GPT-5 Pro vs GPT-5.2
Benchmark Performance
Available Benchmarks
| Benchmark | GPT-5 Pro | GPT-5.2 |
|---|---|---|
| ARC-AGI-1verified-v1-b2e2a31b3d53 · verified_score · leader | 70.1781% of row best · percent · GPT-5 Pro | 86.17100% of row best · percent · GPT-5.2 (XHigh) |
| ARC-AGI-2verified-v2-326661568d5f · verified_score · leader | 18.3335% of row best · percent · GPT-5 Pro | 52.91100% of row best · percent · GPT-5.2 (XHigh) |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark wins | 2 benchmark winsOverall lead |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Technical Differences
Side-by-Side Facts
| Field | GPT-5 Pro | GPT-5.2 |
|---|---|---|
| Developer | OpenAI | OpenAI |
| Family | Gpt 5 | Gpt 5 2 |
| Model | GPT-5 Pro | GPT-5.2 |
| Version | GPT-5 Pro | GPT-5.2 |
| Lifecycle | active | active |
| Released | 2025-10-06 | 2025-12-11 |
| Knowledge cutoff | 2024-09-30 | 2025-08-31 |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 400,000 | 400,000 |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Openai (Standard), Openrouter (Standard) | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, reasoning, structured_outputs, tools |
15 comparable fields · 5 material differences · Pair passes the primary-source comparison gate
GPT-5 Pro Capabilities
GPT-5.2 Capabilities
Internal Comparison Graph
Related Comparisons
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|---|---|---|---|
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GPT-5.2OpenAI | vs | Qwen3 VL PlusQwen | cross-developer peersimage, text |
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Claude Sonnet 4.6Anthropic | vs | GPT-5.2OpenAI | cross-developer peersimage, text |
GPT-4oOpenAI | vs | GPT-5.2OpenAI | family variantsimage, text |
Seed 1.8ByteDance Seed | vs | GPT-5 ProOpenAI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
GPT-5 Pro vs GPT-5.2 FAQs
Is GPT-5 Pro or GPT-5.2 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both GPT-5 Pro and GPT-5.2, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, GPT-5 Pro or GPT-5.2?+
GPT-5 Pro is $7.50 and GPT-5.2 is $1.75 per million tokens, so GPT-5.2 is cheaper on this metric. GPT-5 Pro is $60.00 and GPT-5.2 is $14.00 per million tokens, so GPT-5.2 is cheaper on this metric.
Which has a larger context window, GPT-5 Pro or GPT-5.2?+
Neither model has a larger sourced context window in this comparison. GPT-5 Pro is 400,000 and GPT-5.2 is 400,000.
Which performs better in benchmarks, GPT-5 Pro or GPT-5.2?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can GPT-5 Pro or GPT-5.2 be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. GPT-5 Pro is not marked open weight; GPT-5.2 is not marked open weight.
Can GPT-5 Pro and GPT-5.2 understand images?+
GPT-5 Pro is documented with image input; GPT-5.2 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, GPT-5 Pro or GPT-5.2?+
GPT-5 Pro has the larger sourced maximum output: GPT-5 Pro supports 272,000 and GPT-5.2 supports 128,000 output tokens.
Do GPT-5 Pro and GPT-5.2 support reasoning and tool use?+
GPT-5 Pro: reasoning, tool calling, and image input. GPT-5.2: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, GPT-5 Pro or GPT-5.2?+
GPT-5 Pro has 2 sourced provider routes; GPT-5.2 has 2, a tie.
Which offers better value, GPT-5 Pro or GPT-5.2?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.