Claude Opus 4.6 vs DeepSeek-R1
Anthropic vs DeepSeek · Prices checked 12 August 2026
On blended cost DeepSeek-R1 undercuts Claude Opus 4.6 by about 10.6×: $1.04 per million tokens versus $11.00. A single 100K-input, 10K-output job costs $0.077 on DeepSeek-R1 against $0.750 on Claude Opus 4.6.
Of the 6 shared benchmarks, Claude Opus 4.6 takes 4. The widest gap is on SWE-bench Verified, where Claude Opus 4.6 leads by 23 points. On context, Claude Opus 4.6 is the larger at 1,000,000 tokens versus 64,000.
Pricing and capacity
| Metric | Claude Opus 4.6 | DeepSeek-R1 | Difference |
|---|---|---|---|
| Input / 1M tokens | $5.00 | $0.550 | 9.1× |
| Output / 1M tokens | $25.00 | $2.19 | 11.4× |
| Blended · 70/30calculated | $11.00 | $1.04 | 10.6× |
| Blended · 50/50calculated | $15.00 | $1.37 | 10.9× |
| Blended · 80/20calculated | $9.00 | $0.878 | 10.3× |
| Blended · 20/80calculated | $21.00 | $1.86 | 11.3× |
| Job cost · 100K + 10Kcalculated | $0.750 | $0.077 | 9.8× |
| Job cost · 1M + 100Kcalculated | $7.50 | $0.769 | 9.8× |
| Context window | 1,000,000 | 64,000 | 15.6× |
Input and output rates are as published by each provider. Blended and job-cost rows are calculated comparison metrics, not published prices — how they are derived.
Benchmarks
| Benchmark | Claude Opus 4.6 | DeepSeek-R1 | Leader |
|---|---|---|---|
| MMLU | 88% | 90% | DeepSeek-R1 |
| GPQA Diamond | 79% | 71% | Claude Opus 4.6 |
| MATH | 92% | 95% | DeepSeek-R1 |
| HumanEval | 95% | 90% | Claude Opus 4.6 |
| SWE-bench Verified | 72% | 49% | Claude Opus 4.6 |
| LMArena Elo | 1378 Elo | 1361 Elo | Claude Opus 4.6 |
Only suites both models report are listed, so a missing score is never shown as a loss. Figures are provider-published or from public leaderboards and are not independently re-run.
What each model is for
Claude Opus 4.6
Anthropic · Previous
The flagship of the Claude 4 generation. 1M-token context is GA, and Opus 4.6 leads on agentic coding, long-horizon reasoning and tool-use reliability.
- Agentic coding (Claude Code)
- 1M-token context, GA
- Tool use & function calling
- Multi-step reasoning
DeepSeek-R1
DeepSeek · Reasoning
Open-weights reasoning model with chain-of-thought trained via RL. Comparable to o1 on math benchmarks at a fraction of the price.
- Open-weights reasoning
- Visible chain-of-thought
- Math & code
- Cheap
Frequently asked questions
Which is cheaper, Claude Opus 4.6 or DeepSeek-R1?
On blended cost DeepSeek-R1 undercuts Claude Opus 4.6 by about 10.6×: $1.04 per million tokens versus $11.00. A single 100K-input, 10K-output job costs $0.077 on DeepSeek-R1 against $0.750 on Claude Opus 4.6. Blended cost weights input at 70% and output at 30%; price your own token split for an exact answer, since the cheaper model on a blended basis is not always cheaper for your workload.
Which performs better, Claude Opus 4.6 or DeepSeek-R1?
Of the 6 shared benchmarks, Claude Opus 4.6 takes 4. The widest gap is on SWE-bench Verified, where Claude Opus 4.6 leads by 23 points. These are the figures each provider or public leaderboard publishes, not results we re-run, and a benchmark average can hide the specific behaviour your workload depends on.
Which has the larger context window, Claude Opus 4.6 or DeepSeek-R1?
On context, Claude Opus 4.6 is the larger at 1,000,000 tokens versus 64,000. The context window caps everything in a single request: prompt, retrieved documents, conversation history and the model’s own output all share it.
Can I compare Claude Opus 4.6 and DeepSeek-R1 on my own numbers?
Yes. Open both in the side-by-side comparison tool to see every field at once, or use the token calculator to price your actual prompt and monthly request volume against each model. Both are free and need no sign-up.
Price it for your own workload
Related matchups
Terms used on this page
Prices and scores are recomputed on every deploy from the catalogue. Prices checked 12 August 2026.