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Anthropic: Claude Opus 4.8 (batch): AI model

Context window:
1,000,000 tokens
Input:
$2.5/1M tokens
Output:
$12.5/1M tokens
Type:
text, image
  • Vision
  • Tools
  • Streaming
  • Long context

Thinking levels: max · xhigh · high · medium · low

Anthropic: Claude Opus 4.8 (batch) is a AI model from Anthropic, available through Hormouz via an OpenAI-compatible API with stable access from inside Iran.

Claude Opus 4.8 is Anthropic's most capable generally available model in the Opus family. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token...

Quickstart

curl https://api.hormouz.net/v1/chat/completions \
  -H "Authorization: Bearer ng-YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-opus-4.8:batch",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Specs

VendorAnthropic
TypeText, Image
Context window1,000,000 tokens
Pricing$2.50/M in · $12.50/M out
APIChat Completions
CapabilitiesStreaming · Vision · Tools

Benchmarks

41.8
Intelligence Index
Better than 82% of models we compared
74.3
Coding Index
Better than 89% of models we compared
41.9
Agentic Index
Better than 82% of models we compared

Reasoning

GPQA Diamond
Graduate-level scientific reasoning
92%
HLE
Humanity's Last Exam
48.7%
IFBench
Instruction-following
62.2%
AA-LCR
Long-context reasoning
77.7%
CritPt
Research-level physics reasoning
20.9%
AA Omniscience
Broad factual knowledge accuracy
48.8%
Non-Hallucination
Rate of avoiding fabricated answers
60.7%

Coding

SciCode
Python for scientific computing
54.4%
Terminal-Bench Hard
Agentic coding & terminal use
58.3%

Agentic

τ²-Bench
Tool-use agents in dual-control scenarios
94.4%
GDPval
Economically valuable tasks
47.8%

Source: Artificial Analysis

Design Arena

How Design Arena works ↗

Ranking distribution

First
23,411
Second
18,522
Third
7,793
Fourth
4,342

9913 tournaments ?

Agentic Game Dev
Top 17%
1,238Elo
Win rate: 55.8%
Agentic HTML Slides
Top 33%
1,227Elo
Win rate: 55.6%
Agentic Slides
Top 11%
1,294Elo
Win rate: 64.8%
Agentic Slides (HTML)
Top 33%
1,230Elo
Win rate: 56%
Agentic Slides (Python)
Top 11%
1,310Elo
Win rate: 68.9%
Android Native
Top 22%
1,247Elo
Win rate: 56.4%
Full-Stack
Top 23%
1,248Elo
Win rate: 55.3%
Godot Game Dev
Top 28%
1,231Elo
Win rate: 55.8%
HTML Slides
Top 17%
1,220Elo
Win rate: 58%Avg time: 266s
Mobile Apps
Top 20%
1,223Elo
Win rate: 56%
PPTX Slides
Top 12%
1,306Elo
Win rate: 67.9%
Python Slides
Top 12%
1,298Elo
Win rate: 65.9%Avg time: 403s
Web Apps
Top 31%
1,224Elo
Win rate: 51.4%
3D
Top 28%
1,233Elo
Win rate: 52.1%Avg time: 85.7s
ASCII Art
Top 9%
1,288Elo
Win rate: 62.2%Avg time: 28.3s
Code
Top 23%
1,259Elo
Win rate: 52.8%Avg time: 111s
Data Viz
Top 25%
1,247Elo
Win rate: 53.1%Avg time: 75.1s
Game Dev
Top 18%
1,275Elo
Win rate: 53.2%Avg time: 144s
SVG
Top 27%
1,195Elo
Win rate: 52.1%Avg time: 31.8s
UI Component
Top 24%
1,265Elo
Win rate: 53.6%Avg time: 83.6s
Website
Top 23%
1,263Elo
Win rate: 53.1%Avg time: 115s

Metrics sourced from Design Arena

Code example

cURL
curl https://api.hormouz.net/v1/chat/completions \
  -H "Authorization: Bearer ng-YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-opus-4.8:batch",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'
Python
from openai import OpenAI
client = OpenAI(api_key="ng-YOUR_API_KEY", base_url="https://api.hormouz.net/v1")
response = client.chat.completions.create(
    model="anthropic/claude-opus-4.8:batch",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)
JavaScript
import OpenAI from "openai";
const client = new OpenAI({ apiKey: "ng-YOUR_API_KEY", baseURL: "https://api.hormouz.net/v1" });
const response = await client.chat.completions.create({
  model: "anthropic/claude-opus-4.8:batch",
  messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);

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Updated 2026-10-13