| Signal | GPT-5.2 | Delta | o3 Deep Research |
|---|---|---|---|
Capabilities | 100 | -- | |
Benchmarks | 89 | +1 | |
Pricing | 14 | -26 | |
Context window size | 89 | +5 | |
Recency | 100 | -- | |
Output Capacity | 85 | +2 | |
| Overall Result | 3 wins | of 6 | 1 wins |
16
days higher
3
days
11
days higher
OpenAI
OpenAI
GPT-5.2 saves you $2125.00/month
That's $25500.00/year compared to o3 Deep Research at your current usage level of 100K calls/month.
| Metric | GPT-5.2 | o3 Deep Research | Winner |
|---|---|---|---|
| Overall Score | 90 | 88 | GPT-5.2 |
| Rank | #4 | #6 | GPT-5.2 |
| Quality Rank | #4 | #6 | GPT-5.2 |
| Adoption Rank | #4 | #6 | GPT-5.2 |
| Parameters | -- | -- | -- |
| Context Window | 400K | 200K | GPT-5.2 |
| Pricing | $1.75/$14.00/M | $10.00/$40.00/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 100 | GPT-5.2 |
| Benchmarks | 89 | 88 | GPT-5.2 |
| Pricing | 14 | 40 | o3 Deep Research |
| Context window size | 89 | 84 | GPT-5.2 |
| Recency | 100 | 100 | GPT-5.2 |
| Output Capacity | 85 | 83 | GPT-5.2 |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Here's what the scores mean for these two models:
Scores 90/100 (rank #4), placing it in the top 99% of all 290 models tracked.
Scores 88/100 (rank #6), placing it in the top 98% of all 290 models tracked.
With only a 2-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
GPT-5.2 offers 69% better value per quality point. At 1M tokens/day, you'd spend $236.25/month with GPT-5.2 vs $750.00/month with o3 Deep Research - a $513.75 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. GPT-5.2 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($14.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (90/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
GPT-5.2 and o3 Deep Research are extremely close in overall performance (only 1.5 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-5.2
Marginally better benchmark scores; both are excellent
Best for Cost
GPT-5.2
69% lower pricing; better value at scale
Best for Reliability
GPT-5.2
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.2
Stronger community support and better developer experience
Best for Production
GPT-5.2
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.2 | o3 Deep Research |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
OpenAI
GPT-5.2 saves you $46.05/month
That's 70% cheaper than o3 Deep Research at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | GPT-5.2 | o3 Deep Research |
|---|---|---|
| Context Window | 400K | 200K |
| Max Output Tokens | 128,000 | 100,000 |
| Open Source | No | No |
| Created | Dec 10, 2025 | Oct 10, 2025 |
GPT-5.2 scores 90/100 (rank #4) compared to o3 Deep Research's 88/100 (rank #6), giving it a 2-point advantage. GPT-5.2 is the stronger overall choice, though o3 Deep Research may excel in specific areas like certain benchmarks.
GPT-5.2 is ranked #4 and o3 Deep Research is ranked #6 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
GPT-5.2 is cheaper at $14.00/M output tokens vs o3 Deep Research's $40.00/M output tokens - 2.9x more expensive. Input token pricing: GPT-5.2 at $1.75/M vs o3 Deep Research at $10.00/M.
GPT-5.2 has a larger context window of 400,000 tokens compared to o3 Deep Research's 200,000 tokens. A larger context window means the model can process longer documents and conversations.