Anthropic has launched a newer model, Claude Opus 4.6 (high), we suggest considering this model instead.

For more information, see Comparison of Claude Opus 4.6 (high) to other models and API provider benchmarks for Claude Opus 4.6 (high).

Claude Opus 4.5 (Non-reasoning) logo
Anthropic
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Proprietary model

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Released November 2025

Claude Opus 4.5 (Non-reasoning) API Provider Benchmarking & Analysis

Model Comparison

Analysis of API providers for Claude Opus 4.5 (Non-reasoning) across performance metrics including latency (time to first token), output speed (output tokens per second), price and others. API providers benchmarked include Databricks, Google Vertex, Microsoft Azure, Anthropic, Amazon Bedrock.

Fastest

#1
Google VertexGoogle Vertex
46.3 t/s
#2
AnthropicAnthropic
45.8 t/s
#3
AzureAzure
45.2 t/s
#4
DatabricksDatabricks
44.7 t/s
#5
AmazonAmazon
44.0 t/s

Output speed

Total 5 providers

Lowest Latency

#1
Google VertexGoogle Vertex
0.87 s
#2
AnthropicAnthropic
1.67 s
#3
AzureAzure
1.73 s
#4
AmazonAmazon
1.74 s
#5
DatabricksDatabricks
2.21 s

Time to first answer token

Total 5 providers

Lowest Price

Updated
#1
Google VertexGoogle Vertex
$4.10
#2
AnthropicAnthropic
$4.10
#3
AmazonAmazon
$4.10
#4
DatabricksDatabricks
$7.00
#5
AzureAzure
$7.00

Blended price (per 1M tokens)

Total 5 providers

Claude Opus 4.5 is available through 5 API providers, each offering different performance characteristics and pricing. Below is a comparison of the key metrics across providers.

  • For output speed, the top providers are Google Vertex (46.3 t/s), Anthropic (45.8 t/s), Azure (45.2 t/s).
  • For latency, Google Vertex (0.87s), Anthropic (1.67s), Azure (1.73s) offer the lowest time to first token.
  • For pricing, Google Vertex (4.10), Anthropic (4.10), Amazon (4.10) offer the lowest blended prices per 1M tokens.
  • Google Vertex stands out as the overall leader, ranking first across all three categories: speed, latency, and pricing.

Highlights

Speed

Output tokens per second · Higher is better

End-to-End Response Time

Seconds · Lower is better
Updated

Price

USD per 1M tokens (blended) · Lower is better

Update: Default performance benchmarking workload has updated to 10k input tokens to better reflect production use cases. You can still select different workloads above.

PricingPricing now includes “Cache Hit Price” with new blend ratios.

Pricing: Cache Hit, Input, and Output

Price (USD per M Tokens) · Lower is better · 10,000 Input Tokens

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

Price per token included in the request/message sent to the API, represented as USD per million Tokens.

The blended cache price shown here uses cache hit price only. Other caching costs differ by provider:

  • Anthropic: charges a separate cache write fee, with different rates for 5-minute and 1-hour TTLs (1-hour TTL is more expensive). Blended price charts use Anthropic cache write price for the input leg.
  • Google (Vertex/Gemini): charges a per-hour cache storage fee in addition to cache hit pricing. Some providers also use tiered pricing for prompts above 200K tokens.
  • OpenAI, DeepSeek, others: typically charge only cache hit pricing with no write or storage fee.

See Prompt Caching for the full breakdown.

Price per token generated by the model (received from the API), represented as USD per million Tokens.

Pricing: Blended Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended) · Lower is better

Price per token, shown in USD per million tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio (default 7:2:1 cache-input-output).

