Official

anthropic / claude-3.7-sonnet

The most intelligent Claude model and the first hybrid reasoning model on the market (claude-3-7-sonnet-20250219)

Warm

Public
1.1M runs
Priced per token
Commercial use
License

Run with an API

Playground API Examples README

Prediction

anthropic/claude-3.7-sonnet

Official model

anthropic/claude-3.7-sonnet

9f04v4ypdhrme0cn7q6bc4t0sw

Status

Succeeded

Source

Web

Total duration

5.8s

Created

about 2 months ago

Input

prompt: Give me a recipe for pancakes that could feed all of California.
max_tokens: 8192
system_prompt
max_image_resolution: 0.5

{
  "prompt": "Give me a recipe for pancakes that could feed all of California.",
  "max_tokens": 8192,
  "system_prompt": "",
  "max_image_resolution": 0.5
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run anthropic/claude-3.7-sonnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const input = {
  prompt: "Give me a recipe for pancakes that could feed all of California.",
  max_tokens: 8192,
  system_prompt: "",
  max_image_resolution: 0.5
};

for await (const event of replicate.stream("anthropic/claude-3.7-sonnet", { input })) {
  process.stdout.write(event.toString());
};

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run anthropic/claude-3.7-sonnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

# The anthropic/claude-3.7-sonnet model can stream output as it's running.
for event in replicate.stream(
    "anthropic/claude-3.7-sonnet",
    input={
        "prompt": "Give me a recipe for pancakes that could feed all of California.",
        "max_tokens": 8192,
        "system_prompt": "",
        "max_image_resolution": 0.5
    },
):
    print(str(event), end="")

To learn more, take a look at the guide on getting started with Python.

Run anthropic/claude-3.7-sonnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "input": {
      "prompt": "Give me a recipe for pancakes that could feed all of California.",
      "max_tokens": 8192,
      "system_prompt": "",
      "max_image_resolution": 0.5
    }
  }' \
  https://api.replicate.com/v1/models/anthropic/claude-3.7-sonnet/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

# Colossal California Pancake Recipe ## Ingredients - 800 million cups all-purpose flour (roughly 100 million pounds) - 400 million cups milk (about 3.2 billion pints) - 200 million eggs (approximately 16.7 million dozen) - 40 million cups sugar - 20 million tablespoons baking powder - 10 million teaspoons salt - 10 million cups butter, melted ## Instructions 1. Locate approximately 10,000 industrial-sized mixing facilities across the state. 2. Coordinate 100,000 volunteer mixing teams. 3. Combine dry ingredients in massive containers using cement mixer-style equipment. 4. In separate containers, whisk together the milk and eggs (perhaps using fire hose systems for circulation). 5. Gradually incorporate wet ingredients into dry ingredients. 6. Cook on 500,000 simultaneously operating extra-large griddles. 7. Serve with approximately 5 million gallons of maple syrup. ## Notes - Cooking time: Approximately 3 weeks with 24/7 operation - Would require borrowing industrial equipment from multiple nations - May cause maple syrup shortages worldwide - Environmental impact statement pending Would you like me to calculate the exact nutritional information for 39 million servings? 😊

{
  "completed_at": "2025-02-25T15:49:55.109073Z",
  "created_at": "2025-02-25T15:49:49.292000Z",
  "data_removed": false,
  "error": null,
  "id": "9f04v4ypdhrme0cn7q6bc4t0sw",
  "input": {
    "prompt": "Give me a recipe for pancakes that could feed all of California.",
    "max_tokens": 8192,
    "system_prompt": "",
    "max_image_resolution": 0.5
  },
  "logs": "Running prediction...",
  "metrics": {
    "input_token_count": 21,
    "tokens_per_second": 53.60948617837659,
    "output_token_count": 311,
    "predict_time": 5.802968394,
    "total_time": 5.817073,
    "time_to_first_token": 0.015861292
  },
  "output": [
    "#",
    " Colossal California",
    " Pancake",
    " Recipe\n\n## Ingredients",
    "\n- 800",
    " million",
    " cups",
    " all",
    "-purpose flour (",
    "roughly",
    " 100",
    " million",
    " pounds",
    ")\n- 400",
    " million cups",
    " milk",
    " (about",
    " 3",
    ".",
    "2",
    " billion p",
    "ints)\n- ",
    "200 million eggs (",
    "approximately 16.",
    "7 million",
    " dozen",
    ")\n- 40",
    " million cups sugar",
    "\n- 20 million",
    " tabl",
    "espoons baking powder",
    "\n- 10 ",
    "million teaspoons salt",
    "\n- 10",
    " million cups butter,",
    " melted",
    "\n\n## Instructions\n1.",
    " Locate",
    " approximately",
    " 10,",
    "000 industrial",
    "-sized mixing facilities",
    " across",
    " the",
    " state.",
    "\n2. Coordinate",
    " ",
    "100,000 volunteer",
    " mixing",
    " teams.\n3.",
    " Combine",
    " dry",
    " ingredients in massive",
    " containers",
    " using",
    " cement",
    " mixer",
    "-",
    "style",
    " equipment.\n4.",
    " In",
    " separate containers, wh",
    "isk together the",
    " milk",
    " an",
    "d eggs (",
    "perhaps",
    " using fire",
    " hose",
    " systems",
    " for",
    " circulation",
    ").\n5.",
    " Gradually incorporate wet",
    " ingredients into dry ingredients.",
    "\n6. Cook",
    " on",
    " ",
    "500",
    ",000 simultaneously",
    " operating extra",
    "-large griddles.",
    "\n7. Serve",
    " with",
    " approximately",
    " 5",
    " million gallons of",
    " maple syrup.",
    "\n\n## Notes",
    "\n- Cooking",
    " time:",
    " Approximately 3 weeks",
    " with",
    " ",
    "24/7 operation",
    "\n- Woul",
    "d require",
    " borrow",
    "ing industrial",
    " equipment",
    " from multiple",
    " nations",
    "\n- May",
    " cause",
    " maple",
    " syrup shortages worldwide",
    "\n- Environmental",
    " impact statement",
    " pending\n\nWoul",
    "d you like me to calculate",
    " the exact nutrit",
    "ional information",
    " for ",
    "39",
    " million serv",
    "ings?",
    " ",
    "😊"
  ],
  "started_at": "2025-02-25T15:49:49.306105Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream-b.svc.ric1.c.replicate.net/v1/streams/hydokvsqdvn3yb3pq7sndxhmwx32kz64yrscbhojdinf5t2fqn7a",
    "get": "https://api.replicate.com/v1/predictions/9f04v4ypdhrme0cn7q6bc4t0sw",
    "cancel": "https://api.replicate.com/v1/predictions/9f04v4ypdhrme0cn7q6bc4t0sw/cancel"
  },
  "version": "hidden"
}

Generated in

5.8 seconds

Input tokens

Output tokens

310

Tokens per second

53.61 tokens / second

Time to first token

16 milliseconds

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