GPT-5.2 Chat
gpt-5-2
70% in · 30% out mix
Higher = better value
Speed
85/100
Context
256K
Tier
smart
Claude 3.5 Sonnet
claude-3-5-sonnet
70% in · 30% out mix
Higher = better value
Speed
95/100
Context
200K
Tier
smart
IN-DEPTH ANALYSIS
GPT-5.2 Chat vs Claude 3.5 Sonnet: Detailed Comparison
GPT-5.2 Chat is OpenAI's mid-range-tier language model with a 256K-token context window, excelling at reasoning. Claude 3.5 Sonnet from Anthropic is a mid-range-tier model supporting 200K tokens in context, with standout performance in coding.
GPT-5.2 Chat is both the cheaper and the stronger model here — it costs 18% less than Claude 3.5 Sonnet on a typical prompt/completion mix and still leads on combined coding and reasoning by 1 points. There is no tradeoff to weigh on this pair: unless you need something specific from Claude 3.5 Sonnet, the cheaper model is simply the better one. GPT-5.2 Chat is priced at $1.75/M input tokens and $14.00/M output tokens. Claude 3.5 Sonnet costs $3.00/M input and $15.00/M output.
In independent benchmark evaluations, GPT-5.2 Chat leads with coding scores of 94/100 and reasoning scores of 96/100, compared to Claude 3.5 Sonnet's 96/100 in coding and 93/100 in reasoning.
Capability breakdown
Across the five core benchmark categories, here is how GPT-5.2 Chat and Claude 3.5 Sonnet stack up head to head:
Best model by task
- coding: Claude 3.5 Sonnet wins with 96/100
- reasoning: GPT-5.2 Chat wins with 96/100
- data extraction: GPT-5.2 Chat wins with 91/100
- creative tasks: GPT-5.2 Chat wins with 95/100
- vision/multimodal: GPT-5.2 Chat wins with 92/100
Estimated monthly cost at scale
At 10M + 2M per month, GPT-5.2 Chat runs about $45.50 while Claude 3.5 Sonnet runs about $60.00 — GPT-5.2 Chat saves roughly $14.50 (24%) every month.
What actually decides it
GPT-5.2 Chat and Claude 3.5 Sonnet 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-5.2 Chat and Claude 3.5 Sonnet are 19 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 3.5 Sonnet's scores as a floor for what it does well and be sceptical of a close-looking result.
Context is effectively a tie: 256K against 200K. Neither model unlocks a document size the other cannot handle, so this axis should not enter the decision. If you were hoping context would break the tie for you, it will not.
Throughput is close enough to ignore — 95/100 versus 85/100. Neither model will feel noticeably quicker in an interactive product, so latency is not a reason to choose between them.
GPT-5.2 Chat wins this comparison outright — cheaper and stronger. Choose Claude 3.5 Sonnet 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
Coding
Reasoning
Extraction
Creative
Vision
Speed Score
Context Window
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!"
- GPT-5.2 Chat
- $0.70
- Claude 3.5 Sonnet
- $1.26
Business email
One typical email (~200 words)
- GPT-5.2 Chat
- $47.25
- Claude 3.5 Sonnet
- $85.05
Code file
50-line Python script
- GPT-5.2 Chat
- $70.00
- Claude 3.5 Sonnet
- $126.00
Prices shown are for 100,000 runs of each workload — one run costs a fraction of a cent on both GPT-5.2 Chat and Claude 3.5 Sonnet, 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_tokensEvery 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
GPT-5.2 Chat
$162.75/mo
$1,953.00/yr
Claude 3.5 Sonnet
$198.00/mo
$2,376.00/yr
Annual Savings
$423.00 saved per year
GPT-5.2 Chat cheaper · $35.25/mo
Deep-Dive Audit — GPT-5.2 Chat & Claude 3.5 Sonnet
Surgically Auditing: Deep Logic
3-YEAR STRATEGIC LOSS PROJECTION
$478.404
Without optimization protocols, current model choices will result in $159.468 capital loss per year.
EFFICIENCY SCORE
96%
This model achieves a 96 benchmark score in this category.
CATEGORY GAP
4 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
%84
Operational Prescription
- Implement model cascading to optimize token spend.
- Analyze complex_reasoning data to leverage local semantic caching.
COST AUDIT PROTOCOL
Overkill Detected
"GPT-5.2 Chat 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 $13.29/month."
3-Tier Intelligent Routing Architecture
84% SAVINGS VIA ROUTINGGPT-5 Nano
IQ Score: 72/100
$18.00/yr
o3-mini
IQ Score: 97/100
$277.20/yr
DeepSeek R1
IQ Score: 97/100
$59.184/yr
Without tiered routing, you pay the 'Inertia Tax' — routing all traffic to the most expensive model regardless of task complexity. Tiered cascade eliminates $1,913.616/year in avoidable overhead.
Deep Logic — Model Cost / Quality Matrix
Source: MMLU-Pro + GPQA Diamond (Apr 2026)| Model | Benchmark | Input (per M) | Output (per M) | Annual Cost* | Value Index |
|---|---|---|---|---|---|
o3-miniBEST VALUE | 97/100 | $1.10 | $4.40 | $66.00 | 100/100 |
GPT-5.2 ChatSELECTED | 96/100 | $1.75 | $14.00 | $189.00 | 35/100 |
Claude 3.7 Sonnet | 95/100 | $3.00 | $15.00 | $216.00 | 30/100 |
GPT-5.6 Terra | 94/100 | $2.00 | $12.00 | $168.00 | 38/100 |
Claude 3.5 Sonnet | 93/100 | $3.00 | $15.00 | $216.00 | 29/100 |
GPT-4.1 | 93/100 | $2.00 | $8.00 | $120.00 | 53/100 |
Claude Sonnet 5 | 92/100 | $3.00 | $15.00 | $216.00 | 29/100 |
Grok 4.5 | 90/100 | $2.00 | $6.00 | $96.00 | 64/100 |
GPT-4o | 90/100 | $2.50 | $10.00 | $150.00 | 41/100 |
Gemini 3.1 Pro | 89/100 | $2.00 | $12.00 | $168.00 | 36/100 |
Gemini 2.0 Pro | 88/100 | $1.25 | $5.00 | $75.00 | 80/100 |
Gemini 1.5 Pro | 87/100 | $1.25 | $5.00 | $75.00 | 79/100 |
Mistral Large 2 | 86/100 | $2.00 | $6.00 | $96.00 | 61/100 |
* Annual cost for given volumes. Value Index = Score / Cost (Higher = Best Value).
// 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);
};Related Comparisons
Explore similar model pairs to find your best fit
GPT-5.2 ChatvsGPT-5.6 Sol
$1.75 · $5/M in
GPT-5.2 ChatvsClaude Opus
$1.75 · $5/M in
GPT-5.2 ChatvsGPT-5.6 Terra
$1.75 · $2/M in
GPT-5.2 ChatvsClaude Sonnet
$1.75 · $3/M in
GPT-5.2 ChatvsGrok 4.5
$1.75 · $2/M in
GPT-5.2 ChatvsGemini 3.1
$1.75 · $2/M in
Claude 3.5vsClaude 3
$3 · $15/M in
Claude 3.5vsGPT-5.6 Terra
$3 · $2/M in