DeepSeek R1 wins on coding (84 vs 80) and price ($0.55 vs $2/1M input). Gemini 3.1 Pro wins on writing quality and context window (2M vs 128K). For most workflows, Gemini 3.1 Pro is the stronger default — best for research and deep document analysis — 2m context at the best premium price.
The safest DeepSeek R1 vs Gemini 3.1 Pro default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
Gemini 3.1 Pro is the strongest answer here for DeepSeek R1 vs Gemini 3.1 Pro — pick it when quality of output matters more than the $2.00/1M/1M input you pay for it.
DeepSeek R1 handles the same job for about 80% less per token. Start here and only move up if the output is not good enough.
Gemini 3.1 Pro is the fastest of these for DeepSeek R1 vs Gemini 3.1 Pro — worth it when latency is what the reader notices, not the last few points of reasoning depth.
DeepSeek R1 leads on coding with a score of 84 vs 80 for Gemini 3.1 Pro.
Gemini 3.1 Pro has the larger context window: 2M vs 128K for DeepSeek R1.
DeepSeek R1 is cheaper at $0.55/1M input tokens vs $2/1M for Gemini 3.1 Pro.
Choose Gemini 3.1 Pro for research, deep document analysis, and long-context reasoning at competitive pricing. Its research and long context scores are what carry the recommendation here.
DeepSeek R1 earns its place when your work is mostly math and science, even though it loses the overall count here.
DeepSeek R1 is the more cost-efficient option at $0.55/1M input — Gemini 3.1 Pro costs 4x 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 DeepSeek R1 vs Gemini 3.1 Pro answer changes when cost, speed, or long-document depth leads the decision.
Google / Premium / Sep 2, 2026
Best for research and deep document analysis — 2M context at the best premium price.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
Your primary use case is writing quality or agentic coding — Claude wins both.
Where the DeepSeek R1 vs Gemini 3.1 Pro recommendation shifts once you weigh price or latency differently.
Open-source o1-class reasoning at a fraction of the cost.
Best for research and deep document analysis — 2M context at the best premium price.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| Gemini 3.1 ProGoogle | $2.00/1M | $12.00/1M | $44 | 2M tokens | Balanced | 80 | 82 | 99 |
| 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 DeepSeek R1 vs Gemini 3.1 Pro, what it is genuinely good at, and where we would steer you away from it.
Ranked first here for DeepSeek R1 vs Gemini 3.1 Pro: 99/100 on research, with the widest margin of anything in this line-up.
Google's flagship with the largest context window of any frontier model at 2M tokens, Deep Think reasoning, and the best price-to-performance among premium models.
Your primary use case is writing quality or agentic coding — Claude wins both.
The best research and long-context model available. Handles entire codebases, legal documents, and large datasets in a single pass — at a lower price than GPT-5.4 or Claude Sonnet 4.6.
Full pricing, benchmark table and release notes on the Gemini 3.1 Pro page.
The value option for DeepSeek R1 vs Gemini 3.1 Pro: about 80% less per token than Gemini 3.1 Pro, at 89/100 on research. Worth starting here and moving up only if the output disappoints.
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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Gemini 3.1 Pro wins on more of the categories we score — research, long context, 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": Gemini 3.1 Pro is aimed at research and deep document analysis, DeepSeek R1 at math and science.
DeepSeek R1 is cheaper at $0.55/1M input and $2.19/1M output. Gemini 3.1 Pro costs $2/1M input and $12/1M output.
Gemini 3.1 Pro has the larger context window at 2M tokens vs DeepSeek R1's 128K. For large document analysis, Gemini 3.1 Pro is the stronger pick.
DeepSeek R1 is better for coding with a score of 84 vs Gemini 3.1 Pro's 80 (out of 100). GPT-6 Astra is the overall coding leader in this directory at 100/100.
Gemini 3.1 Pro 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.
Slower than Flash for everyday lightweight tasks. Claude Sonnet 4.6 is better for writing quality. Avoid it if your primary use case is writing quality or agentic coding — Claude wins both. 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 Gemini 3.1 Pro specifically, the gap shows up most on coding (80 vs 84).
Take a moderate workload of 10M input and 2M output tokens a month. DeepSeek R1 runs $9.88 (at $0.55/1M in and $2.19/1M out); Gemini 3.1 Pro runs $44.00 (at $2/1M in and $12/1M out). That is a $34.12/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 Gemini 3.1 Pro for research and deep document analysis, with DeepSeek R1 handling math and science. Routing high-volume, low-stakes calls to DeepSeek R1 at $0.55/1M and reserving Gemini 3.1 Pro for the hard cases is usually the cheapest arrangement that does not cost you quality.