diff --git a/content/manuals/ai/docker-agent/model-providers.md b/content/manuals/ai/docker-agent/model-providers.md
index 6ebe19f5ea83..82865c10190f 100644
--- a/content/manuals/ai/docker-agent/model-providers.md
+++ b/content/manuals/ai/docker-agent/model-providers.md
@@ -1,7 +1,7 @@
 ---
 title: Model providers
 description: Get API keys and configure cloud model providers for Docker Agent
-keywords: [docker agent, model providers, api keys, anthropic, openai, google, gemini]
+keywords: [docker agent, model providers, api keys, anthropic, openai, google, gemini, groq, deepseek, cerebras, fireworks, together, moonshot, openrouter, ovhcloud, baseten, vercel, cloudflare]
 weight: 10
 ---
 
@@ -16,9 +16,21 @@ models with Docker Model Runner](local-models.md).
 
 Docker Agent supports these cloud model providers:
 
-- Anthropic - Claude models
-- OpenAI - GPT models
-- Google - Gemini models
+- Anthropic — Claude models
+- Baseten — open-weight models via Baseten
+- Cerebras — fast inference for open-weight models
+- Cloudflare AI Gateway — multi-provider gateway with caching and observability
+- Cloudflare Workers AI — open-weight models on the Cloudflare edge
+- DeepSeek — DeepSeek chat and reasoning models
+- Fireworks AI — fast inference for open-weight models
+- Google — Gemini models
+- Groq — ultra-low-latency open-weight models
+- Moonshot AI — Kimi models
+- OpenAI — GPT models
+- OpenRouter — unified gateway to hundreds of models
+- OVHcloud — EU-hosted open-weight models
+- Together AI — large catalog of open-weight models
+- Vercel AI Gateway — unified gateway to OpenAI, Anthropic, Google, and more
 
 ## Anthropic
 
@@ -54,37 +66,193 @@ Available models include:
 - `anthropic/claude-opus-4-5`
 - `anthropic/claude-haiku-4-5`
 
-## OpenAI
+## Baseten
 
-OpenAI provides the GPT family of models, including GPT-5 and GPT-5 mini.
+[Baseten](https://www.baseten.co/) provides AI models through an
+OpenAI-compatible API. It is a good choice for deploying your own models or
+accessing hosted open-weight models.
 
-To get an API key:
+1. Get an API key from [Baseten](https://www.baseten.co/).
+2. Set the environment variable:
 
-1. Go to [platform.openai.com/api-keys](https://platform.openai.com/api-keys).
-2. Sign up or sign in to your account.
-3. Navigate to the API Keys section.
-4. Create a new API key.
-5. Copy the key.
+```console
+$ export BASETEN_API_KEY=your_key_here
+```
 
-Set your API key as an environment variable:
+Use Baseten models in your agent configuration:
+
+```yaml
+agents:
+  root:
+    model: baseten/deepseek-ai/DeepSeek-V3.1
+    instruction: You are a helpful assistant
+```
+
+Or with a named model for more control:
+
+```yaml
+models:
+  baseten_model:
+    provider: baseten
+    model: deepseek-ai/DeepSeek-V3.1
+    max_tokens: 8192
+
+agents:
+  root:
+    model: baseten_model
+    instruction: You are a helpful assistant
+```
+
+## Cerebras
+
+[Cerebras](https://www.cerebras.ai/) serves open-weight models (including
+GPT-OSS and GLM) on its wafer-scale hardware through an OpenAI-compatible API,
+delivering some of the highest inference speeds available.
+
+1. Create an API key from the [Cerebras Cloud console](https://cloud.cerebras.ai/).
+2. Set the environment variable:
 
 ```console
-$ export OPENAI_API_KEY=your_key_here
+$ export CEREBRAS_API_KEY=your_key_here
 ```
 
