Laguna XS 2.1 vs GLM-5

Laguna XS 2.1 is the better all-round choice, scoring 68/100 against GLM-5 (37). It leads on price and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Laguna XS 2.1 is cheaper at $0.06 input / $0.12 output per million tokens (median across 1 API provider; free on Poolside). GLM-5 costs $1.00 input / $3.20 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.075 per million tokens for Laguna XS 2.1 versus $1.55 for GLM-5 (21× as much).

There is no independent benchmark that covers both models yet. Laguna XS 2.1 has not been scored yet and GLM-5 has an ECI of 145.8.

There are no published SWE-bench Verified results for Laguna XS 2.1 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.

Laguna XS 2.1 has the largest context window at 262,144 tokens, against 204,800 for GLM-5. Maximum output per response: Laguna XS 2.1 up to 32,768, GLM-5 up to 131,072 tokens.

Laguna XS 2.1 accepts text; GLM-5 accepts text. They handle the same number of input types.

Yes, both publish their weights, so you can self-host them.

Laguna XS 2.1 is the newest, released Jul 2, 2026. GLM-5 came out Feb 12, 2026.

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.