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GLM-5.1 vs Kimi K2.6 for coding: which should you use?

· GLM· Kimi· Comparison

If DeepSeek V4-Pro is overkill, or you just want options, the two most interesting coding picks from the April 2026 Chinese wave are GLM-5.1 (Z.ai) and Kimi K2.6 (Moonshot). Both write good code, and they win at different things.

Kimi K2.6: the agentic, long-context coder

K2.6 is built for multi-step agent work and large contexts. It scores 66.7% on Terminal-Bench 2.0 and about 58.6% on SWE-Bench Pro, which is strong on real, end-to-end coding tasks that span many files and tool calls. Its standout feature is aggressive prompt-cache pricing (around $0.16/M on cache reads), which makes a long, stable system prompt or codebase context cheap to reuse across an agent session.

On Turiloop it's cheaper than a closed frontier model, and discounted right now.

GLM-5.1: the balanced, low-cost coder

GLM-5.1 is the dependable, well-rounded choice. It doesn't chase a single headline benchmark; it's a solid coder and tool-user at a noticeably lower price. For everyday code generation, refactors and tool loops that don't need a huge context window, it's the cost-efficient default.

On Turiloop it's a low-cost default, cheaper than Kimi on both input and output.

How to choose

  • Long-context, multi-step agents (large codebases, many tool calls, reused context) → Kimi K2.6. The Terminal-Bench score and cache pricing pay off exactly here.
  • Everyday coding on a budget (single files, quick refactors, high volume) → GLM-5.1. You save about 35% on output tokens and rarely miss the extra context.
  • Hardest code, competitive logic → step up to DeepSeek V4-Pro (LiveCodeBench 93.5).

Test both in five minutes

They share one OpenAI-compatible key on Turiloop, so you can run the same coding prompt against both by changing one string:

for model in ["glm-5.1", "kimi-k2.6"]:
    r = client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": "Refactor this function and add tests: ..."}],
    )
    out = r.choices[0].message.content
    # compare outputs side by side

The honest answer is to try both on your own code. Start with GLM-5.1 for cost, and move the long-context agent work to Kimi K2.6. Get a key on Turiloop: international card, pay-as-you-go.