Claude Opus 4.7 wins on coding (96 vs 84) and writing quality and context window (1M vs 128K). DeepSeek R1 wins on price ($0.55 vs $5/1M input). For most workflows, Claude Opus 4.7 is the stronger default — previous opus flagship, now superseded by claude opus 4.8 at the same price.
The safest Claude Opus 4.7 vs DeepSeek R1 default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
Claude Opus 4.7 is the strongest answer here for Claude Opus 4.7 vs DeepSeek R1 — pick it when quality of output matters more than the $5.00/1M/1M input you pay for it.
DeepSeek R1 handles the same job for about 91% less per token. Start here and only move up if the output is not good enough.
Claude Opus 4.7 is the fastest of these for Claude Opus 4.7 vs DeepSeek R1 — worth it when latency is what the reader notices, not the last few points of reasoning depth.
Claude Opus 4.7 leads on coding with a score of 96 vs 84 for DeepSeek R1.
Claude Opus 4.7 has the larger context window: 1M vs 128K for DeepSeek R1.
DeepSeek R1 is cheaper at $0.55/1M input tokens vs $5/1M for Claude Opus 4.7.
Claude Opus 4.7 is the safer default: it is built for highest-ceiling coding, agentic workflows, and deep research, which covers most of what people bring to this comparison.
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 — Claude Opus 4.7 costs 9x 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 Claude Opus 4.7 vs DeepSeek R1 answer changes when cost, speed, or long-document depth leads the decision.
Anthropic / Premium / May 27, 2026
Previous Opus flagship, now superseded by Claude Opus 4.8 at the same price.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need cheaper high-volume throughput, image generation, or a workflow that must stay inside OpenAI tooling.
Where the Claude Opus 4.7 vs DeepSeek R1 recommendation shifts once you weigh price or latency differently.
Previous Opus flagship, now superseded by Claude Opus 4.8 at the same price.
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 |
|---|---|---|---|---|---|---|---|---|
| Claude Opus 4.7Anthropic | $5.00/1M | $25.00/1M | $100 | 1M tokens | Deliberate | 96 | 93 | 95 |
| 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 Claude Opus 4.7 vs DeepSeek R1, what it is genuinely good at, and where we would steer you away from it.
Ranked first here for Claude Opus 4.7 vs DeepSeek R1: 96/100 on coding, with the widest margin of anything in this line-up.
Anthropic's previous Opus flagship, now superseded by Opus 4.8. Still the second-best coding model publicly available at the same $5/$25 price.
You need cheaper high-volume throughput, image generation, or a workflow that must stay inside OpenAI tooling.
Superseded by Opus 4.8 (May 27, 2026) which scores 69.2% SWE-Bench Pro vs 64.3% here — at the same price. For existing pinned integrations Opus 4.7 still works well, but new deployments should use Opus 4.8.
Full pricing, benchmark table and release notes on the Claude Opus 4.7 page.
Where most budgets should land for Claude Opus 4.7 vs DeepSeek R1 — about 91% less per token than Claude Opus 4.7, and still 84/100 on the coding axis.
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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Claude Opus 4.7 wins on more of the categories we score — coding, research, long context — 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": Claude Opus 4.7 is aimed at highest-ceiling coding and agentic workflows, DeepSeek R1 at math and science.
DeepSeek R1 is cheaper at $0.55/1M input and $2.19/1M output. Claude Opus 4.7 costs $5/1M input and $25/1M output.
Claude Opus 4.7 has the larger context window at 1M tokens vs DeepSeek R1's 128K. For large document analysis, Claude Opus 4.7 is the stronger pick.
Claude Opus 4.7 is better for coding with a score of 96 vs DeepSeek R1's 84 (out of 100). GPT-6 Astra is the overall coding leader in this directory at 100/100.
Claude Opus 4.7 is faster with a deliberate speed rating (score: 2) 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.
Opus 4.8 launched at the same $5/$25 price with 69.2% SWE-Bench Pro and parallel subagents. No reason to prefer Opus 4.7 for new integrations — use Opus 4.8 instead. Avoid it if you are starting a new integration — Opus 4.8 is strictly better at the same price. 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 Claude Opus 4.7 specifically, the gap shows up most on coding (96 vs 84).
Take a moderate workload of 10M input and 2M output tokens a month. Claude Opus 4.7 runs $100.00 (at $5/1M in and $25/1M out); DeepSeek R1 runs $9.88 (at $0.55/1M in and $2.19/1M out). That is a $90.12/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 Claude Opus 4.7 for highest-ceiling coding and agentic workflows, with DeepSeek R1 handling math and science. Routing high-volume, low-stakes calls to DeepSeek R1 at $0.55/1M and reserving Claude Opus 4.7 for the hard cases is usually the cheapest arrangement that does not cost you quality.