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Claude Opus 4.6

Claude Opus 4.6 is the first Opus model with a context window of 1M tokens, introduces adaptive thinking for model-decided reasoning depth, supports interleaved thinking and tool calls in a single response, and delivers equal or better performance than fixed extended thinking across programming, analysis, and creative tasks.

Input and output price
Prices from: Input $5, Output $25, Per 1M tokens
24h uptime
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import { streamText } from 'ai'
const result = streamText({
model: 'anthropic/claude-opus-4.6',
prompt: 'Why is the sky blue?',
providerOptions: {
anthropic: {
speed: 'fast',
},
gateway: {
only: ['anthropic'],
},
},
})
Read docs

Copy link to headingProviders

Route requests across multiple providers. Copy a provider slug to set your preference. Visit the docs for more info. Using a provider means you agree to their terms, listed under Legal.

Provider
Context
Max Output
Latency
Throughput
Input
Output
Cache
Web Search
Capabilities
ZDR
No Training
Regional Inference
Free Tier
Release Date
1M128K1.6 s44 tps
$5/M+2 more
$25/M+2 more
Read$0.50/M
Write$6.25/M
$10/K
+3
US
02/05/2026
1M128K1.2 s46 tps
$5/M+2 more
$25/M+2 more
Read$0.50/M
Write$6.25/M
+3
US
EU
02/05/2026
1M128K1.8 s53 tps
$5/M+2 more
$25/M+2 more
Read$0.50/M
Write$6.25/M
$10/K
+3
US
EU
02/05/2026

Copy link to headingPlayground

Try out Claude Opus 4.6 by Anthropic. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days.

anthropic logo
anthropic logo

Claude Opus 4.6

Copy link to headingUptime

Direct request success rate on AI Gateway and per-provider. Visit the docs for more info.

Copy link to headingThroughput

P50 throughput on live AI Gateway traffic, in tokens per second (TPS). Visit the docs for more info.

Copy link to headingLatency

P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds. View the docs for more info.

Copy link to headingMore models by Anthropic

Model
Context
Latency
Throughput
Input
Output
Cache
Web Search
Capabilities
Providers
ZDR
No Training
Free Tier
Release Date
1M2.0 s83 tps
$10/M
$50/M
Read$0.25/M
Write$12.50/M
$10/K
+2
anthropic logo
bedrock logo
vertexAnthropic logo
08/31/2026
1M1.4 s135 tps
$5/M+1 more
$25/M+1 more
Read$0.50/M
Write$6.25/M
$10/K
+3
anthropic logo
bedrock logo
claudeaws logo
+1
07/24/2026
1M1.4 s114 tps
$2/M
$10/M
Read$0.20/M
Write$2.50/M
$10/K
+3
anthropic logo
bedrock logo
claudeaws logo
+1
06/29/2026
1M1.0 s105 tps
$5/M+1 more
$25/M+1 more
Read$0.50/M
Write$6.25/M
$10/K
+3
anthropic logo
bedrock logo
claudeaws logo
+1
05/28/2026
1M1.0 s66 tps
$3/M
$15/M
Read$0.30/M
Write$3.75/M
$10/K
+3
anthropic logo
bedrock logo
claudeaws logo
+1
02/17/2026
200K0.5 s116 tps
$1/M
$5/M
Read$0.10/M
Write$1.25/M
$10/K
+3
anthropic logo
bedrock logo
claudeaws logo
+1
10/15/2025

Copy link to headingAbout Claude Opus 4.6

Claude Opus 4.6 launched on AI Gateway on February 5, 2026, bringing two advances to the Opus tier. First, the context window of 1M tokens. This is the first time an Opus model supports this context size, matching what Sonnet 4.5 gained. For teams needing both Opus-level intelligence and large context capacity, this closes a capability gap.

Second, adaptive thinking: a new thinking type parameter (set as thinking: { type: 'adaptive' }) that lets the model decide when and how much to reason, rather than requiring you to specify a fixed thinking budget. Claude Opus 4.6 also supports interleaved thinking and tool calls within a single response. The model can reason, call a tool, reason further about the result, and call another tool, all in one response rather than requiring separate turns. This applies to complex agentic workflows where the best next tool call depends on reasoning about previous results.

Anthropic described Claude Opus 4.6 as built to power agents that handle real-world work, with strength across the development lifecycle. To use Claude Opus 4.6, set the model to anthropic/claude-opus-4.6 in the AI SDK, Chat Completions API, Responses API, Messages API, or other API formats, from TypeScript or Python. When using the AI SDK, configure providerOptions.anthropic with the thinking and effort parameters as needed.

Copy link to headingWhat To Consider When Choosing a Provider

  • Configuration: Requests using the context window of 1M tokens generate higher per-request token volumes than typical API calls. AI Gateway cost tracking per request is useful for budgeting large-context workloads.
  • Zero Data Retention: Zero Data Retention is available for this model. It is offered on a per-provider and model basis. See the documentation for details.
  • Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.

Copy link to headingWhen to Use Claude Opus 4.6

Best for

  • Opus intelligence at large context: Entire large codebases, extensive document sets, or long conversation histories where prior Opus models hit context limits
  • Interleaved reasoning and tool use: Complex multi-step pipelines where reasoning about tool results before the next call improves outcomes
  • Adaptive thinking efficiency: Letting the model calibrate its own reasoning depth avoids over-spending thinking tokens on simpler requests in mixed workloads
  • Programming, analysis, and creative tasks: At Opus depth, Claude Opus 4.6 excels across all three categories
  • Development lifecycle agents: The announced strength area for this checkpoint

Consider alternatives when

  • Primary cost constraint: Sonnet 4.6 approaches Opus-level intelligence at lower cost per token
  • Smaller context sufficient: Earlier Opus versions handle workloads that don't need the context window of 1M tokens
  • Maximum speed required: Sonnet and Haiku variants serve latency-sensitive use cases better

Claude Opus 4.6 closes the context window gap between the Opus and Sonnet tiers while introducing adaptive thinking, a more efficient approach to reasoning that performs on par with or better than fixed thinking budgets. For teams that need Opus-level intelligence at large context scale, this is the model.

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