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

The blended cache price shown here uses cache hit price only. Other caching costs differ by provider:

  • Anthropic: charges a separate cache write fee, with different rates for 5-minute and 1-hour TTLs (1-hour TTL is more expensive). Blended price charts use Anthropic cache write price for the input leg.
  • Google (Vertex/Gemini): charges a per-hour cache storage fee in addition to cache hit pricing. Some providers also use tiered pricing for prompts above 200K tokens.
  • OpenAI, DeepSeek, others: typically charge only cache hit pricing with no write or storage fee.

See Prompt Caching for the full breakdown.

Figures represent median (P50) measurement over the past 72 hours to reflect sustained changes in performance.

Pricing: Cache Discount

1 - (cache hit price / input price) · Higher is better

Reduction in input token cost due to cache hit relative to input price. Formula: 1 - (Cache Hit Price per Token / Input Token Price), where cache hit price is the first-party cache hit price or the median provider cache hit price. Note that this discount figure does not account for all costs associated with cache hits, such as cache write and storage costs.

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

The blended cache price shown here uses cache hit price only. Other caching costs differ by provider:

  • Anthropic: charges a separate cache write fee, with different rates for 5-minute and 1-hour TTLs (1-hour TTL is more expensive). Blended price charts use Anthropic cache write price for the input leg.
  • Google (Vertex/Gemini): charges a per-hour cache storage fee in addition to cache hit pricing. Some providers also use tiered pricing for prompts above 200K tokens.
  • OpenAI, DeepSeek, others: typically charge only cache hit pricing with no write or storage fee.

See Prompt Caching for the full breakdown.

Figures represent median (P50) measurement over the past 72 hours to reflect sustained changes in performance.

Speed vs. Price

Blended at 7:2:1 (cache-input-output) · Output speed: output tokens per second · USD per 1M tokens (blended)
Most attractive quadrant
Amazon
Anthropic
Azure
Databricks
Google Vertex

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Price per token, shown in USD per million tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio (default 7:2:1 cache-input-output).

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

The blended cache price shown here uses cache hit price only. Other caching costs differ by provider:

  • Anthropic: charges a separate cache write fee, with different rates for 5-minute and 1-hour TTLs (1-hour TTL is more expensive). Blended price charts use Anthropic cache write price for the input leg.
  • Google (Vertex/Gemini): charges a per-hour cache storage fee in addition to cache hit pricing. Some providers also use tiered pricing for prompts above 200K tokens.
  • OpenAI, DeepSeek, others: typically charge only cache hit pricing with no write or storage fee.

See Prompt Caching for the full breakdown.

Figures represent median (P50) measurement over the past 72 hours to reflect sustained changes in performance.

Speed

Measured by Output Speed (tokens per second)

Output Speed

Output tokens per second · Higher is better · 10,000 Input Tokens

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Figures represent median (P50) measurement over the past 72 hours to reflect sustained changes in performance.

Latency vs. Output Speed

Latency: seconds to first token received · Output speed: output tokens per second · 10,000 Input Tokens
Most attractive quadrant
Size represents Price (USD per M Tokens)
Amazon
Anthropic
Azure
Databricks
Google Vertex

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Time to first token received, in seconds, after API request sent. For reasoning models which share reasoning tokens, this will be the first reasoning token. For models which do not support streaming, this represents time to receive the completion.

Price per token, shown in USD per million tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio (default 7:2:1 cache-input-output).

Figures represent median (P50) measurement over the past 72 hours to reflect sustained changes in performance.

Latency

Measured by Time (seconds) to First Token

Time to First Token

Seconds to first token received · Lower is better · 10,000 Input Tokens

Time to first token received, in seconds, after API request sent. For reasoning models which share reasoning tokens, this will be the first reasoning token. For models which do not support streaming, this represents time to receive the completion.

Figures represent median (P50) measurement over the past 72 hours to reflect sustained changes in performance.

