chore: import upstream snapshot with attribution

models/poolside/laguna-m.1.toml

@@ -0,0 +1,19 @@
+name = "Laguna M.1"
+description = "Poolside's flagship agentic coding model for long-horizon work"
+family = "laguna"
+release_date = "2026-04-28"
+last_updated = "2026-06-13"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = false
+open_weights = true
+
+[limit]
+context = 262_144
+output = 32_768
+
+[modalities]
+input = ["text"]
+output = ["text"]

models/poolside/laguna-xs-2.1.toml

@@ -0,0 +1,52 @@
+name = "Laguna XS 2.1"
+description = "Agentic coding model from Poolside in the XS size class for local deployment"
+family = "laguna"
+release_date = "2026-07-02"
+last_updated = "2026-07-02"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = false
+open_weights = true
+
+[limit]
+context = 262_144
+output = 32_768
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 70.9
+metric = "resolved"
+harness = "Harbor"
+source = "https://poolside.ai/blog/introducing-laguna-xs-2-1"
+date = "2026-07-02"
+
+[[benchmarks]]
+name = "SWE-Bench Multilingual"
+score = 63.1
+metric = "resolve rate"
+harness = "Harbor"
+source = "https://poolside.ai/blog/introducing-laguna-xs-2-1"
+date = "2026-07-02"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 47.6
+metric = "resolve rate"
+harness = "Harbor"
+source = "https://poolside.ai/blog/introducing-laguna-xs-2-1"
+date = "2026-07-02"
+
+[[benchmarks]]
+name = "Terminal-Bench"
+score = 37.5
+metric = "success rate"
+harness = "Harbor"
+version = "2.0"
+source = "https://poolside.ai/blog/introducing-laguna-xs-2-1"
+date = "2026-07-02"

models/poolside/laguna-xs.2.toml

@@ -0,0 +1,19 @@
+name = "Laguna XS.2"
+description = "Agentic coding model from Poolside in the XS size class for local deployment"
+family = "laguna"
+release_date = "2026-04-28"
+last_updated = "2026-06-13"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = false
+open_weights = true
+
+[limit]
+context = 262_144
+output = 32_768
+
+[modalities]
+input = ["text"]
+output = ["text"]