Quick answer: Claude 3 Opus (released March 4, 2024,
claude-3-opus-20240229) was Anthropic's most capable model at launch — the first Claude to post near-human performance on graduate-level reasoning (GPQA), surpass GPT-4 Turbo on most benchmarks, and achieve near-perfect needle-in-a-haystack recall at 200K tokens. At $15/$75 per million tokens, it remains the reference point for understanding how far the field has moved since early 2024.
Where Claude 3 Opus leads
Where it lags
Best for: historical comparisons, regression baselines, and teams that need to understand what "state of the art in early 2024" looked like.
Claude 3 Opus was the flagship of Anthropic's Claude 3 family, released March 4, 2024 alongside Claude 3 Sonnet and Claude 3 Haiku. At launch it topped most published benchmarks for commercial models: 86.8% MMLU, 50.4% GPQA Diamond, and 60.1% MATH — all state of the art at the time. Anthropic's internal agentic coding evaluation had it solving 38% of tasks, which was the highest reported number before Claude 3.5 Sonnet raised the bar to 64% just three months later.
Its defining quality at release was a twofold improvement in factual accuracy over Claude 2.1 on difficult open-ended questions, and near-perfect (>99%) accuracy on the needle-in-a-haystack recall test at 200K tokens. The model also demonstrated what Anthropic described as "metacognition": in some cases, Opus recognised when a needle sentence had been artificially inserted into context rather than treating it as genuine source material.
From a Benchgen perspective, Claude 3 Opus is a 2024 baseline. Teams running benchmarks in early 2024 generated a lot of trajectory data against this model. Comparing those results to current-generation models using Benchgen's evaluation dimensions provides a concrete, quantified view of how much agent reliability has improved.
| Field | Value |
|---|---|
| Organization | Anthropic |
| API identifier | claude-3-opus-20240229 |
| Context window | 200,000 tokens |
| Max output | 4,096 tokens |
| License | Proprietary |
| Release date | March 4, 2024 |
| Knowledge cutoff | August 2023 |
| Modality | Multimodal (text and vision) |
| Input (per 1M tokens) | Output (per 1M tokens) | |
|---|---|---|
| Anthropic | $15.00 | $75.00 |
Prompt caching reduces input costs by up to 90%. Source: Anthropic pricing page.
Claude 3 Opus has a 200,000-token context window — roughly 300 pages of text — with a maximum output of 4,096 tokens. The 4,096-token output cap is significantly lower than later models (Claude 3.5 Sonnet outputs up to 8,192; Opus 4.6 up to 128K). This limits its usefulness for tasks requiring long generated responses.
| Benchmark | Score | Source | Date |
|---|---|---|---|
| MMLU | 86.8% | Anthropic — Introducing the next generation of Claude | 2024-03 |
| GPQA Diamond | 50.4% | Anthropic — Introducing the next generation of Claude | 2024-03 |
| HumanEval | 84.9% | Anthropic — Introducing the next generation of Claude | 2024-03 |
| MATH | 60.1% | Anthropic — Introducing the next generation of Claude | 2024-03 |
| GSM8K | 95.0% | Anthropic — Introducing the next generation of Claude | 2024-03 |
Scores are reported by Anthropic and shown for context. They are not Benchgen measurements.
| Model | Context | MMLU | GPQA Diamond | Price (in/out per 1M) |
|---|---|---|---|---|
| Claude 3 Opus | 200K | 86.8% | 50.4% | $15 / $75 |
| Claude 3.5 Sonnet | 200K | 88.7% | 65.0% | $3 / $15 |
| GPT-4o | 128K | 88.7% | 53.6% | $2.50 / $10 |
Claude 3.5 Sonnet outperforms Claude 3 Opus on every benchmark listed above while costing 5× less. There is no current production use case where Claude 3 Opus is the optimal choice over its successors. (Rival scores from respective provider announcements; not Benchgen measurements.)
Claude 3 Opus was the first Claude model Anthropic ran through internal agentic coding evaluations: 38% task completion, at the time a high-water mark. That number was rapidly eclipsed — Claude 3.5 Sonnet hit 49% SWE-bench Verified just months later — but it established the evaluation methodology that Anthropic and the broader industry have refined since.
For Benchgen users, Claude 3 Opus trajectory data collected in early 2024 is valuable historical material. Running the same evaluation harness against it today and comparing to current models is one of the cleanest ways to quantify capability progress. Expect Tool-Call Accuracy and Goal Completion scores noticeably below what Sonnet 4 or Opus 4 achieve on the same tasks.
from anthropic import Anthropic
client = Anthropic(api_key="YOUR_API_KEY")
message = client.messages.create(
model="claude-3-opus-20240229",
max_tokens=1024,
messages=[{"role": "user", "content": "Analyse the technical risks in this architecture doc..."}],
)
print(message.content[0].text)Specs and scores sourced from Anthropic's Claude 3 family announcement. Third-party benchmark scores attributed inline. Last updated 2026-06-19.
Claude 3 Opus is a large language model developed by Anthropic.
This model isn’t on any benchmark leaderboard yet.