Last refreshed 2026-07-26. Next refresh: weekly.
Why use Claude Sonnet 4.5 on Replicate API?
Replicate API offers Claude Sonnet 4.5 with pay-as-you-go pricing at $3.00/1M input tokens. Replicate is a cloud-based platform that enables users to run machine learning models easily and efficiently.
Compare Claude Sonnet 4.5 across 8 providers to find the best fit for your use caseInput / 1M
$3.00
Output / 1M
$15.00
Cache
Not sourced
Batch
Not sourced
Setup recipe
Python + curlInstall
pip install replicateAuth
export REPLICATE_API_TOKEN=...Call
import replicate
output = replicate.run(
"anthropic/claude-4.5-sonnet",
input={"prompt": "Hello"}Model ID
anthropic/claude-4.5-sonnetRequest example
import replicate
# reads REPLICATE_API_TOKEN from env
# anthropic/claude-4.5-sonnet format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
"anthropic/claude-4.5-sonnet",
input={"prompt": "Hello"}
)
# Output is a list or generator depending on the model
print("".join(output))Gotchas
- Use provider model ID "anthropic/claude-4.5-sonnet", not the LLMReference slug "claude-sonnet-4-5".
- Replicate uses "owner/model-name" format (e.g. "meta/meta-llama-3-8b-instruct") for the latest version, or "owner/model-name:version-sha" to pin to a specific version. The REST endpoint splits owner and model-name into the path: /v1/models/{owner}/{model-name}/predictions.
- The examples expect REPLICATE_API_TOKEN; rename it only if your application config maps the new variable.
Compare Claude Sonnet 4.5 Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Microsoft Foundry | $3.00 | $15.00 |
| Anthropic | $3.00 | $15.00 |
| Snowflake Cortex | — | — |
| GCP Vertex AI | $3.00 | $15.00 |
| AWS Bedrock | $9.00 | $45.00 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $3.00 |
| Output tokens | $15.00 |
Capabilities
VisionMultimodalReasoningJSON / Tool useStructured Outputs
About Claude Sonnet 4.5
Claude Sonnet 4.5 is Anthropic's Claude 4.5 model with multimodal text and image input and an optional reasoning mode. It offers a 200K-token context window and scores 86 on MMLU PRO.
Get Started
Model Specs
Released2025-09-29
Context200k
ArchitectureDecoder Only
Knowledge cutoff2025-12