-Use OpenAI models in your agent configuration:
+Use Cerebras models in your agent configuration:
 
 ```yaml
 agents:
   root:
-    model: openai/gpt-5
+    model: cerebras/gpt-oss-120b
+    instruction: You are a helpful assistant
+```
+
+Available models include:
+
+- `cerebras/gpt-oss-120b`
+- `cerebras/zai-glm-4.7`
+
+## Cloudflare AI Gateway
+
+[Cloudflare AI Gateway](https://developers.cloudflare.com/ai-gateway/) is a
+single OpenAI-compatible endpoint that routes to models from OpenAI, Anthropic,
+Workers AI, and more, with caching, rate limiting, and observability.
+
+The gateway endpoint is account- and gateway-scoped. Three environment variables
+are required:
+
+```console
+$ export CLOUDFLARE_ACCOUNT_ID=your_account_id
+$ export CLOUDFLARE_GATEWAY_ID=your_gateway_id
+$ export CLOUDFLARE_API_TOKEN=your_api_token
+```
+
+Use Cloudflare AI Gateway in your agent configuration:
+
+```yaml
+agents:
+  root:
+    model: cloudflare-ai-gateway/workers-ai/@cf/meta/llama-3.1-8b-instruct
+    instruction: You are a helpful assistant
+```
+
+Or with a named model:
+
+```yaml
+models:
+  cf_gateway_model:
+    provider: cloudflare-ai-gateway
+    model: "workers-ai/@cf/meta/llama-3.1-8b-instruct"
+
+agents:
+  root:
+    model: cf_gateway_model
+    instruction: You are a helpful assistant
+```
+
+> [!NOTE]
+> The alias sends your token in the standard `Authorization: Bearer` header,
+> which works for unauthenticated gateways (the default) routing to Workers AI
+> models. Gateways with authentication enabled require the `cf-aig-authorization`
+> header, which is not supported by this alias. For that setup, use a [custom
+> provider](reference/config.md#models) instead.
+
+## Cloudflare Workers AI
+
+[Cloudflare Workers AI](https://developers.cloudflare.com/workers-ai/) runs
+open-weight models (Llama, Mistral, Qwen, Gemma, and more) on Cloudflare's
+global edge network.
+
+Workers AI is account-scoped, so two environment variables are required:
+
+```console
+$ export CLOUDFLARE_ACCOUNT_ID=your_account_id
+$ export CLOUDFLARE_API_TOKEN=your_api_token
+```
+
+Use Cloudflare Workers AI in your agent configuration:
+
+```yaml
+agents:
+  root:
+    model: cloudflare-workers-ai/@cf/meta/llama-3.1-8b-instruct
+    instruction: You are a helpful assistant
+```
+
+Available models include `@cf/meta/llama-3.1-8b-instruct`,
+`@cf/mistralai/mistral-small-3.1-24b-instruct`, and more. See the
+[Workers AI models catalog](https://developers.cloudflare.com/workers-ai/models/)
+for the full list.
+
+## DeepSeek
+
+[DeepSeek](https://www.deepseek.com/) serves its frontier chat and reasoning
+models through an OpenAI-compatible API, with strong price/performance on coding
+and reasoning tasks.
+
+1. Create an API key from the [DeepSeek Platform](https://platform.deepseek.com/api_keys).
+2. Set the environment variable:
+
+```console
+$ export DEEPSEEK_API_KEY=your_key_here
+```
+
+Use DeepSeek models in your agent configuration:
+
+```yaml
+agents:
+  root:
+    model: deepseek/deepseek-chat
     instruction: You are a helpful coding assistant
 ```
 
 Available models include:
 
