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OPTERA LABS

Claude Opus 5 VS Claude 3 Opus

2026 Cost & Performance Comparison
Model A · Anthropic

Claude Opus 5

claude-opus-5

Intelligence Score98%
Cost / 1M Tokens$11.00

70% in · 30% out mix

Value Index(score÷cost)
8.9

Higher = better value

Speed

63/100

Context

1.0M

Tier

power

Model B · Anthropic

Claude 3 Opus

claude-3-opus

Intelligence Score90%
Cost / 1M Tokens$33.00

70% in · 30% out mix

Value Index(score÷cost)
2.7

Higher = better value

Speed

50/100

Context

200K

Tier

power

IN-DEPTH ANALYSIS

Claude Opus 5 vs Claude 3 Opus: Detailed Comparison

Claude Opus 5 is Anthropic's flagship-tier language model with a 1.0M-token context window, excelling at coding. Claude 3 Opus from Anthropic is a flagship-tier model supporting 200K tokens in context, with standout performance in reasoning.

Claude Opus 5 is both the cheaper and the stronger model here — it costs 67% less than Claude 3 Opus on a typical prompt/completion mix and still leads on combined coding and reasoning by 27 points. There is no tradeoff to weigh on this pair: unless you need something specific from Claude 3 Opus, the cheaper model is simply the better one. Claude Opus 5 is priced at $5.00/M input tokens and $25.00/M output tokens. Claude 3 Opus costs $15.00/M input and $75.00/M output.

In independent benchmark evaluations, Claude Opus 5 leads with coding scores of 99/100 and reasoning scores of 98/100, compared to Claude 3 Opus's 80/100 in coding and 90/100 in reasoning.

Capability breakdown

Across the five core benchmark categories, here is how Claude Opus 5 and Claude 3 Opus stack up head to head:

coding
99
80
reasoning
98
90
data extraction
96
85
creative tasks
96
89
vision/multimodal
95
87

Best model by task

  • coding: Claude Opus 5 wins with 99/100
  • reasoning: Claude Opus 5 wins with 98/100
  • data extraction: Claude Opus 5 wins with 96/100
  • creative tasks: Claude Opus 5 wins with 96/100
  • vision/multimodal: Claude Opus 5 wins with 95/100

Estimated monthly cost at scale

At 10M + 2M per month, Claude Opus 5 runs about $100.00 while Claude 3 Opus runs about $300.00 — Claude Opus 5 saves roughly $200.00 (67%) every month.

What actually decides it

Both models come from Anthropic, so they share a tokenizer, an API surface, and a billing account. Switching between them is a model-string change and nothing else — no new SDK, no re-tokenizing your prompts to re-estimate cost, no second vendor to onboard. That makes routing between them far cheaper to implement than a cross-vendor split.

These are the same lab's model at the same tier, 28 months apart — so this is an upgrade question, not a choice between alternatives. Claude Opus 5 is the current entry; Claude 3 Opus is here because plenty of production traffic still runs on it. If you are starting something new there is little reason to pick the older one, and if you are already on it the question is whether the migration cost is worth the gain.

The context gap is the largest single difference on this pair: Claude Opus 5 takes 1.0M tokens against 200K for Claude 3 Opus, roughly 5.0x. That is the difference between feeding in a whole repository or a full contract set and having to chunk it. If your work involves documents you cannot split cleanly, this decides it on its own.

Throughput is close enough to ignore — 63/100 versus 50/100. Neither model will feel noticeably quicker in an interactive product, so latency is not a reason to choose between them.

One practical asymmetry: Claude Opus 5 offers a batch API at 50% off standard rates, and Claude 3 Opus does not. For anything that does not need an answer immediately — nightly enrichment, backfills, evaluation runs — that discount can be worth more than the difference in list price, and it is easy to overlook when comparing headline rates.

Claude Opus 5 wins this comparison outright — cheaper and stronger. Choose Claude 3 Opus only if it has a specific capability you need; on price and benchmarks it is behind on both.

Benchmark Comparison

Head-to-head scores across 5 categories — sourced from official evals

CategoryClaude OpusClaude 3Winner

Coding

99
80
A

Reasoning

98
90
A

Extraction

96
85
A

Creative

96
89
A

Vision

95
87
A
Claude Opus 5: 5 wins
Claude 3 Opus: 0 wins
Claude Opus 5 leads overall

Speed Score

63/100vs50/100
ClaudeClaude

Context Window

1000Kvs200K
ClaudeClaude

What Is a Token?

Models don't read words — they process tokens.

A token is roughly 4 characters of English text (~¾ of a word). Your API bill is priced per million tokens — understanding this directly reduces your costs.

Short phrase

"Hello, world!"

