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-5.1 | Kimi K2.6 | |
|---|---|---|
| Maker | Z.ai | Moonshot |
| Architecture | 754B 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 | ~200K | 256K |
| Multimodal | Text | Text + image |
| License | MIT | Modified-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?
| Priority | Winner |
|---|---|
| Long single-task autonomous runs | GLM-5.1 |
| Commercial self-hosting (license) | GLM-5.1 (MIT) |
| Image input / UI-from-screenshot | Kimi K2.6 |
| Large multi-agent orchestration | Kimi K2.6 |
| Lower cost | Kimi 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/api/v1/... \
-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.