-- `openai/gpt-5`
-- `openai/gpt-5-mini`
+- `deepseek/deepseek-chat` — DeepSeek-V3, general-purpose chat and tool calling
+- `deepseek/deepseek-reasoner` — DeepSeek-R1, extended-reasoning model
+
+## Fireworks AI
+
+[Fireworks AI](https://fireworks.ai/) is a fast inference host for open-weight
+models, serving Kimi K2, Llama, Qwen, DeepSeek, GLM, and others through an
+OpenAI-compatible API.
+
+1. Create an API key from the [Fireworks dashboard](https://fireworks.ai/account/api-keys).
+2. Set the environment variable:
+
+```console
+$ export FIREWORKS_API_KEY=your_key_here
+```
+
+Use Fireworks AI models in your agent configuration:
+
+```yaml
+agents:
+  root:
+    model: fireworks/accounts/fireworks/models/kimi-k2-instruct
+    instruction: You are a helpful assistant
+```
+
+Fireworks model IDs use the `accounts/fireworks/models/<name>` form. See the
+[Fireworks model library](https://fireworks.ai/models) for current IDs.
 
 ## Google Gemini
 
@@ -117,6 +285,198 @@ Available models include:
 - `google/gemini-2.5-flash`
 - `google/gemini-2.5-pro`
 
+## Groq
+
+[Groq](https://groq.com/) serves open-weight models on its LPU inference engine
+through an OpenAI-compatible API, with a focus on very low latency.
+
+1. Create an API key from the [Groq Console](https://console.groq.com/keys).
+2. Set the environment variable:
+
+```console
+$ export GROQ_API_KEY=your_key_here
+```
+
+Use Groq models in your agent configuration:
+
+```yaml
+agents:
+  root:
+    model: groq/llama-3.3-70b-versatile
+    instruction: You are a helpful assistant
+```
+
+Available models include `llama-3.3-70b-versatile`, `llama-3.1-8b-instant`, and
+more. See the [Groq models documentation](https://console.groq.com/docs/models)
+for current model IDs.
+
+## Moonshot AI
+
+[Moonshot AI](https://www.moonshot.ai/) serves its Kimi model family through an
+OpenAI-compatible API. Kimi K2 models are well-suited for coding and agentic
+tasks.
+
+1. Create an API key from the [Moonshot AI console](https://platform.moonshot.ai/console/api-keys).
+2. Set the environment variable:
+
+```console
+$ export MOONSHOT_API_KEY=your_key_here
+```
+
+Use Moonshot AI models in your agent configuration:
+
+```yaml
+agents:
+  root:
+    model: moonshot/kimi-k2-0905-preview
+    instruction: You are a helpful assistant
+```
+
+Available models include:
+
+- `moonshot/kimi-k2-0905-preview`
+- `moonshot/kimi-k2-turbo-preview`
+- `moonshot/kimi-k2-thinking`
+
+## OpenAI
+
+OpenAI provides the GPT family of models, including GPT-5 and GPT-5 mini.
+
+To get an API key:
+
+1. Go to [platform.openai.com/api-keys](https://platform.openai.com/api-keys).
+2. Sign up or sign in to your account.
+3. Navigate to the API Keys section.
+4. Create a new API key.
+5. Copy the key.
+
+Set your API key as an environment variable:
+
+```console
+$ export OPENAI_API_KEY=your_key_here
+```
+
+Use OpenAI models in your agent configuration:
+
+```yaml
+agents:
+  root:
+    model: openai/gpt-5
+    instruction: You are a helpful coding assistant
+```
+
+Available models include:
+
+- `openai/gpt-5`
+- `openai/gpt-5-mini`
+
+## OpenRouter
+
+[OpenRouter](https://openrouter.ai/) provides access to hundreds of models from
