Claude Opus 4.6

Google Vertex AI chat

Claude Opus 4.6 is a Google Vertex AI chat model.It supports a 1,000,000-token context windowwith up to 128,000 output tokens.Input is priced at $5.00/M tokens and output at $25.00/M tokens. Capabilities include function calling, vision, reasoning, prompt caching. Route Claude Opus 4.6 via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: May 12, 2026 View source ↗
Cost calculator

Estimate Claude Opus 4.6 spend

Pick a workload, fine-tune the sliders, and see the monthly bill.

~3K in / ~400 out · 5K req/day
3,000
01,000,000
400
0128,000
5,000
01,000,000
cached @ $0.5000/M
Per request
$0.0250
in $0.0150 · out $0.0100
Per day
$125
5,000 requests
Per month
$3,805
152,188 requests

Estimate uses $5.00/M input · $25.00/M output. Provider pricing changes. Production costs vary with retries, streaming overhead, and tool-call rounds.
Want this for free? Cache + route via Agent Command Center — first 100K requests and 100K cache hits free every month.

Pricing

Per-token rates, expressed in USD per 1M tokens. Verified May 12, 2026.

Input $5.00/M
Output $25.00/M
Cached input $0.500/M

Limits

Context window
1,000,000 tokens
Max input
1,000,000 tokens
Max output
128,000 tokens
Modalities
vision, pdf, text

Capabilities

  • Function calling ✓ supported
  • Parallel tool calls — not advertised
  • Vision input ✓ supported
  • Audio input — not advertised
  • Audio output — not advertised
  • PDF input ✓ supported
  • Streaming ✓ supported
  • Structured output ✓ supported
  • Prompt caching ✓ supported
  • Reasoning ✓ supported

Where it's strong

  • +pricing — cheaper than 93% of priced chat models on Future AGI
  • +long-context tasks — context window in the top 8% of peers
  • +PDF input — only 16% of chat models on Future AGI advertise this
  • +prompt caching — only 23% of chat models on Future AGI advertise this

Watch out for

  • No major caveats flagged from public spec.

Benchmark scores

Reported public benchmark numbers. Each row links to the source.

Chatbot Arena ELOgeneral· overall
Captured May 12, 2026
τ-bench (retail)agent
Captured May 12, 2026
GPQA Diamondreasoning
Captured May 12, 2026
Captured May 12, 2026
SWE-bench Verifiedagent· With a prompt modification
Captured May 12, 2026
MMMU-Promultimodal· without tools
Captured May 12, 2026
ARC-AGI-2reasoning· max effort and a 120k thinking budget
Captured May 12, 2026
Humanity's Last Examreasoning· with tools
Captured May 12, 2026
Try it

Call Claude Opus 4.6 via Agent Command Center

One OpenAI-compatible endpoint. Routing, fallback, semantic caching, guardrails, and cost tracking come along for the ride. First 100K requests + 100K cache hits free every month.

SDK
Native Future AGI client (agentcc / @agentcc/client). Per-call metadata — provider, cost, latency, cache hit, request id — is returned on x-agentcc-* response headers, so any HTTP client can read it.
# Claude Opus 4.6 via the Agent Command Center Python SDK
# pip install agentcc
import os
from agentcc import AgentCC

client = AgentCC(
    api_key=os.environ["AGENTCC_API_KEY"],   # from app.futureagi.com → Settings → API Keys
    base_url="https://gateway.futureagi.com/v1",
)

resp = client.chat.completions.create(
    model="vertex-ai/claude-opus-4-6",
    messages=[{"role": "user", "content": "Hello, Claude Opus 4.6!"}],
)

print(resp.choices[0].message.content)
print(f"Tokens: {resp.usage.total_tokens}")

# Per-call gateway metadata is returned on x-agentcc-* response headers.
# When you need it programmatically, use .with_raw_response to get them:
raw = client.chat.completions.with_raw_response.create(
    model="vertex-ai/claude-opus-4-6",
    messages=[{"role": "user", "content": "Same call, but I want the headers."}],
)
print("Provider:", raw.headers.get("x-agentcc-provider"))
print("Latency:", raw.headers.get("x-agentcc-latency-ms"), "ms")
print("Cost:   ", raw.headers.get("x-agentcc-cost"), "USD")
print("Cache:  ", raw.headers.get("x-agentcc-cache"))
Set AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗
Advanced: fallback + cache config (YAML)
strategy: cost-optimized
targets:
  - model: claude-opus-4-6
    provider: vertex-ai
    weight: 80
fallbacks:
  - model: claude-opus-4-6-20260205
    provider: anthropic
  - model: gemini-3-1-pro-preview
    provider: google
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }

Same model on other providers

claude-opus-4-6 is also available via 2 other routes. Pricing, regions, and capabilities can differ — compare before routing production traffic.

ProviderInput / 1MOutput / 1MVerified
Azure AI Foundry$5.00/M$25.00/MMay 12, 2026
Anthropic$5.00/M$25.00/MMay 12, 2026

Compare with similar models

Grouped by Chatbot Arena tier (Claude Opus 4.6 sits at 1502 ELO).

FAQ

How much does Claude Opus 4.6 cost?

Input is priced at $5.00 per 1M tokens and output at $25.00 per 1M tokens (Google Vertex AI, last verified May 12, 2026).

What is the context window of Claude Opus 4.6?

Claude Opus 4.6 supports a 1,000,000-token context window with up to 128,000 output tokens.

Does Claude Opus 4.6 support function calling?

Yes — Claude Opus 4.6 supports function (tool) calling.

Is Claude Opus 4.6 good for production?

Claude Opus 4.6 is well-suited for pricing — cheaper than 93% of priced chat models on Future AGI and long-context tasks — context window in the top 8% of peers.

How can I route to Claude Opus 4.6 with fallback?

Use Agent Command Center: a single OpenAI-compatible endpoint that supports cost-optimized routing, latency-aware retries, model fallback, and shadow traffic. Configure once, swap models without app changes.

Useful links for Claude Opus 4.6

Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.