Llama 3.2 Vision 90B vs Depth Anything v2: Which AI Model Should You Choose?
Pricing, context windows, latency, capabilities, and a one-line code switch โ everything you need to pick the right model.
Llama 3.2 Vision 90B and Depth Anything v2 are closely matched on pricing and context. The right choice depends on your specific workload โ see the table below for the full breakdown.
Side-by-side specs
| Spec | Llama 3.2 Vision 90B | Depth Anything v2 |
|---|---|---|
| Provider | Replicate | Replicate |
| Category | Multimodal | Multimodal |
| Input cost / 1M tokens | n/a | n/a |
| Output cost / 1M tokens | n/a | n/a |
| Context window | 131K tokens | โ |
| Max output tokens | 4,096 | โ |
| Avg. latency | โ | โ |
| Featured | โ | Yes |
| New | โ | โ |
| Capabilities | text image | image |
Pricing example
A typical chat workload of 100,000 input tokens plus 50,000 output tokens.
100K in ร n/a + 50K out ร n/a
100K in ร n/a + 50K out ร n/a
Switch in one line
Both models live behind Railwail's OpenAI-compatible endpoint. Replace the model string and you are done.
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.RAILWAIL_API_KEY,
baseURL: "https://railwail.com/v1",
});
// Before โ using Llama 3.2 Vision 90B
let r = await client.chat.completions.create({
model: "lucataco/ollama-llama3.2-vision-90b",
messages: [{ role: "user", content: "Hello" }],
});
// After โ switched to Depth Anything v2
r = await client.chat.completions.create({
model: "chenxwh/depth-anything-v2",
messages: [{ role: "user", content: "Hello" }],
});from openai import OpenAI
client = OpenAI(
api_key=os.environ["RAILWAIL_API_KEY"],
base_url="https://railwail.com/v1",
)
# Before โ using Llama 3.2 Vision 90B
r = client.chat.completions.create(
model="lucataco/ollama-llama3.2-vision-90b",
messages=[{"role": "user", "content": "Hello"}],
)
# After โ switched to Depth Anything v2
r = client.chat.completions.create(
model="chenxwh/depth-anything-v2",
messages=[{"role": "user", "content": "Hello"}],
)# Before โ using Llama 3.2 Vision 90B
curl https://railwail.com/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "lucataco/ollama-llama3.2-vision-90b",
"messages": [{"role": "user", "content": "Hello"}]
}'
# After โ switched to Depth Anything v2
curl https://railwail.com/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "chenxwh/depth-anything-v2",
"messages": [{"role": "user", "content": "Hello"}]
}'Which one wins for...
Quick verdicts derived from public specs. Always validate on your own workload.
Higher coding category match or larger context wins.
Bigger context window helps maintain long-form coherence.
The larger context window is the deciding factor.
Multimodal/vision support is required for image inputs.
Lower average latency wins for interactive UX.
The model with the lower input-token price wins.
Frequently asked questions
Try Llama 3.2 Vision 90B and Depth Anything v2 side by side
One API key, one endpoint, both models. Start free โ no credit card required.