4 tokens
Claude Opus 5
$2.20
Claude 3 Opus
$6.48

Business email

One typical email (~200 words)

~270 tokens
Claude Opus 5
$148.50
Claude 3 Opus
$437.40

Code file

50-line Python script

~400 tokens
Claude Opus 5
$220.00
Claude 3 Opus
$648.00

Prices shown are for 100,000 runs of each workload — one run costs a fraction of a cent on both Claude Opus 5 and Claude 3 Opus, so the number only becomes meaningful at production volume. Input tokens only; add your output volume in the calculator below.

How to check your token usage

response.usage.total_tokens

Every API response includes a usage object. Sum total_tokens across all calls to get your monthly figure, then use the calculator below.

Your Cost Calculator

Enter your actual monthly token usage to see real savings

Quick Presets

30.0M TOKENS
Prompt 70%Completion 30%
CHEAPER

Claude Opus 5

$330.00/mo

$3,960.00/yr

$5/M in$25/M out

Claude 3 Opus

$990.00/mo

$11,880.00/yr

$15/M in$75/M out

Annual Savings

$7,920.00 saved per year

Claude Opus 5 cheaper · $660.00/mo

Deep-Dive Audit — Claude Opus 5 & Claude 3 Opus

SURGICAL AUDIT LAB19F3CC69

Surgically Auditing: Deep Logic

Leakage Detected

3-YEAR STRATEGIC LOSS PROJECTION

$991.404

Without optimization protocols, current model choices will result in $330.468 capital loss per year.

EFFICIENCY SCORE

98%

Deep Logic

This model achieves a 98 benchmark score in this category.

CATEGORY GAP

2 pts

Distance from Leader

Competitive Landscape Analysis

Source: MMLU-Pro + GPQA Diamond (Apr 2026)

Category Champion: Claude Fable 5

According to MMLU-Pro + GPQA Diamond (Apr 2026) data, Claude Fable 5 provides the optimum balance for Deep Logic tasks.

Market Score

%100

Savings Rate

%92

Operational Prescription

  • Implement model cascading to optimize token spend.
  • Analyze complex_reasoning data to leverage local semantic caching.

COST AUDIT PROTOCOL

Overkill Detected

"Claude Opus 5 is overpriced for this task type. Claude Fable 5 scores 100 in this category at a fraction of the cost."

Categorical Alternative Opportunity

"Claude Fable 5 leads this category with 100 points according to MMLU-Pro + GPQA Diamond (Apr 2026) data."

Inertia Tax Detected

"85% of traffic can be routed to cheaper models. Fast tier (GPT-5 Nano) and Smart tier (o3-mini) can save $27.54/month."

3-Tier Intelligent Routing Architecture

92% SAVINGS VIA ROUTING
Fast Tier
50%

GPT-5 Nano

IQ Score: 72/100

$18.00/yr

Smart Tier
35%

o3-mini

IQ Score: 97/100

$277.20/yr

Power Tier
15%

DeepSeek R1

IQ Score: 97/100

$59.184/yr

Fast Tier 50%Smart Tier 35%Power Tier 15%

Without tiered routing, you pay the 'Inertia Tax' — routing all traffic to the most expensive model regardless of task complexity. Tiered cascade eliminates $3,965.616/year in avoidable overhead.

Deep Logic — Model Cost / Quality Matrix

Source: MMLU-Pro + GPQA Diamond (Apr 2026)
ModelBenchmarkInput (per M)Output (per M)Annual Cost*Value Index
Claude Fable 5LEADER
100/100
$10.00$50.00$720.00
5/100
GPT-5.6 Sol
99/100
$5.00$30.00$420.00
8/100
Claude Opus 5SELECTED
98/100
$5.00$25.00$360.00
9/100
Claude Opus 4.6
98/100
$5.00$25.00$360.00
9/100
DeepSeek R1BEST VALUE
97/100
$0.55$2.19$32.88
100/100
Claude Opus 4.8
96/100
$5.00$25.00$360.00
9/100
Claude 3 Opus
90/100
$15.00$75.00$1,080.00
3/100
Llama 3.1 405B
88/100
$2.70$2.70$64.80
46/100

* Annual cost for given volumes. Value Index = Score / Cost (Higher = Best Value).

Tactical Code Gen
// iOPTERA Surgical Routing Wrapper
const auditModel = async (prompt: string) => {
  const complexity = measureComplexity(prompt);
  
  // Tactical Cascade Logic
  if (complexity < 0.45) {
    // Redirect simple tasks to efficient model
    return await llm.call("iOPTERA Optimization", prompt); 
  }
  
  // High-latency routing for complex reasoning
  return await llm.call("Claude Fable 5", prompt);
};
READY TO DEPLOY IN Vercel Edge OR AWS Lambda

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