Claude Fable 5 wins on coding (100 vs 84) and writing quality and context window (1M vs 128K). DeepSeek R1 wins on price ($0.55 vs $10/1M input). For most workflows, Claude Fable 5 is the stronger default — superseded by fable 5.1 — still 80.3% swe-bench pro, but 5.1 is better and cheaper to run.
The safest Claude Fable 5 vs DeepSeek R1 default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
Claude Fable 5 is the strongest answer here for Claude Fable 5 vs DeepSeek R1 — pick it when quality of output matters more than the $10.00/1M/1M input you pay for it.
DeepSeek R1 handles the same job for about 95% less per token. Start here and only move up if the output is not good enough.
Claude Fable 5 is the fastest of these for Claude Fable 5 vs DeepSeek R1 — worth it when latency is what the reader notices, not the last few points of reasoning depth.
Claude Fable 5 leads on coding with a score of 100 vs 84 for DeepSeek R1.
Claude Fable 5 has the larger context window: 1M vs 128K for DeepSeek R1.
DeepSeek R1 is cheaper at $0.55/1M input tokens vs $10/1M for Claude Fable 5.
Choose Claude Fable 5 for the hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning. Its coding and research 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 — Claude Fable 5 costs 18x 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 Fable 5 vs DeepSeek R1 answer changes when cost, speed, or long-document depth leads the decision.
Anthropic / Premium / Sep 1, 2026
Superseded by Fable 5.1 — still 80.3% SWE-Bench Pro, but 5.1 is better and cheaper to run.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You are starting new work — Claude Fable 5.1 supersedes it at the same base price with 75% cheaper cache reads. Also skip it if you are latency- or cost-sensitive.
Where the Claude Fable 5 vs DeepSeek R1 recommendation shifts once you weigh price or latency differently.
Superseded by Fable 5.1 — still 80.3% SWE-Bench Pro, but 5.1 is better and cheaper to run.
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 Fable 5Anthropic | $10.00/1M | $50.00/1M | $200 | 1M tokens | Deliberate | 100 | 98 | 100 |
| 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 Fable 5 vs DeepSeek R1, what it is genuinely good at, and where we would steer you away from it.
Ranked first here for Claude Fable 5 vs DeepSeek R1: 100/100 on coding, with the widest margin of anything in this line-up.
Anthropic's new Mythos-class flagship and the most capable coding model anyone can use — 80.3% SWE-Bench Pro, an 11-point jump over Opus 4.8. 1M context, 128K output, native parallel subagents. Released June 9, 2026.
You are starting new work — Claude Fable 5.1 supersedes it at the same base price with 75% cheaper cache reads. Also skip it if you are latency- or cost-sensitive.
Superseded by Claude Fable 5.1 on September 1, 2026, which beats it on every benchmark Anthropic published and costs less to run thanks to a 75% cache-read cut. Fable 5 remains a frontier-class model — 80.3% SWE-Bench Pro, an 11-point leap over Opus 4.8 — and stays available at the same $10/$50, but there is no reason to start new work on it.
Full pricing, benchmark table and release notes on the Claude Fable 5 page.
The value option for Claude Fable 5 vs DeepSeek R1: about 95% less per token than Claude Fable 5, at 84/100 on coding. 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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Claude Fable 5 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 Fable 5 is aimed at the hardest coding tasks and autonomous multi-step agents, DeepSeek R1 at math and science.
DeepSeek R1 is cheaper at $0.55/1M input and $2.19/1M output. Claude Fable 5 costs $10/1M input and $50/1M output.
Claude Fable 5 has the larger context window at 1M tokens vs DeepSeek R1's 128K. For large document analysis, Claude Fable 5 is the stronger pick.
Claude Fable 5 is better for coding with a score of 100 vs DeepSeek R1's 84 (out of 100). GPT-6 Astra is the overall coding leader in this directory at 100/100.
Claude Fable 5 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.
Priced at $10/$50 per 1M tokens — double Opus 4.8 ($5/$25). Deliberate pace; not for latency-sensitive interactive apps. Standard-use safeguards block some high-risk security workloads (use Mythos 5 with partner access). Avoid it if you are starting new work — Claude Fable 5.1 supersedes it at the same base price with 75% cheaper cache reads. Also skip it if you are latency- or cost-sensitive. 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 Fable 5 specifically, the gap shows up most on coding (100 vs 84).
Take a moderate workload of 10M input and 2M output tokens a month. Claude Fable 5 runs $200.00 (at $10/1M in and $50/1M out); DeepSeek R1 runs $9.88 (at $0.55/1M in and $2.19/1M out). That is a $190.12/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 Fable 5 for the hardest coding tasks and autonomous multi-step agents, with DeepSeek R1 handling math and science. Routing high-volume, low-stakes calls to DeepSeek R1 at $0.55/1M and reserving Claude Fable 5 for the hard cases is usually the cheapest arrangement that does not cost you quality.