[Workers AI] Add Qwen 3.8 27B model (#32813)

Author: mchenco

src/content/changelog/workers-ai/2026-08-17-qwen-3.8-27b-workers-ai.mdx

@@ -0,0 +1,22 @@
+---
+title: "Qwen 3.8 27B now available on Workers AI"
+description: Qwen 3.8 27B, Alibaba's 27-billion-parameter vision language model, is now available on Workers AI.
+products:
+  - workers-ai
+date: 2026-08-17
+---
+
+[`@cf/qwen/qwen3.8-27b`](/workers-ai/models/qwen3.8-27b/) is now available on Workers AI.
+
+Qwen 3.8 27B is a 27-billion-parameter instruction-tuned vision language model from Alibaba's Qwen family. It processes images and text together, with reasoning and function calling for agentic workflows.
+
+**Key capabilities:**
+
+- **Vision**: Accept image and text inputs and generate text responses.
+- **Reasoning**: Support thinking mode for complex, step-by-step problem-solving.
+- **Function calling**: Build agents that invoke tools and APIs across multiple conversation turns.
+- **262,144 token context window**: Retain long conversations and multimodal inputs across extended agent sessions.
+
+Use Qwen 3.8 27B through the [Workers AI binding](/workers-ai/configuration/bindings/) (`env.AI.run()`) or the REST API at `/ai/run`. You can also use [AI Gateway](/ai-gateway/) with these endpoints.
+
+For more information, refer to the [Qwen 3.8 27B model page](/workers-ai/models/qwen3.8-27b/) and [pricing](/workers-ai/platform/pricing/).

src/content/docs/workers-ai/platform/pricing.mdx

@@ -70,6 +70,7 @@ The Price in Tokens column is equivalent to the Price in Neurons column - the di
 | @cf/qwen/qwq-32b                             | $0.660 per M input tokens <br/> $1.000 per M output tokens                                        | 60000 neurons per M input tokens <br/> 90909 neurons per M output tokens                                                 |
 | @cf/qwen/qwen2.5-coder-32b-instruct          | $0.660 per M input tokens <br/> $1.000 per M output tokens                                        | 60000 neurons per M input tokens <br/> 90909 neurons per M output tokens                                                 |
 | @cf/qwen/qwen3-30b-a3b-fp8                   | $0.051 per M input tokens <br/> $0.335 per M output tokens                                        | 4625 neurons per M input tokens <br/> 30475 neurons per M output tokens                                                  |
+| @cf/qwen/qwen3.8-27b                         | $0.450 per M input tokens <br/> $3.200 per M output tokens                                        | 40909 neurons per M input tokens <br/> 290909 neurons per M output tokens                                               |
 | @cf/openai/gpt-oss-120b                      | $0.350 per M input tokens <br/> $0.750 per M output tokens                                        | 31818 neurons per M input tokens <br/> 68182 neurons per M output tokens                                                 |
 | @cf/openai/gpt-oss-20b                       | $0.200 per M input tokens <br/> $0.300 per M output tokens                                        | 18182 neurons per M input tokens <br/> 27273 neurons per M output tokens                                                 |
 | @cf/aisingapore/gemma-sea-lion-v4-27b-it     | $0.351 per M input tokens <br/> $0.555 per M output tokens                                        | 31876 neurons per M input tokens <br/> 50488 neurons per M output tokens                                                 |

src/content/workers-ai-models/deepseek-v4-pro-0813.json

@@ -1,10 +1,6 @@
 {
     "name": "@cf/deepseek-ai/deepseek-v4-pro-0813",
     "properties": [
-        {
-            "property_id": "beta",
-            "value": "false"
-        },
         {
             "property_id": "require_workers_paid",
             "value": "true"
@@ -48,7 +44,7 @@
     ],
     "id": "2d50837b-2dc7-4994-a690-a38e25c16d74",
     "source": 1,
-    "description": "deepseek-ai/deepseek-v4-pro-0813",
+    "description": "DeepSeek V4 Pro is a high-capability reasoning model from DeepSeek with a one million token context window, built for long-horizon agentic workflows and complex, multi-step problem-solving",
     "task": {
         "id": "c329a1f9-323d-4e91-b2aa-582dd4188d34",
         "name": "Text Generation",