| Signal | GPT-5.2 | Delta | GPT-5.2-Codex |
|---|---|---|---|
Capabilities | 100 | -- | |
Benchmarks | 89 | -- | |
Pricing | 86 | -- | |
Context window size | 89 | -- | |
Recency | 100 | -- | |
Output Capacity | 85 | -- | |
| Overall Result | 0 wins | of 6 | 0 wins |
Score History
90.5
current score
Tied
right now
90.5
current score
OpenAI
OpenAI
| Metric | GPT-5.2 | GPT-5.2-Codex | Winner |
|---|---|---|---|
| Overall Score | 91 | 91 | -- |
| Rank | #5 | #3 | GPT-5.2-Codex |
| Quality Rank | #5 | #3 | GPT-5.2-Codex |
| Adoption Rank | #5 | #3 | GPT-5.2-Codex |
| Parameters | -- | -- | -- |
| Context Window | 400K | 400K | -- |
| Pricing | $1.75/$14.00/M | $1.75/$14.00/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 100 | GPT-5.2 |
| Benchmarks | 89 | 89 | GPT-5.2 |
| Pricing | 86 | 86 | GPT-5.2 |
| Context window size | 89 | 89 | GPT-5.2 |
| Recency | 100 | 100 | GPT-5.2 |
| Output Capacity | 85 | 85 | 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%). Learn more about our methodology.
Scores 91/100 (rank #5), placing it in the top 99% of all 290 models tracked.
Scores 91/100 (rank #3), placing it in the top 99% of all 290 models tracked.
With only a 0-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.
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
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 (91/100) 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 GPT-5.2-Codex are extremely close in overall performance (only 0 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
0% 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 | GPT-5.2-Codex |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
OpenAI
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | GPT-5.2 | GPT-5.2-Codex |
|---|---|---|
| Context Window | 400K | 400K |
| Max Output Tokens | 128,000 | 128,000 |
| Open Source | No | No |
| Created | Dec 10, 2025 | Jan 14, 2026 |
Both GPT-5.2 and GPT-5.2-Codex score 91/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
GPT-5.2 is ranked #5 and GPT-5.2-Codex is ranked #3 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 GPT-5.2-Codex's $14.00/M output tokens - 1.0x more expensive. Input token pricing: GPT-5.2 at $1.75/M vs GPT-5.2-Codex at $1.75/M.
GPT-5.2 has a larger context window of 400,000 tokens compared to GPT-5.2-Codex's 400,000 tokens. A larger context window means the model can process longer documents and conversations.