+many providers through a single OpenAI-compatible API, with automatic failover
+and unified billing.
+
+1. Get an API key from [OpenRouter](https://openrouter.ai/settings/keys).
+2. Set the environment variable:
+
+```console
+$ export OPENROUTER_API_KEY=your_key_here
+```
+
+Use OpenRouter in your agent configuration:
+
+```yaml
+agents:
+  root:
+    model: openrouter/meta-llama/llama-3.3-70b-instruct
+    instruction: You are a helpful assistant
+```
+
+OpenRouter model IDs include the upstream provider name (for example
+`anthropic/claude-sonnet-4-5` or `meta-llama/llama-3.3-70b-instruct`). Docker
+Agent preserves the full upstream model ID after the first slash. See the
+[OpenRouter models list](https://openrouter.ai/models) for available models.
+
+## OVHcloud
+
+[OVHcloud AI Endpoints](https://endpoints.ai.cloud.ovh.net/) serves open-weight
+models through an OpenAI-compatible API, hosted in the EU. Several models are
+available on a rate-limited free tier with no billing setup required.
+
+1. Create an access token from the
+   [OVHcloud AI Endpoints portal](https://endpoints.ai.cloud.ovh.net/).
+2. Set the environment variable:
+
+```console
+$ export OVH_AI_ENDPOINTS_ACCESS_TOKEN=your_token_here
+```
+
+Use OVHcloud models in your agent configuration:
+
+```yaml
+agents:
+  root:
+    model: ovhcloud/Qwen3.5-397B-A17B
+    instruction: You are a helpful assistant
+```
+
+Available models include `Qwen3.5-397B-A17B`, `Qwen3-32B`,
+`Meta-Llama-3_3-70B-Instruct`, and more. See the
+[AI Endpoints catalogue](https://endpoints.ai.cloud.ovh.net/) for current model
+IDs.
+
+## Together AI
+
+[Together AI](https://www.together.ai/) is one of the largest hosts of
+open-weight models, serving Llama, Qwen, DeepSeek, Kimi, GLM, and others
+through an OpenAI-compatible API.
+
+1. Create an API key from the [Together AI settings](https://api.together.ai/settings/api-keys).
+2. Set the environment variable:
+
+```console
+$ export TOGETHER_API_KEY=your_key_here
+```
+
+Use Together AI models in your agent configuration:
+
+```yaml
+agents:
+  root:
+    model: together/meta-llama/Llama-3.3-70B-Instruct-Turbo
+    instruction: You are a helpful assistant
+```
+
+See the [Together AI model library](https://docs.together.ai/docs/serverless-models)
+for current model IDs.
+
+## Vercel AI Gateway
+
+[Vercel AI Gateway](https://vercel.com/docs/ai-gateway) is a unified
+OpenAI-compatible endpoint that routes to models from OpenAI, Anthropic, Google,
+xAI, and more at list price with no markup.
+
+1. Create an API key from the [Vercel AI Gateway dashboard](https://vercel.com/docs/ai-gateway).
+2. Set the environment variable:
+
+```console
+$ export AI_GATEWAY_API_KEY=your_key_here
+```
+
+Use Vercel AI Gateway in your agent configuration:
+
+```yaml
+agents:
+  root:
+    model: vercel/openai/gpt-5
+    instruction: You are a helpful assistant
+```
+
+Vercel AI Gateway model IDs use the `creator/model` form (for example
+`openai/gpt-5` or `anthropic/claude-sonnet-4.5`). See the
+[Vercel AI Gateway documentation](https://vercel.com/docs/ai-gateway) for the
+current model list.
+
 ## OpenAI-compatible providers
 
