GPT-5.2 wins on coding (85 vs 84) and writing quality and context window (200K vs 128K). DeepSeek R1 wins on price ($0.55 vs $1.75/1M input). For most workflows, GPT-5.2 is the stronger default — capable but outclassed — gpt-5.4 is now cheaper and better.
The safest GPT-5.2 vs DeepSeek R1 default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
GPT-5.2 is the strongest answer here for GPT-5.2 vs DeepSeek R1 — pick it when quality of output matters more than the $1.75/1M/1M input you pay for it.
DeepSeek R1 handles the same job for about 83% less per token. Start here and only move up if the output is not good enough.
GPT-5.2 is the fastest of these for GPT-5.2 vs DeepSeek R1 — worth it when latency is what the reader notices, not the last few points of reasoning depth.
GPT-5.2 leads on coding with a score of 85 vs 84 for DeepSeek R1.
GPT-5.2 has the larger context window: 200K vs 128K for DeepSeek R1.
DeepSeek R1 is cheaper at $0.55/1M input tokens vs $1.75/1M for GPT-5.2.
Choose GPT-5.2 for serious coding and complex product work. Its coding and research scores are what carry the recommendation here.
Choose DeepSeek R1 when your work is mostly math and science — that is the workload it was tuned for.
DeepSeek R1 is the more cost-efficient option at $0.55/1M input — GPT-5.2 costs 3x more per input token, so the gap is worth taking seriously wherever token volume rather than peak quality drives the bill.
Switch the scoring lens to see whether the GPT-5.2 vs DeepSeek R1 answer changes when cost, speed, or long-document depth leads the decision.
OpenAI / Premium / Sep 3, 2026
Capable but outclassed — GPT-5.4 is now cheaper and better.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You're starting a new project — GPT-5.4 is cheaper and more capable.
Where the GPT-5.2 vs DeepSeek R1 recommendation shifts once you weigh price or latency differently.
Capable but outclassed — GPT-5.4 is now cheaper and better.
Open-source o1-class reasoning at a fraction of the cost.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| GPT-5.2OpenAI | $1.75/1M | $14.00/1M | $46 | 200k tokens | Balanced | 85 | 82 | 84 |
| DeepSeek R1DeepSeek | $0.55/1M | $2.19/1M | $9.88 | 128k tokens | Deliberate | 84 | 60 | 89 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for GPT-5.2 vs DeepSeek R1, what it is genuinely good at, and where we would steer you away from it.
Our pick for GPT-5.2 vs DeepSeek R1. It scores 85/100 on the coding axis we weight this page by, and nothing else in this shortlist matches it on output quality.
Reliable OpenAI flagship for serious coding and product work — a strong default before GPT-5.4 was released.
You're starting a new project — GPT-5.4 is cheaper and more capable.
Still capable but GPT-5.4 at $2.50/1M input is now cheaper and better. Hard to justify GPT-5.2 at $12/1M for new projects.
Full pricing, benchmark table and release notes on the GPT-5.2 page.
The cost-conscious pick for GPT-5.2 vs DeepSeek R1, about 83% less per token than GPT-5.2 than the top choice while holding 84/100 on coding.
Open-source reasoning model that matches o1-class performance on math, science, and complex coding at a fraction of the cost — the best open alternative to proprietary reasoning models.
Speed matters — R1's deliberate reasoning makes it wrong for interactive or high-throughput use cases.
The open-source reasoning model benchmark. If you need o1-class thinking at open-source pricing, nothing else competes.
Full pricing, benchmark table and release notes on the DeepSeek R1 page.
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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GPT-5.2 wins on more of the categories we score — coding, research, reasoning — so it is the better default of the two. DeepSeek R1 is the better pick when your work is mostly math and science. Neither is universally "better": GPT-5.2 is aimed at serious coding and complex product work, DeepSeek R1 at math and science.
DeepSeek R1 is cheaper at $0.55/1M input and $2.19/1M output. GPT-5.2 costs $1.75/1M input and $14/1M output.
GPT-5.2 has the larger context window at 200K tokens vs DeepSeek R1's 128K. For large document analysis, GPT-5.2 is the stronger pick.
GPT-5.2 is better for coding with a score of 85 vs DeepSeek R1's 84 (out of 100). GPT-6 Astra is the overall coding leader in this directory at 100/100.
GPT-5.2 is faster with a balanced speed rating (score: 3) vs DeepSeek R1's deliberate rating (score: 1). Speed matters most for interactive and high-throughput work; for batch jobs the DeepSeek R1 latency penalty is usually invisible.
Superseded by GPT-5.4 for most use cases. Claude Sonnet 4.6 leads on both coding and writing quality. Avoid it if you're starting a new project — GPT-5.4 is cheaper and more capable. That is the main case for looking at DeepSeek R1 instead.
Slow — deliberate reasoning takes significantly longer than standard models. Overkill for routine tasks where a faster model gets the same result. Same data sovereignty concerns as DeepSeek V3 for regulated industries. Avoid it if speed matters — R1's deliberate reasoning makes it wrong for interactive or high-throughput use cases. Against GPT-5.2 specifically, the gap shows up most on coding (85 vs 84).
Take a moderate workload of 10M input and 2M output tokens a month. GPT-5.2 runs $45.50 (at $1.75/1M in and $14/1M out); DeepSeek R1 runs $9.88 (at $0.55/1M in and $2.19/1M out). That is a $35.62/month difference — DeepSeek R1 is the cheaper of the two at this volume, and the gap scales linearly as you send more. Output tokens dominate the bill on both, so prompt length matters far less than response length.
Yes, and for most teams that beats picking one. A common split is GPT-5.2 for serious coding and complex product work, with DeepSeek R1 handling math and science. Routing high-volume, low-stakes calls to DeepSeek R1 at $0.55/1M and reserving GPT-5.2 for the hard cases is usually the cheapest arrangement that does not cost you quality.