diff --git a/models.md b/models.md
index 1c7d15e..71182bc 100644
--- a/models.md
+++ b/models.md
@@ -35,22 +35,53 @@ Trade-offs are real: the most private option (Tinfoil) isn't the greenest, and
 the greenest option (GreenPT) isn't the most private. The point of the co-op is
 that **you choose** which axis matters more for a given task.
 
+**How to pick, quick guide:**
+
+- **Everyday chat and drafting** → a fast model: `tinfoil/glm-5-3-flash`,
+  `greenpt/glm-5.3-flash`, or `greenpt/green-l`. These handle the bulk of what
+  people use chat for, at a fraction of flagship cost.
+- **Hard reasoning, coding, agentic work** → a flagship: `tinfoil/glm-5-3` or
+  `greenpt/glm-5.3` (same underlying model, different provider trade-off),
+  or `tinfoil/deepseek-v4-1-flash` for long documents and tool-driven tasks.
+- **Images in, text out (vision)** → `tinfoil/glm-5-3-flash`,
+  `tinfoil/deepseek-v4-1-flash`, or the Apertus models — see the ✅ in the
+  table below.
+- **Cheap and cheerful** → `tinfoil/gpt-oss-120b` or `greenpt/glm-5.3-flash`.
+- **Model origins matter to you** → the Apertus models (publicly developed;
+  see below).
+
 ## Current models
 
 Pricing is per 1 million tokens, input / output (what the co-op pays the
 provider — your own cost is your monthly allowance, not per-token billing).
+**Vision** means the model accepts images as input (screenshots, photos,
+documents to reason about) — all models output text. None of our current
+models generate images.
 
-| Model | Provider | Privacy | Green energy | Pricing (in / out) | Notes |
-|---|---|---|---|---|---|
-| `tinfoil/deepseek-v4-1-flash` | Tinfoil | architectural | undisclosed | $0.65 / $1.45 | Default; best for agentic tasks (1M context, tool calling). |
-| `tinfoil/gpt-oss-120b` | Tinfoil | architectural | undisclosed | $0.15 / $0.60 | Lightweight fallback. |
-| `tinfoil/glm-5-3-flash` | Tinfoil | architectural | undisclosed | $0.40 / $1.25 | Fast, efficient MoE model. |
-| `greenpt/green-r` | GreenPT | policy | 100% renewable | $0.35 / $0.95 | Reasoning, renewable energy. |
-| `greenpt/green-l` | GreenPT | policy | 100% renewable | $0.25 / $0.80 | Lightweight, renewable energy. |
-| `greenpt/glm-5.3-flash` | GreenPT | policy | 100% renewable | $0.11 / $0.44 | Fast GLM model, renewable energy. |
-| `greenpt/glm-5.3` | GreenPT | policy | 100% renewable | $1.10 / $4.40 | GLM flagship — strongest agentic model in the green tier, 1M context. |
-| `publicai/apertus-v1.5-8b` | PublicAI | policy | undisclosed | $0.10 / $0.20 | Fully open sovereign model, small/fast. |
-| `publicai/apertus-v1.5-70b` | PublicAI | policy | undisclosed | $0.82 / $2.92 | Fully open sovereign model, large/capable. |
+| Model | Provider | Privacy | Green | Vision | Context | Pricing (in / out) | Notes |
+|---|---|---|---|---|---|---|---|
+| `tinfoil/glm-5-3-flash` | Tinfoil | architectural | undisclosed | ✅ | 1M | $0.40 / $1.25 | Fast multimodal MoE; great everyday default with image input. |
+| `tinfoil/glm-5-3` | Tinfoil | architectural | undisclosed | — | 1M | $1.80 / $5.75 | GLM flagship; strongest agentic model, private tier. |
+| `tinfoil/deepseek-v4-1-flash` | Tinfoil | architectural | undisclosed | ✅ | 1M | $0.65 / $1.45 | Efficient MoE, image input, tool calling; great for long docs and agents. |
+| `tinfoil/gpt-oss-120b` | Tinfoil | architectural | undisclosed | — | 131K | $0.15 / $0.60 | Lightweight open-weight reasoning; cheapest private tier. |
+| `tinfoil/kimi-k3` | Tinfoil | architectural | undisclosed | ✅ (image + video) | 262K | $4.00 / $20.00 | Moonshot's flagship multimodal MoE; premium tier. |
+| `greenpt/green-r` | GreenPT | policy | 100% renewable | — | 128K | $0.35 / $0.95 | Reasoning-focused, renewable energy. |
+| `greenpt/green-l` | GreenPT | policy | 100% renewable | — | 128K | $0.25 / $0.80 | Lightweight, renewable energy. |
+| `greenpt/glm-5.3-flash` | GreenPT | policy | 100% renewable | — | 1M | $0.11 / $0.44 | Fast GLM model, renewable energy. |
+| `greenpt/glm-5.3` | GreenPT | policy | 100% renewable | — | 1M | $1.10 / $4.40 | GLM flagship — strongest agentic model in the green tier. |
+| `publicai/apertus-v1.5-8b` | PublicAI | policy | undisclosed | ✅ | 262K | $0.10 / $0.20 | Fully open sovereign model, small/fast, image understanding. |
+| `publicai/apertus-v1.5-70b` | PublicAI | policy | undisclosed | ✅ | 262K | $0.82 / $2.92 | Fully open sovereign model, large/capable, image understanding. |
+
+Vision is verified working through the co-op gateway (base64 image input via
+`/v1/chat/completions`, standard OpenAI format). In the chat UI, just attach
+an image to your message while using a ✅ model.
+
+**Same model, two providers:** `glm-5-3` (Tinfoil) and `glm-5.3` (GreenPT)
+are the same Z.ai model offered by two providers — Tinfoil's is
+architecturally private at $1.80/$5.75; GreenPT's is 100% renewable at
+$1.10/$4.40. That price/privacy trade-off in a single comparison is the
+co-op's whole idea in miniature: you pick which axis matters for the task
+at hand.
 
 ### Audio models
 
@@ -72,16 +103,25 @@ Spanish, Italian, Portuguese, Dutch, and Hindi variants.
 ```bash
 # Speech-to-text
 curl https://gateway.inference.coop/v1/audio/transcriptions \
-  -H "Authorization: Bearer sk-your-key" \
+  -H "Authorization: Bearer ***" \
   -F file=@your-audio.mp3 \
   -F model=tinfoil/whisper-large-v3-turbo
 
 # Text-to-speech (returns WAV audio)
 curl https://gateway.inference.coop/v1/audio/speech \
-  -H "Authorization: Bearer sk-your-key" \
+  -H "Authorization: Bearer ***" \
   -H "Content-Type: application/json" \
   -d '{"model": "tinfoil/voxtral-tts", "input": "Hello from the co-op", "voice": "neutral_female"}' \
   --output speech.wav
+
+# Vision (image input to a multimodal chat model)
+curl https://gateway.inference.coop/v1/chat/completions \
+  -H "Authorization: Bearer ***" \
+  -H "Content-Type: application/json" \
+  -d '{"model": "tinfoil/glm-5-3-flash", "messages": [{"role": "user", "content": [
+        {"type": "text", "text": "What is in this image?"},
+        {"type": "image_url", "image_url": {"url": "data:image/png;base64,..."}}
+      ]}]}'
 ```
 
 ### About the Apertus models