 You can use the `openai` provider type to connect to any model or provider that
diff --git a/content/manuals/ai/docker-agent/reference/config.md b/content/manuals/ai/docker-agent/reference/config.md
index a5447b86e5a9..70e5ea56ecca 100644
--- a/content/manuals/ai/docker-agent/reference/config.md
+++ b/content/manuals/ai/docker-agent/reference/config.md
@@ -34,7 +34,7 @@ rag: # Optional - RAG sources
     docs: [./documents]
     strategies: [...]
 
-metadata: # Optional - author, license, readme
+metadata: # Optional - author, license, readme, version, tags
   author: Your Name
 ```
 
@@ -171,8 +171,10 @@ structured_output:
 | `parallel_tool_calls` | boolean | Enable parallel tool execution (default: true) | No       |
 | `token_key`           | string  | Authentication token key                       | No       |
 | `track_usage`         | boolean | Track token usage                              | No       |
-| `thinking_budget`     | mixed   | Reasoning effort (provider-specific)           | No       |
-| `provider_opts`       | object  | Provider-specific options                      | No       |
+| `thinking_budget`        | mixed   | Reasoning effort (provider-specific)                                        | No       |
+| `compaction_model`       | string  | Model to use for session compaction (summary generation); defaults to the agent's own model | No |
+| `bypass_models_gateway`  | boolean | Connect directly to the provider, bypassing any configured models gateway   | No       |
+| `provider_opts`          | object  | Provider-specific options                                                   | No       |
 
 ### Alloy models
 
@@ -182,6 +184,74 @@ Use multiple models in rotation by separating names with commas:
 model: anthropic/claude-sonnet-4-5,openai/gpt-5
 ```
 
+### Compaction model
+
+By default, when a session is compacted (via `/compact`, the proactive
+threshold trigger, or post-overflow recovery), Docker Agent uses the agent's
+own model to summarize the conversation. That summary call ingests the entire
+conversation and is the slowest, most expensive call in a session.
+
+You can point `compaction_model` at a smaller, faster model to make compaction
+cheaper without changing the model that runs the conversation:
+
+```yaml
+models:
+  primary:
+    provider: anthropic
+    model: claude-sonnet-4-5
+    compaction_model: fast   # use the cheaper model for compaction
+  fast:
+    provider: anthropic
+    model: claude-haiku-4-5
+
+agents:
+  root:
+    model: primary
+    instruction: You are a helpful assistant.
+```
+
+The value can be a model name from the `models` section or an inline
+`provider/model` spec (for example `openai/gpt-5-mini`). When omitted,
+compaction reuses the agent's own model.
+
+> [!NOTE]
+> If the compaction model has a smaller context window than the primary model,
+> Docker Agent triggers compaction against the smaller window, so the summary
+> call can always ingest the full conversation. Pair the primary with a
+> compaction model whose context window is at least as large to keep the
+> proactive trigger aligned with the primary's window.
+
+### Bypass models gateway
+
+When a models gateway is configured (via `--models-gateway` or
+`CAGENT_MODELS_GATEWAY`), Docker Agent routes all model requests through it by
+default. Set `bypass_models_gateway: true` on a specific model to make it
+connect directly to its provider instead:
+
+```yaml
+models:
+  # Routed through the gateway when one is configured.
+  gateway-model:
+    provider: openai
+    model: gpt-5
+
+  # Always connects directly to Anthropic, even when a gateway is configured.
+  # Requires ANTHROPIC_API_KEY to be set.
+  direct-model:
+    provider: anthropic
+    model: claude-sonnet-4-5
+    bypass_models_gateway: true
+
+agents:
+  root:
+    model: direct-model
+    instruction: You are a helpful assistant.
+```
+
+A bypassed model authenticates with its own provider credentials
+(`OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, or the explicit `token_key`) rather
+than the gateway's token.
+
 ### Thinking budget
 
 Controls reasoning depth. Configuration varies by provider:
@@ -534,16 +604,20 @@ Results:
 
 Documentation and sharing information:
 
-| Property  | Type   | Description                     |
-| --------- | ------ | ------------------------------- |
-| `author`  | string | Author name                     |
-| `license` | string | License (e.g., MIT, Apache-2.0) |
-| `readme`  | string | Usage documentation             |
+| Property  | Type     | Description                               |
+| --------- | -------- | ----------------------------------------- |
+| `author`  | string   | Author name                               |
+| `license` | string   | License (e.g., MIT, Apache-2.0)           |
+| `readme`  | string   | Usage documentation                       |
+| `version` | string   | Semantic version string                   |
+| `tags`    | []string | Tags for categorization and discovery     |
 
 ```yaml
 metadata:
   author: Your Name
   license: MIT
+  version: "1.0.0"
+  tags: [coding, review]
   readme: |
     Description and usage instructions
 ```