diff --git a/providers/lanseq/logo.svg b/providers/lanseq/logo.svg
new file mode 100644
index 00000000000..dffc0334255
--- /dev/null
+++ b/providers/lanseq/logo.svg
@@ -0,0 +1,3 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24">
+  <path d="M5 4h4v12h10v4H5V4zm6 4h8v4h-8V8z" fill="currentColor"/>
+</svg>
diff --git a/providers/lanseq/models/qwen3.8-27b-int4.toml b/providers/lanseq/models/qwen3.8-27b-int4.toml
new file mode 100644
index 00000000000..a2e1df9c4a2
--- /dev/null
+++ b/providers/lanseq/models/qwen3.8-27b-int4.toml
@@ -0,0 +1,26 @@
+# First-party Lanseq deployment documentation:
+# https://api.lanseq.cloud/docs
+# Pricing: input = $0.25/M tokens, cache_read = $0.045/M tokens, output = $1.99/M tokens.
+# Limits: context = 70,000 tokens, max output = 8,192 tokens.
+# Reasoning wire control: reasoning_effort = none | low | medium | xhigh.
+
+base_model = "alibaba/qwen3.8-27b"
+name = "Qwen3.8-27B INT4"
+description = "Text-only INT4 deployment of Qwen3.8-27B served by Lanseq."
+attachment = false
+
+reasoning_options = [
+  { type = "effort", values = ["none", "low", "medium", "xhigh"] },
+]
+
+[cost]
+input = 0.25
+output = 1.99
+cache_read = 0.045
+
+[limit]
+context = 70_000
+output = 8_192
+
+[modalities]
+input = ["text"]
diff --git a/providers/lanseq/provider.toml b/providers/lanseq/provider.toml
new file mode 100644
index 00000000000..f073bad3d64
--- /dev/null
+++ b/providers/lanseq/provider.toml
@@ -0,0 +1,5 @@
+name = "Lanseq"
+npm = "@ai-sdk/openai-compatible"
+env = ["LANSEQ_API_KEY"]
+api = "https://api.lanseq.cloud/v1"
+doc = "https://api.lanseq.cloud/docs"