End-to-End Response Time

Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed

End-to-End Response Time

Seconds to output 500 tokens, including reasoning model 'thinking' time · Lower is better · 10,000 Input Tokens

Seconds to receive a 500 token response. Key components:

  • Input time: Time to receive the first response token
  • Thinking time (only for reasoning models): Time reasoning models spend outputting tokens to reason prior to providing an answer. Amount of tokens based on the average reasoning tokens across a diverse set of 60 prompts (methodology details).
  • Answer time: Time to generate 500 output tokens, based on output speed

For fair comparison, the number of reasoning tokens is standardized across all providers for each model based on the model's representative query token counts.

Figures represent median (P50) measurement over the past 72 hours to reflect sustained changes in performance.

API Features

Function (Tool) Calling & JSON Mode

ModelsFunction callingJSON Mode
Databricks logoDatabricks
Google Vertex logoGoogle Vertex
Azure logoAzure
Anthropic logoAnthropic
Amazon logoAmazon

Indicates whether the provider supports function calling in their API. Function calling is also known as 'Tool Calling'.

Indicates whether the provider supports JSON mode in their API. When JSON mode is enabled, the models will always return a valid JSON object.

Context Window

Context window: tokens limit · Higher is better

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

While models have their own context window, in cases this is limited by providers.

Summary Table of Key Comparison Metrics

Frequently Asked Questions

Common questions about Claude Opus 4.5 (Non-reasoning) providers

Claude Opus 4.5 (Non-reasoning) is available through 5 API providers: Databricks, Google Vertex, Azure, Anthropic, and Amazon. Each provider offers different performance characteristics and pricing.

Claude Opus 4.5 (Non-reasoning) is currently available through 5 API providers that we benchmark and track.

The fastest providers for Claude Opus 4.5 (Non-reasoning) by output speed are Google Vertex (46.3 t/s), Anthropic (45.8 t/s), and Azure (45.2 t/s). Output speed measures how quickly tokens are generated after the model starts responding.

The providers with the lowest time to first token for Claude Opus 4.5 (Non-reasoning) are Google Vertex (0.87s), Anthropic (1.67s), and Azure (1.73s). Lower latency means faster initial response time.

The most affordable providers for Claude Opus 4.5 (Non-reasoning) by blended price are Google Vertex ($4.10 per 1M tokens), Anthropic ($4.10 per 1M tokens), and Amazon ($4.10 per 1M tokens). Blended price uses a 7:2:1 cache hit/input/output token ratio.

The providers with the lowest input token pricing for Claude Opus 4.5 (Non-reasoning) are Databricks ($5.00 per 1M input tokens), Azure ($5.00 per 1M input tokens), and Google Vertex ($6.25 per 1M input tokens).

The providers with the lowest output token pricing for Claude Opus 4.5 (Non-reasoning) are Databricks ($25.00 per 1M output tokens), Google Vertex ($25.00 per 1M output tokens), and Azure ($25.00 per 1M output tokens).

Prices for Claude Opus 4.5 (Non-reasoning) vary up to 1.7x across providers. The most affordable is Google Vertex at $4.10 per 1M tokens, while Databricks charges $7.00 per 1M tokens.

2 of 5 providers support JSON mode for Claude Opus 4.5 (Non-reasoning): Google Vertex and Anthropic.

All 5 providers of Claude Opus 4.5 (Non-reasoning) support function calling (tool use).

Google Vertex leads across all key metrics for Claude Opus 4.5 (Non-reasoning), offering the fastest speed, lowest latency, and most competitive pricing.

When choosing a provider for Claude Opus 4.5 (Non-reasoning), consider: output speed (for throughput-intensive tasks), latency (for interactive applications requiring quick first responses), pricing (for cost-sensitive workloads), and API features like JSON mode or function calling.

Yes, provider performance can vary over time due to infrastructure changes, load balancing, and updates. We continuously benchmark all providers and display historical performance trends in the "Over Time" charts.

For information about Claude Opus 4.5 (Non-reasoning)'s intelligence, capabilities, modalities, and how it compares to other models, see the model overview page. View model overview