DeepSeek-R1 Chat: pricing, context window and benchmarks
DeepSeek-R1 Chat is a multimodal model from DeepSeek. It offers a 400,000-token context window, costs $5.62 per million input tokens and $21.49 per million output tokens, and averages 82.4 across the index's benchmark suite.
Pricing
DeepSeek-R1 Chat costs $5.62 per million input tokens and $21.49 per million output tokens. A blended 3:1 input-to-output mix works out to about $9.59 per million tokens. Cached input is listed at $0.69 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $5.62 | per 1M tokens |
| Output | $21.49 | per 1M tokens |
| Cached input | $0.69 | per 1M tokens |
| Blended 3:1 | $9.59 | estimate per 1M tokens |
| 1M in + 1M out | $27.11 | estimate |
Benchmarks
Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 83.4 | 97 | 84th | |
| GPQA Diamond | 80.0 | 55 | 91th | |
| SWE-bench Verified | 71.7 | 80 | 87th | |
| HumanEval | 84.9 | 120 | 80th | |
| MATH-500 | 89.1 | 56 | 91th | |
| AIME 2025 | 78.6 | 106 | 82th | |
| LiveCodeBench | 79.3 | 50 | 92th | |
| IFEval | 89.5 | 76 | 87th | |
| TruthfulQA | 82.3 | 121 | 80th | |
| HellaSwag | 90.6 | 71 | 88th | |
| MMMU | 77.1 | 114 | 81th | |
| Arena Elo | 1433.3 | 112 | 81th |
What DeepSeek-R1 Chat is good for
DeepSeek-R1 Chat is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $5.62 per million input tokens, it sits in the mid-range of the index, and the 400,000-token context window is enough for large files and multi-file diffs.
Strengths
- Large 400,000-token context window for long documents and agent traces.
- Open weights make self-hosting, fine-tuning and data-residency review possible.
- Accepts more than text, including image input where the provider supports it.
- Reasoning-oriented profile, useful for multi-step problems and structured analysis.
- Coding benchmarks are a relative strength within its tier.
Trade-offs
- No standout weakness in the indexed specifications, but real-world behaviour still needs testing.
How it compares
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| DeepSeek-V3.2 Chat | DeepSeek | 1000000 | $5.80 | 82.5 |
| DeepSeek-R1 Chat | DeepSeek | 400000 | $5.62 | 82.4 |
| GPT-4.1 | OpenAI | 1000000 | $15.71 | 82.4 |
| Claude 3.7 Sonnet Turbo | Anthropic | 200000 | $15.56 | 82.3 |
| Kimi K2 Instruct | Moonshot AI | 1000000 | $5.80 | 82.3 |
| Kimi K2 Chat | Moonshot AI | 400000 | $5.74 | 82.1 |
FAQ
How much does DeepSeek-R1 Chat cost?
DeepSeek-R1 Chat is listed at $5.62 per million input tokens and $21.49 per million output tokens. Cached input is $0.69 per million tokens. A blended 3:1 input-to-output mix is about $9.59 per million tokens.
What is the context window of DeepSeek-R1 Chat?
DeepSeek-R1 Chat has a context window of 400,000 tokens and can emit up to 128,000 output tokens per request in this index.
Is DeepSeek-R1 Chat open weights?
Yes. DeepSeek-R1 Chat is listed as an open-weight model under a open weights licence.
How does DeepSeek-R1 Chat score on benchmarks?
DeepSeek-R1 Chat averages 82.4 across the scored benchmarks in this index, ranking #80 of 600 models. Its strongest relative result is Arena Elo at 1433.3.
What is DeepSeek-R1 Chat best for?
DeepSeek-R1 Chat is tuned toward coding work. It is a reasonable candidate for code generation, review, debugging and repository-scale tasks, especially when paired with a retrieval layer. At $5.62 per million input tokens, it sits in the mid-range of the index, and the 400,000-token context window is enough for large files and multi-file diffs.