM vs Kimi: Which Open-Weight Coding Model Wins in 2026?

Two Open-Weight Agent Coders

GLM-5.1 (Z.ai) and Kimi K2.6 (Moonshot) are both open-weight models built for agentic, long-horizon coding — and both are genuinely competitive with closed flagships on their strengths. They differ on multimodality, agent style, and licensing. Both are on LinkModel under one key.

Specs

GLM-5.1Kimi K2.6
MakerZ.aiMoonshot
Architecture754B MoE (40B active)1T MoE (~32B active)
Input / Output (1M)~$1.40 / ~$4.40$0.95 / $4.00
Cache read~$0.26$0.16
Context~200K256K
MultimodalTextText + image
LicenseMITModified-MIT

Where GLM-5.1 Wins

  • Long autonomous runs — built for 8-hour continuous engineering tasks, planning and self-correcting throughout. Placed 3rd on Code Arena (~1530 Elo) and scored 58.4% on SWE-Bench Pro.
  • Fully MIT — commercial self-hosting without authorization.
  • Sustained agentic stamina — strong when the model must hold context and standards across a full workflow.

Where Kimi K2.6 Wins

  • Multimodal input — the only one of the two that takes images (UI-from-screenshot, document-with-figures).
  • Agent swarms — orchestrates up to 300 parallel sub-agents across thousands of steps.
  • Cheaper — lower input and better cache-hit economics.
  • Benchmarks — reported ahead of GPT-5.4 on HLE-Full with tools.

Which Should You Use?

PriorityWinner
Long single-task autonomous runsGLM-5.1
Commercial self-hosting (license)GLM-5.1 (MIT)
Image input / UI-from-screenshotKimi K2.6
Large multi-agent orchestrationKimi K2.6
Lower costKimi K2.6

Shared Caveats

Both are Chinese labs whose official APIs process data in China (a GDPR consideration) — self-host or use a zero-retention gateway (LinkModel defaults to zero retention). And check licensing: GLM-5.1 is MIT, Kimi K2.6 is Modified-MIT (commercial self-hosting needs authorization).

Test Both

Both are OpenAI-compatible; swap the model string:

# swap "glm-5.1" ⇄ "kimi-k2.6"
curl -X POST https://api.linkmodel.ai/v1/chat/completions \
  -H "Authorization: Bearer $LINKMODEL_API_KEY" -H "Content-Type: application/json" \
  -d '{ "model": "glm-5.1", "messages": [{"role":"user","content":"Refactor this module across files and run tests until green."}] }'

More in best coding LLM API, open-source LLM API, and DeepSeek vs Kimi vs MiniMax.

Bottom Line

GLM-5.1 for long autonomous runs and MIT self-hosting; Kimi K2.6 for multimodal input, agent swarms, and lower cost. Both punch above their price.

Start free with a $1 credit and point a coding agent at each.

About the author

Claire Lowe

Claire Lowe

AI and API researcher at LinkMode

Claire Lowe is an AI and API researcher at LinkModel, specializing in generative AI models, API pricing, provider comparisons, and multimodal infrastructure. Her work is grounded in official documentation, primary-source pricing data, and hands-on research, with a focus on helping developers and businesses make informed decisions about AI models and API providers.

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