Back to Audit
OPTERA LABS

GPT-5.6 Sol VS Claude 3 Opus

2026 Cost & Performance Comparison
Model A · OpenAI

GPT-5.6 Sol

gpt-5-6-sol

Intelligence Score99%
Cost / 1M Tokens$12.50

70% in · 30% out mix

Value Index(score÷cost)
7.9

Higher = better value

Speed

70/100

Context

1.1M

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

GPT-5.6 Sol vs Claude 3 Opus: Detailed Comparison

GPT-5.6 Sol is OpenAI's flagship-tier language model with a 1.1M-token context window, excelling at reasoning. Claude 3 Opus from Anthropic is a flagship-tier model supporting 200K tokens in context, with standout performance in reasoning.

GPT-5.6 Sol is both the cheaper and the stronger model here — it costs 62% less than Claude 3 Opus on a typical prompt/completion mix and still leads on combined coding and reasoning by 26 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. GPT-5.6 Sol is priced at $5.00/M input tokens and $30.00/M output tokens. Claude 3 Opus costs $15.00/M input and $75.00/M output.

In independent benchmark evaluations, GPT-5.6 Sol leads with coding scores of 97/100 and reasoning scores of 99/100, 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 GPT-5.6 Sol and Claude 3 Opus stack up head to head:

coding
97
80
reasoning
99
90
data extraction
95
85
creative tasks
96
89
vision/multimodal
96
87

Best model by task

  • coding: GPT-5.6 Sol wins with 97/100
  • reasoning: GPT-5.6 Sol wins with 99/100
  • data extraction: GPT-5.6 Sol wins with 95/100
  • creative tasks: GPT-5.6 Sol wins with 96/100
  • vision/multimodal: GPT-5.6 Sol wins with 96/100

Estimated monthly cost at scale

At 10M + 2M per month, GPT-5.6 Sol runs about $110.00 while Claude 3 Opus runs about $300.00 — GPT-5.6 Sol saves roughly $190.00 (63%) every month.

What actually decides it

GPT-5.6 Sol and Claude 3 Opus come from different labs, which means different tokenizers, different API shapes, and a second vendor relationship. The same English text does not produce the same token count on both, so a price-per-million comparison understates the difference — measure your own prompts on each before treating the headline rates as the full story.

GPT-5.6 Sol and Claude 3 Opus are 28 months apart, which is more than one generation in this market. Benchmark comparisons across that gap flatter the older model: it was measured against the evaluations that existed at the time. Treat Claude 3 Opus's scores as a floor for what it does well and be sceptical of a close-looking result.

The context gap is the largest single difference on this pair: GPT-5.6 Sol takes 1.1M tokens against 200K for Claude 3 Opus, roughly 5.3x. 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.

Latency separates them: GPT-5.6 Sol scores 70/100 against 50/100 for Claude 3 Opus, a 20-point gap. That matters for anything a person waits on — chat, autocomplete, interactive tools. For batch and background work it does not, and trading latency for capability there is usually the right call.

One practical asymmetry: GPT-5.6 Sol 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.

GPT-5.6 Sol 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

CategoryGPT-5.6 SolClaude 3Winner

Coding

97
80
A

Reasoning

99
90
A

Extraction

95
85
A

Creative

96
89
A

Vision

96
87
A
GPT-5.6 Sol: 5 wins
Claude 3 Opus: 0 wins
GPT-5.6 Sol leads overall

Speed Score

70/100vs50/100
GPT-5.6Claude

Context Window

1050Kvs200K
GPT-5.6Claude

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
GPT-5.6 Sol
$2.00
Claude 3 Opus
$6.48

Business email

One typical email (~200 words)

~270 tokens
GPT-5.6 Sol
$135.00
Claude 3 Opus
$437.40

Code file

50-line Python script

~400 tokens
GPT-5.6 Sol
$200.00
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 GPT-5.6 Sol 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

GPT-5.6 Sol

$375.00/mo

$4,500.00/yr

$5/M in$30/M out

Claude 3 Opus

$990.00/mo

$11,880.00/yr

$15/M in$75/M out

Annual Savings

$7,380.00 saved per year

GPT-5.6 Sol cheaper · $615.00/mo

Deep-Dive AuditGPT-5.6 Sol & Claude 3 Opus

SURGICAL AUDIT LAB5FD86E79

Surgically Auditing: Deep Logic

Leakage Detected

3-YEAR STRATEGIC LOSS PROJECTION

$1,171.404

Without optimization protocols, current model choices will result in $390.468 capital loss per year.

EFFICIENCY SCORE

99%

Deep Logic

This model achieves a 99 benchmark score in this category.

CATEGORY GAP

1 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

%93

Operational Prescription

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

COST AUDIT PROTOCOL

Overkill Detected

"GPT-5.6 Sol 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 $32.54/month."

3-Tier Intelligent Routing Architecture

93% 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 $4,685.616/year in avoidable overhead.

Deep LogicModel 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 SolSELECTED
99/100
$5.00$30.00$420.00
8/100
Claude Opus 5
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

Related Comparisons

Explore similar model pairs to find your best fit